Land use change in rapidly developing economies – A case study on land use intensification and land fallowing in Kerala, India

Land use change in rapidly developing economies – A case study on land use intensification and land fallowing in Kerala, India | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Land use change in rapidly developing economies – A case study on land use intensification and land fallowing in Kerala, India Akshara Thekkeyil, Shijo Joseph, Fathima Abdurazak, Giby Kuriakose, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2164710/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The land use/land cover change is a local driver of environmental change having cascading impacts and implications at the global level and therefore requires appreciable consideration when perceived from sustainability perspectives. Kerala, the southernmost state of India has undergone a dramatic transition from a traditional agrarian economy to a modern thriving economy involving the irrational exploitation of natural resources, precisely, land and its components. The present study addresses how land is being changed along an urbanization gradient in the most agglomerative city in the state, Kochi, during the last one and half decades. High-resolution remote sensing data available from the Google Earth Engine pertaining to the four time periods, i.e., 2005, 2010, 2015, and 2020, representing urban, suburban, and rural areas, were analysed to estimate the changes in land use land cover. A semi-structured interview was conducted at the household level to identify the major drivers of land use change. The results indicated the presence of two major and divergent trends; the first one is the intensification of land use activities at the rate of 1.37% per annum, primarily driven by urbanization and infrastructure developments, and the second one is the fallowing and abandonment of land (at the rate of 0.21% per annum) driven by the increased cost of cultivation and unexpected changes in meteorological events frequently reported in the recent history of Kerala. The rates of change are more prominent in the rural areas while the urban grids are nearing saturation occupying nearly two-third of the area with urban features at the expense of greenery. Though the progression with respect to urbanization and infrastructure developments is expected, the fallowing and abandonment of land is unanticipated, raising serious questions in the developmental pathways to achieve Sustainable Development Goals in the State of Kerala. Remote Sensing Land use/land cover change Land Fallowing and Abandonment Sustainable Development Goals Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Land is a critical natural resource pivotal for the sustenance of life on earth. However, the immoderate upsurge in population resulted in the unsustainable and indiscriminate utilisation of land. Drastic changes in land use/land cover (LU/LC) have occurred over the years, for which the anthropogenic contribution is undeniable (Lambin et al., 2001 ; Rawat and Kumar, 2015 ; Liping et al., 2018 ; Song et al., 2018 ). Human-induced LU/LC changes have reduced the capacity of soil to store carbon, increasing soil bulk density (Sasmito et al., 2019 ) and leading to global warming through enhanced greenhouse gas emissions (Muñoz-Rojas et al. , 2012). A significant reduction in the quality of groundwater and surface water was identified in relation to the changing land use pattern (Mishra et al., 2014 ; Kumar et al., 2019 ; Zanotti et al., 2019 ; Ahmad et al., 2021 ). Other ecological consequences of LU/LC change include biodiversity loss, alterations in the biogeochemical cycles, land degradation, and so on (Zhao et al., 2006 ; Allan et al., 2015 ; Song et al., 2018 ). The conversion of lands in association with urbanisation and industrialization has led to land scarcity for agriculture, thereby posing a serious threat to food security (Chen, 2007 ; Pandey and Seto, 2015 ). The rapidly developing economies are predominantly under the brunt of this trend compared to the developed nations now and are driven by the complex connections of various social, demographic, economic, cultural, institutional, technological, and meteorological parameters (Lambin and Meyfroidt, 2011 ). Kerala, the state located on the southwestern end of the Indian subcontinent, is undergoing a transition from a traditional backward agrarian economy to a modern flourishing economy (Shinoj, 2015 ). The structural transformation that the state witnesses comprise four characteristics including a reduced share of agriculture in employment generation and economic development, enhanced share of industries and other sectors in the economy, increased rural to urban migration in search of jobs (Shinoj, 2015 ), and a demographic transition in the rates of birth and death leading to an increase in population prior to arriving at an equilibrium state (Sanitha, 2015 ). As a result, two major and divergent trends are being observed in the recent land use history of Kerala. The first one is an intensification of human activities and sprawling of urban centres along the urban-rural continuum (Kumar, 2005 ), and the second one is the fallowing and abandonment of land due to low economic return in the agricultural sector compared to other sectors. During early 2000s, Kochi urban agglomeration was the only city having more than a million population of the 18 urban agglomerations, but by 2011, it increased to seven cities, namely, Kozhikode, Thrissur, Malappuram, Thiruvananthapuram, Kannur and Kollam. Between 2001 and 2011, there has been a dramatic increase in the urban population owing to the reclassification of numerous rural areas to urban (i.e., into census towns), and there has been rapid increment of census towns from 99 in 2001 to 461 in 2011, i.e., an increase of almost 366% (Thaickavil, 2020 ). The urbanisation witnessed in Kerala is different from other parts of the country as it is characterised not just by the migration of rural population to urban areas (Bhagat, 2011 ), yet additionally a decrease in the area of agricultural fields and their conversion for other economic activities (Thomas, 2017 ). On the other hand, the drastic reduction of human labour and the increase in the labour cost leaves much of the marginal lands to the process of fallowing and abandonment (Sreya and Vidhyavathi, 2018 ). Recently, the aspirant young populations tend to migrate to metro cities and major towns in search of white- and blue-collar jobs kept no or less human resources for agricultural practices, resulting in a surge in labour costs in the rural areas (Jose and Padmanabhan, 2015 ). Extreme climatic events, and changes in the weather patterns have increased the risk of marginalised farmers, acting as an impetus that pace up the land diversion to other economically profitable land uses or leaving the land uncultivated. Though various laws were introduced to enhance the agricultural sector, it was found beneficial only to rich and influential farmers leaving behind marginal farmers, forcing them to leave the land fallow (Viswanathan, 2014 ). Land abandonment can be a significant deterrent to attaining Sustainable Development Goals (SDGs) primarily goals 1 (no poverty), 2 (zero hunger) and 3 (good health and well-being) (Hobbs and Cramer, 2007 ; Plieninger et al., 2014 ; Filho et al., 2016 ; Mbow et al., 2019 ). Currently, the land use in growing economies like Kerala can be sketched along the gradient of transitioning from rural to urban landscapes with varying characteristics (Fig. 1 ). Firstly, the commercial business and urban centers where intensive human activities take place, the price of the land shoot up in no time. The city/urban centers and the roadways of the major national and state highways are examples of such areas. These regions have high population density alongside corresponding infrastructures in association with the increasing rate of urbanization. The second one is the suburban area where a transition from rural to urban is expected in the near future. Such areas are predominantly characterized by small holder land use systems with houses, homesteads, and small-scale industries/business establishments. The level of human activities in those areas are medium and the prices of land are more or less same or slightly on the upward side over the years. The third represents predominantly agricultural landscapes in the rural areas where the level of human interventions on land is low compared to the urban and suburban areas and characterized by lower population density and less economic activities. The low economic returns compared to investment in agriculture makes such areas less attractive for investors, and the price of the land is on a negative trend. The impending danger of land fallowing, and the resultant land abandonment is threatening the very existence of agricultural sustainability in those areas. Our present study aims to develop empirical evidence of changes in land use along the rural to urban continuum in a rapidly developing city of Kerala, Kochi, over the last one and half decades. The study also addresses the major factors that drive the changes in land use, both land use intensification, and land fallowing. 2. Materials And Methods 2.1. Study area The study was carried out in the most populous metropolitan city in Kerala, i.e., Kochi, also known as the industrial, financial and economic capital of Kerala (Fig. 2). The city comprises an area of 87.5 square kilometer with its major portion lying at the sea level and having a coastline of 48 km. The city has a larger network of backwaters enveloping the northern tip of the peninsula, various islands and the mainland. Laccadive sea is present at the west while the eastern region comprises the urban mainland. The urban agglomeration population marked tremendous growth with the number rising from 0.8 million to 2.1 million from the year 1981 to 2011. The region has a flat elevation with a warm and humid climate having a temperature range between 20 o C to 35 o C (Murali and Kumar, 2015 ). The average annual rainfall is 3100 mm with 132 average annual rainy days. The economic growth of the city began with the economic reforms brought about by the Central government during the early 1990s. The service sector played a central role in boosting the economy with the establishment of numerous IT parks and port-based infrastructures which triggered the construction and developmental boom in the city. Kochi witnessed rapid commercialisation over the years and has now developed into the commercial hub of Kerala (Ernakulam District Administration, 2021 ) primarily because of an all-weather harbour, good quality water, and access to cheap hydro-electric power (George and Rajan, 2015 ). 2.2. Remote Sensing Data Analysis The remote sensing and GIS analysis was carried out in Google Earth Pro (GEP) as well as ArcGIS ver 25.1 (ESRI 2021). Headquarters of the Cochin Corporation was taken as the center point of the study, around which 10, 20 and 30km buffers were created to represent urban, suburban and rural areas respectively. The buffered area was then gridded into 1km grids using a fishnet grid in ArcGIS for its delineation into urban, suburban, and rural grids. Intensive study grids were randomly selected and time-series satellite data for these grids for the years 2005, 2010, 2015 and 2020 were analysed using GEP. Special care was given to opt data which are cloud free, clear and geometrical registration error is less than one pixel. Manual digitization was done in these grids for these years by fixing an eye elevation of 50m in GEP. For digitizing the data, various classes like buildings, mixed orchards, water bodies, tarred roads, muddy roads, railway tracks, barren areas, fallow lands, and paddy fields were considered depending on the respective grid. As the digitization was done manually, the chances of occurrence of errors were high, thus topology was run. Topology is generally used to display topological relationships, exceptions, and errors. LU/LC maps for the years 2005, 2010, 2015 and 2020 were obtained post error correction which was further used for the analysis of changes that occurred over the years. 2.3. Household Survey Ground truthing and household survey was carried out to validate whether the changes detected in the remote sensing analysis over the years is consistent with the actual ground situation. A semi-structured interview at the household level was conducted in the grids pertaining to Vyttila in the urban area, Edathala in the suburban area, and Maravanthuruthu in the rural area. The survey was limited to those households who have been residing in the region for at least 20 years or more. Ten such households from each urban, suburban, and rural areas were surveyed randomly during the period August to November 2021. The questionnaire included sessions on how the land use changed over the years, and what were the major reasons for the change in those areas. A priori list of drivers of land use change was prepared in consultation with academicians, researchers, and practitioners. The drivers included were urbanization and infrastructure development, industrialization, uncertain markets and less profitability from agriculture produce, labour availability and increased cost of labour, soil degradation and reduced fertility of the soil, values, beliefs, less interest and lack of respect in agriculture as a profession, migration of youth to urban areas in search of white and blue-collar jobs, unexpected rain, flood, drought, and other meteorological events, absence of government-backed schemes, policies and support, and absence of science-driven practices in agriculture sector. The responses were recorded on paper and then entered separately in excel worksheets for further analyses. The flow chart depicting the entire methodology is given in Fig. 3 . 3. Results In general, of the 900 ha of the study area, buildings have shown an increasing trend in all the 3 regions where the initial value of 139 ha rose to 227 ha by 2020 (i.e., 15–25% of the total geographical area studied) with drastic changes happening in the urban area. The mixed vegetation showed a decreasing trend from 547.1 ha in 2005 (i.e., 61% of the geographical area) to 467.3 ha in 2020 (i.e., 52% of the area), particularly in the urban grids as a result of the expansion in buildings. The case of paddy fields is similar to that of mixed orchards in terms of the decrease in the area with the change being highly critical in certain suburban and rural areas. It was found that the area occupied by paddy fields diminished from 155 ha to 111 ha by 2020. When fallow lands are taken into consideration, they have shown an increasing trend in rural and suburban areas. The value expanded to 29 ha by 2020 from nearly zero in 2005. 3.1. LU/LC Change in Urban Areas While considering the case of the urban area, of the total area of 300 ha (Table 1 and Fig. 4 ), 124 ha of land were occupied by buildings in 2005 which expanded to 174 ha by 2020, i.e., an increment of almost 16.6%. Mixed vegetation occupied an area of 145 ha in 2005 which decreased to 93 ha by 2020, a reduction of 17.3% while the water bodies decreased from 9 ha to 8 ha by 2010 and thereafter remained the same until 2020. The urban area witnessed an expansion of tarred roads from 14 ha in 2005 to 19 ha by 2020, almost an increment of 1.6%. During the initial years, 1ha of land were muddy roads, which reduced to zero by 2020 as all the muddy roads got converted to tarred roads as a part of urban development. The changes in other land cover classes were nominal. Of the three study areas, the Vyttila grid showed maximum land area conversion between 2005 and 2020. Table 1 Land use/ land cover change in urban area from 2005–2020 in hectares LULC YEAR 2005 2010 2015 2020 Mixed vegetation 145 128 108.6 93 Buildings 124 140 159 174 Muddy roads 1 1 - - Tarred roads 14 16 19 19 Railway track 1 1 1 1 Other barren areas 6 6 4.4 5 Waterbody 9 8 8 8 TOTAL 300 300 300 300 3.2. LU/LC Change in Suburban Areas On account of the suburban area, the area occupied by buildings was only 7 ha in 2005 which increased to 25 ha by 2020 (i.e., an increase of 6%). The mixed vegetation showed a slight increase from 199.6 ha in 2005 to 203.4 ha by 2010, but thereafter the area shrank to 189.4 ha by 2020. In the suburban area, paddy cultivation exhibited a diminishing pattern over the last one and half decades. In 2005, 85 ha of land were devoted to paddy which declined to 63 ha by 2020, a change of about 7.3% net reduction in area was observed. In the case of fallow lands, there were no fallow lands at the beginning of the study period which got increased to 12 ha by 2020 (i.e., 4% of the area studied). Tarred roads had undergone an escalation from 4 ha to 8 ha during 2005 to 2020. In 2005, 2 ha of muddy roads were found which gradually decreased to 0.2 ha by 2020. Classes like buildings, mixed orchards, paddy fields, and fallow lands had witnessed major changes in terms of area of occupancy, primarily in the grid pertaining to Edathala which was once an agrarian region as it is clearly visible from Table 2 and Fig. 5 . Table 2 Land use/ land cover change in suburban area from 2005–2020 in hectares. LULC YEAR 2005 2010 2015 2020 Mixed vegetation 199.6 203.4 196.46 189.4 Paddy fields 85 70 67 63 Buildings 7 12 17 25 Fallow lands - 8 10 12 Muddy roads 2 0.2 0.14 0.2 Tarred roads 4 5 5 8 Other barren areas 2 1 3 2 Waterbody 0.4 0.4 0.4 0.4 TOTAL 300 300 300 300 3.3. LU/LC Change in Rural Areas A positive trend in the area of buildings was witnessed in the rural areas. The buildings expanded to 28 ha in 2020 from 8 ha in 2005, i.e., an expansion of 6.6%. While the extent of mixed vegetation is decreased to 184.9 ha by 2020 from 202.5 ha in 2005. A drastic decline in the area of paddy fields was also observed from 2005 to 2020, i.e., a decrease from 70 ha to 48 ha which is close to 7.3% in the net area. This was very prominent in the grid pertaining to Nedumbasserry. The fallow lands also showed a sharp increase in the extent of the area from zero to 17 ha in the last one and half decades (i.e., approximately 6% of the total geographical area studied in the category of rural is fallowed currently), indicating serious consequences on the agricultural sector. Tarred roads expanded from 2 ha to 6 ha during 2005 to 2020. Critical changes had taken place in the case of paddy fields, fallow lands, mixed orchards and buildings (Table 3 and Fig. 6 ). Table 3 Land use/ land cover in rural area from 2005–2020 in hectares. LULC YEAR 2005 2010 2015 2020 Mixed vegetation 202.5 194 191.8 184.9 Paddy field 70 61 57 48 Building 8 16 22 28 Fallow land - 9 10 17 Muddy road 0.5 1 0.2 0.1 Tarred road 2 4 4 6 Other barren area 4 3 3 4 Waterbody 11 10 10 10 Railway track 2 2 2 2 TOTAL 300 300 300 300 3.4. Rate of change in land use intensification and fallowing The buildings, roads and railways constituted only 47% in the urban area in 2005 which was increased to 65% by 2020 (i.e., an increase of 18%). The annual rate of change was 1.2%. No fallowing was observed in the urban areas. For the suburban areas, buildings and other infrastructures accounted for 4.3% in 2005 which was increased to 5.7% in 2010, 7% in 2015, and 11% in 2020. Annually, the rate of change observed was 0.84% from 2005 to 2010, 0.99% from 2010 to 2015, and 2.21% from 2015 to 2020, averaging an annual rate of land use intensification of 1.35%. When considering the case of land fallowing, no fallow or abandoned agriculture areas were observed in 2005 whereas this rose to 12 ha in 2020 (4% of the suburban study area). The annual rate of land fallowing was 0.27% in 15 years. A similar trend in land use intensification and land fallowing was observed in the rural areas as well. During 2005, the land occupied by buildings, railways and roads in the rural areas was only 4% which was increased to nearly 12% in 2020, almost three times the initial value. Annually, the land use intensification activities and the resultant conversion were at the pace of 1.57%. The fallowing of the land was also prominent in the rural grids where 5.67% of the total area was kept fallowed or abandoned in the year 2020 from nil at the beginning of the study period. The rate of fallowing was 0.38% per annum. Altogether, the urban, suburban, and rural grids in the study area showed the land use intensification activities at the rate of 1.37% per annum and land fallowing and abandonment at the rate of 0.21% per annum. 3.4. Drivers of LU/LC Change All the major factors that contributed to the LU/LC change in the study area, specifically in urban, suburban, and rural areas are presented in Fig. 7 . In the urban area, urbanisation and infrastructure development showed the highest-ranking in LULC changes. This was followed by the migration of youth in search of white and blue-collar jobs, and the changes in the values, beliefs, less interests and lack of respect to agriculture as a profession. All the respondents were of the opinion that the policies developed by the government had nothing to do with the stagnation of the agricultural sector. The factor that received the lowest ranking was industrialisation, indicating the irrelevance of industrial development in LU/LC change in the highly populated urban grids. The case of suburban areas reveals the pertinence of labour availability and increased labour cost in changing the land use pattern. Uncertain markets and less profitability from agricultural produce emerged as second ranking. Lack of interest, changing values, beliefs, and lack of respect for agriculture as a profession alongside large-scale migration of individuals to urban areas in search of other demanding jobs were ranked third and fourth respectively. Urbanisation and infrastructural development received the fifth ranking. Similar to urban areas, factors related to the quality of soil, meteorological parameters, government policies, science-driven practices, and industrialisation obtained lower ranks. In the rural area, the most critical factor that drove the LULC change was unexpected rain, flood, drought, and other meteorological events. Uncertain market and reduced profit was the second highest while shortages in the availability of labour and labour costs gained the third highest ranking. The fourth and fifth ranking was given for the factors related to changing values of youth and their subsequent migration to urban centres respectively. Similar to urban and suburban areas, all other factors played only nominal roles in LU/LC change. 4. Discussion Momentous changes have taken place in LU/LC in the study area over the years in terms of intensification of land use activities as well as fallowing of lands. The rate at which urbanisation as well as infrastructural development is taking place in Kochi is surprisingly high that side-lines several traditional practices and results in changes or abandonment of natural habitats even in the peri-urban areas of Kochi. More than one-third of the land cover grids considered for the present study is now constituted by urban features, leaving little land for vegetation, and other land covers. The fallowing and abandonment of land was not found in the urban grids as every piece of the land is worth of thousands of dollars and is under the radar of the lucrative real-estate business. The growth of the urban consumer class has a close relationship with land use change which is greatly influenced by the globalized flow of people, capital, commodities, and so on (Meyfroidt et al., 2013 ). The pace at which land utilization changes in the rural and suburban grids is also remarkable. During the early 2000s, agriculture was a major source of income for individuals dwelling in suburban and rural areas. A major portion of the land in these regions was devoted to paddy cultivation along with the cultivation of other crops like rubber, coconut, nutmeg, and so on. Over the years, agriculture lost its charm as a source of living which prompted its conversion to other purposes. People likewise lost interest in agriculture due to abridged profit from agricultural produce alongside uncertain markets which ultimately led to their migration to urban agglomerations in search of white- and blue-collar jobs. These results are well aligned with the global literature that uncertain markets, less profitability, urbanization, infrastructural expansion, migration of rural population to urban areas, lack of enough employment in rural areas, and attitudes, values, beliefs, and individual perceptions of people primarily drive changes in agricultural practices, and the land system dynamics (Oslon et al., 2004 ; Benayas et al., 2007 ; Lasanta et al., 2017 ; Ranganathan and Pandey, 2018 ; Castro et al., 2020 ; Chaudhary et al., 2020 ). Similarly, extreme weather conditions and the periodic occurrence of floods in the recent history of Kerala have aggravated the situation which forced the farmers to leave their land fallow as the recurring losses were dreadful and irrevocable. The present study reveals that agriculture is losing its aesthetic as well as economic value, persuading increased dependence on other Indian states for meeting the dietary requirements. A large portion of people in suburban, as well as rural regions, are unable to do cultivation on their lands due to reduced availability of labour as well as increased labour cost even after having the desire to do cultivation. This trend is actually forcing them to leave their land fallow. A greater number of farmers gave it their best attempt to continue cultivation on their land yet continuous yield and profit loss constrained them to refrain from cultivation. Likewise, with the development of corporate jobs with higher pay and living standards, the youth got attracted to it, losing interest in cultivation, leaving behind agriculture as a source of income and consequently permitting their land to fallow. This further prompted the migration of suburban and rural population to cities for a better standard of living and thus posing a serious problem in the agri-labour market in Kerala. Despite the fact that there was large-scale migration of immigrants from other Indian states, they weren’t found fit to do cultivation on these lands as they came from an entirely different cultural and linguistic background (Priya et al., 2018 ) with different skills other than the agriculture practices in the study area. Though institutional factors like lack of appropriate land use policies were considered insignificant factors in LU/LC change, there were situations which depicted its inability to forestall the fallowing of lands. The farmers were left with no choice except to abandon their land and convert it for other purposes reluctantly with the hope that at least it could give them a stable income. Regardless of acknowledging the significance of agriculture in guaranteeing food security of the state, absence of labour, and good quality agricultural practices pose a deterrent in its formative pathway. The study found that the older generation is as yet keen on returning to the older tradition of cultivation if provided with prominent support from the government primarily in the form of appropriate land use policies, financial support and other beneficial social and agricultural interventions. It was additionally found that some were of the opinion of promoting cultivation in their own households which involve the practice of roof top cultivation, vertical gardening etc. that could be beneficial for at least meeting the food requirements of that specific household. Hence, for the advancement of the agricultural sector as well as for the prevention of land fallowing, an urgent call has to be made to develop appropriate interventions from the side of government by considering all the necessary aspects including societal, ecological and economic. 5. Conclusion The present study analysed the changes on land use and land cover along the urbanization gradient in the most agglomerative city of Kerala, Kochi, from 2005 to 2020. Two major and divergent trends were observed; the first one is the intensification of land use activities, and the second one is the fallowing and abandonment of land. Significant changes in the areas occupied by buildings, mixed vegetation, paddy fields and fallow lands were observed. Both buildings and fallow lands depicted an expanding trend while paddy fields and mixed vegetation represented a diminishing trend. These changes were more or less similar in urban, suburban and rural areas. In the urban area, the major factor which contributed towards LU/LC change during 2005 to 2020 was urbanisation and infrastructure development which got the highest ranking followed by the sectoral transition from agriculture to white- and blue-collar jobs as a result of lack of interest and changing values and beliefs of the youth. While considering the case of suburban areas, the prominent factor which led to LU/LC change was labour availability and increased cost of labour followed by uncertain markets and less profitability from agricultural produce. In the rural area, the most critical factor of change was unexpected rain, flood, drought and other meteorological events followed by uncertain markets and reduced profit prompting huge losses to the farmers. The study calls for immediate interventions in reducing the rate of fallowing, and re-establishing agriculture in the fallow lands with appropriate socio-economic and institutional interventions. Declarations ACKNOWLEDGEMENTS The authors would like to thank Hon’ble Vice Chancellors of Kerala University of Fisheries and Ocean Studies (KUFOS) and Kerala Agricultural University (KAU) for permitting and providing necessary facilities to conduct the study. We also acknowledge the co-operation of all the respondents of survey of Kochi, Kerala. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions Research framework, material preparation, data collection and analysis were performed by Akshara Thekkeyil and Shijo Joseph. The first draft of the manuscript was written by Akshara Thekkeyil and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References Ahmad, W., Iqbal, J., Nasir, M. J., Ahmad, B., Khan, M. T., Khan, S. 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Effect of land use changes on water quality in an ephemeral coastal plain: Khambhat City, Gujarat, India. Water. 11(4), 724. https://doi.org/10.3390/w11040724 Lambin, E. F., Meyfroidt, P. 2011. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl. Acad. Sci. U.S.A. 108(9), 3465-3472. https://doi.org/10.1073/pnas.1100480108 Lambin, E. F., Turner, B. L., Geist, H. J., Agbola, S. B., Angelsen, A., Bruce, J. W., Coomes, O.T., Dirzo, R., Fischer, G., Folke, C., George, P.S., Homewood, K., Imbernon, J., Leemans, R., Li, X., Moran, E.F., Montimore, M., Ramakrishnan, P.S., Richards, J.F., Skanes, H., Steffen W., Stone, G.D., Svedin, U., Veldcamp, T.A., Vogel, C., Xu, J. 2001. The causes of land-use and land-cover change: moving beyond the myths. Glob. Environ. Change. 11(4): 261-269. https://doi.org/10.1016/S0959-3780(01)00007-3 Lasanta, T., Arnáez, J., Pascual, N., Ruiz-Flaño, P., Errea, M.P. Lana-Renault, N. 2017. Space–time process and drivers of land abandonment in Europe. Catena. 140: 810-823. https://doi.org/10.1016/j.catena.2016.02.024 Liping, C., Yujun, S. Saeed, S. 2018. Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques: a case study of a hilly area, Jiangle, China. PLoS One. 13(7). https://doi.org/10.1371/journal.pone.0200493 Mbow, C., Rosenzweig, C., Barioni, L. G., Benton, T. G., Herrero, M., Krishnapillai, M., Waha, K. 2019. Chapter 5: food security. IPCC Special Report on Climate Change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. https://www.ipcc.ch/site/assets/uploads/2019/11/08_Chapter-5.pdf [05 May 2021]. Meyfroidt, P., Lambin, E. F., Erb, K. H., Hertel, T. W. 2013. Globalization of land use: distant drivers of land change and geographic displacement of land use. Curr. Opin. Environ. Sustain. 5(5): 438-444. https://doi.org/10.1016/j.cosust.2013.04.003 Mishra, N., Khare, D., Gupta, K. K., Shukla, R. 2014. Impact of land use change on groundwater—a review. Adv. Water Resour. Protec., 2(28), 28-41. https://www.researchgate.net/publication/279951307_Impact_of_Land_Use_Change_on_Groundwater_-_A_Review Muñoz-Rojas, M., Jordán, A., Zavala, L. M., De La Rosa, D., Abd-Elmabod, S. K., Anaya-Romero, M. 2015. Impact of land use and land cover changes on organic carbon stocks in Mediterranean soils (1956–2007). 2012. Land Degrad. Develop. 26(2): 168-179 https://doi.org/10.1002/ldr.2194 Murali, R. M., Kumar, P. D. 2015. Implications of sea level rise scenarios on land use/land cover classes of the coastal zones of Cochin, India. J. Environ. Manage. 148: 124-133. Oslon, J.M., Misana, S., Campbell, D.J., Mbonile, M., Mugisha, S. 2004. A research framework to identify the root causes of land use change leading to land degradation and changing biodiversity. Land Use Change Impacts and Dynamics (LUCID) project, Working paper 48. https://www.researchgate.net/publication/236240061_A_Research_Framework_to_Identify_the_Root_Causes_of _Land_Use_Change_Leading_to_Land_Degradation_and_Changing_Biodiversity [20 October 2020]. Pandey, B., Seto, K.C. 2015. Urbanization and agricultural land loss in India: comparing satellite estimates with census data. J. Environ. Manage. 148: 53-66. https://doi.org/10.1016/j.jenvman.2014.05.014 Plieninger, T., Hui, C., Gaertner, M., Huntsinger, L. 2014. The impact of land abandonment on species richness and abundance in the Mediterranean basin: a meta-analysis. PLoS One. 9(5). https://dx.doi.org/10.1371%2Fjournal.pone.0098355 Priya, T., Pulikkamath, A., Mooventhan, G. 2018. An inquiry to the status and causes of fallow land in Kerala. J. Adv. Res. Appl. Sci . 5(4): 67-75 Ranganathan, T., Pandey, G. 2018. Who leaves farmland fallow and why? an empirical investigation using nationally representative survey data from India. Eur. J. Dev. Res. 30: 914-933. https://doi.org/10.1057/s41287-018-0139-2 Rawat, J. S., Kumar, M. 2015. Monitoring land use/cover change using remote sensing and GIS techniques: a case study of Hawalbagh block, district Almora, Uttarakhand, India. Egypt. J. Remote Sens. Space Sci. 18(1): 77-84. https://doi.org/10.1016/j.ejrs.2015.02.002 Reja, M. S., Das, B. 2019. Labour migration within India: motivations and social networks. South Asia Res. 39(2): 125-142. https://doi.org/10.1177%2F0262728019842018 Sanitha, V. P. 2015. Structural changes and pattern of agricultural development in Kerala. M.Sc. thesis, Central University of Punjab. http://210.212.34.21/handle/32116/1972 Sasmito, S.D., Taillardat, P., Clendenning, J.N., Cameron, C., Friess, D.A., Murdiyarso, D., Hutley, L.B. 2019. Effect of land‐use and land‐cover change on mangrove blue carbon: a systematic review. Glob. Change Biol. 25(12): 4291-4302. https://doi.org/10.1111/gcb.14774 Shinoj, P. 2015. Agriculture performance and future outlook on food commodities in Kerala. Agric. Econ. Res. Rev . 245: 247-258. Song, X. P., Hansen, M. C., Stehman, S. V., Potapov, P. V., Tyukavina, A., Vermote, E. F., Townshend, J. R. 2018. Global land change from 1982 to 2016. Nature. 560(7720): 639-643. https://doi.org/10.1038/s41586-018-0411-9 Sreya, B., Vidhyavathi, A. 2018. Dynamics of land use pattern in Kerala–a temporal analysis. Madras Agric. J. 105(1-3): 91. http://dx.doi.org/10.29321/MAJ.2018.000109 Thaickavil, N. N. 2020. Land use model for rural-urban transition in Kerala. National Conference and Seminar on Innovations in Engineering & Technology. https://www.researchgate.net/publication/339999743_Land_Use_Model_for_Rural-Urban_Transition_in_Kerala [20 July 2021]. Thomas, J. S. 2017. A study on urbanisation of Kerala with reference to the cities and the slum population. Technology. 49(4). https://www.researchgate.net/publication/342348034_A_Study_on_Urbanisation_of_Kerala_with_Reference_to _the_Cities_and_the_Slum_Population_NAGARLOK_VOL_XLIX_Part_4_Oct-Dec_2017 Viswanathan, P. K. 2014. The rationalization of agriculture in Kerala: implications for the natural environment, agro-ecosystems and livelihoods. Agrar. South: J. Polit. Econ. 3(1): 63-107. https://doi.org/10.1177%2F2277976014530232 Zanotti, C., Rotiroti, M., Fumagalli, L., Stefania, G. A., Canonaco, F., Stefenelli, G., Prévôt, A.S.H., Leoni, B., Bonomi, T. 2019. Groundwater and surface water quality characterization through positive matrix factorization combined with GIS approach. Water Res., 159, 122-134. https://doi.org/10.1016/j.watres.2019.04.058 Zhao, S., Peng, C., Jiang, H., Tian, D., Lei, X., Zhou, X. 2006. Land use change in Asia and the ecological consequences. Ecol. Res . 21: 890-896. https://doi.org/10.1007/s11284-006-0048-2 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2164710","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":144422116,"identity":"b1094018-1c44-4711-ad79-9a88e945c8ca","order_by":0,"name":"Akshara Thekkeyil","email":"","orcid":"","institution":"Kerala University of Fisheries and Ocean Studies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akshara","middleName":"","lastName":"Thekkeyil","suffix":""},{"id":144422118,"identity":"f0e061df-89a1-4eda-bc8c-56ba59f27d6b","order_by":1,"name":"Shijo Joseph","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDACCcYGAzCDvQFIGFiQooXnAEiLBDFa4IwEFC5uID+7uaHg44579vwzn1/d8KNAgoG/vTsBrxaDOwcbDGeeKU6ccTun7GYP0GESZ85uwK9FIrHBmLctIYHhdk7aDR6gFgOJXPxa5GdAtNjL3zyTdvMPMVoYbkC0MG64wX7sNlG2GAC1GM5sS0jceCaH7baMgQQPQb/Iz0h/ZvAR6DC548ef3Xzzx0aOv72XgMMYGNggUcnAA6Z5CCkHAeYHEJr9ATGqR8EoGAWjYAQCAChkSWa7/2R/AAAAAElFTkSuQmCC","orcid":"","institution":"Kerala University of Fisheries and Ocean Studies","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Shijo","middleName":"","lastName":"Joseph","suffix":""},{"id":144422120,"identity":"8356bc86-21ca-4968-8563-f8f53ba6baea","order_by":2,"name":"Fathima Abdurazak","email":"","orcid":"","institution":"Kerala University of Fisheries and Ocean Studies","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fathima","middleName":"","lastName":"Abdurazak","suffix":""},{"id":144422122,"identity":"b6933365-f57e-4fc2-af13-c7fac4834553","order_by":3,"name":"Giby Kuriakose","email":"","orcid":"","institution":"Sacred Heart College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Giby","middleName":"","lastName":"Kuriakose","suffix":""},{"id":144422124,"identity":"f54cc523-6a21-41a1-b2d9-5cdb8110a4ed","order_by":4,"name":"P O Nameer","email":"","orcid":"","institution":"Kerala Agricultural University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"P","middleName":"O","lastName":"Nameer","suffix":""},{"id":144422126,"identity":"0811d206-4c03-4475-8c60-cf0d20209ea1","order_by":5,"name":"Purushothaman Chirakkuzhyil Abhilash","email":"","orcid":"","institution":"Banaras Hindu University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Purushothaman","middleName":"Chirakkuzhyil","lastName":"Abhilash","suffix":""}],"badges":[],"createdAt":"2022-10-14 05:44:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2164710/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2164710/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":27939148,"identity":"69ee802a-f9e3-45df-ac65-56ca4887fb5d","added_by":"auto","created_at":"2022-10-18 15:28:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1371535,"visible":true,"origin":"","legend":"\u003cp\u003eAn artistic view of current land use practices observed in rapidly developing economies such as in Kerala, India.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/f69bf1cad2d29ada59d28e9f.png"},{"id":27939149,"identity":"01c913c3-c071-426c-bebf-b97151e42885","added_by":"auto","created_at":"2022-10-18 15:28:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2795931,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study area showing grids and study sites. The urban, suburban, and rural areas were defined using a buffering algorithm with a radial distance of 10 km, 20 k,m and 30 km respectively from the city center. The grid size is 1 X 1 km.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/f7abbff927226426eda6dbe5.png"},{"id":27938528,"identity":"059a43b2-47eb-4ec3-8c65-9c7b16d3e0f9","added_by":"auto","created_at":"2022-10-18 15:23:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":128222,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the methodology followed for the analysis of land use intensification and land fallowing in the study area.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/e32027a38b7231f32cdcb213.png"},{"id":27939464,"identity":"33f6b39e-eceb-4bca-8f76-441217bff3d6","added_by":"auto","created_at":"2022-10-18 15:33:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1174388,"visible":true,"origin":"","legend":"\u003cp\u003eLU/LC change in urban grids from 2005 to 2020.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/5cb4831bfed6e0df32d301f7.png"},{"id":27938529,"identity":"00a76ef1-7280-4fe3-9887-adf690a3b4b4","added_by":"auto","created_at":"2022-10-18 15:23:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":496520,"visible":true,"origin":"","legend":"\u003cp\u003eLU/LC change in suburban grids from 2005 to 2020.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/1f06f12cc2df3756ac37a979.png"},{"id":27938530,"identity":"d2984b05-f30d-4c2e-a1a6-601f233de0f5","added_by":"auto","created_at":"2022-10-18 15:23:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1023522,"visible":true,"origin":"","legend":"\u003cp\u003eLU/LC change in rural grids from 2005 to 2020\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/a0392e076ae31a4d6de0c0e2.png"},{"id":27938532,"identity":"ad937a45-17ea-4766-9c7d-44f2c39b80c5","added_by":"auto","created_at":"2022-10-18 15:23:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":195958,"visible":true,"origin":"","legend":"\u003cp\u003eMajor drivers which contributed to the LU/LC change in the study area from 2005 to 2020.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/080d01635240791539eb6655.png"},{"id":28979688,"identity":"2cb52238-1463-4150-8140-271ecb39c8ff","added_by":"auto","created_at":"2022-11-12 08:44:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6055864,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2164710/v1/fa5101f7-ffaa-4129-a6f3-a297ed6c2a8b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Land use change in rapidly developing economies – A case study on land use intensification and land fallowing in Kerala, India","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLand is a critical natural resource pivotal for the sustenance of life on earth. However, the immoderate upsurge in population resulted in the unsustainable and indiscriminate utilisation of land. Drastic changes in land use/land cover (LU/LC) have occurred over the years, for which the anthropogenic contribution is undeniable (Lambin et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Rawat and Kumar, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Liping et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Human-induced LU/LC changes have reduced the capacity of soil to store carbon, increasing soil bulk density (Sasmito et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and leading to global warming through enhanced greenhouse gas emissions (Mu\u0026ntilde;oz-Rojas \u003cem\u003eet al.\u003c/em\u003e, 2012). A significant reduction in the quality of groundwater and surface water was identified in relation to the changing land use pattern (Mishra et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kumar et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zanotti et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ahmad et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Other ecological consequences of LU/LC change include biodiversity loss, alterations in the biogeochemical cycles, land degradation, and so on (Zhao et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Allan et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Song et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The conversion of lands in association with urbanisation and industrialization has led to land scarcity for agriculture, thereby posing a serious threat to food security (Chen, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pandey and Seto, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The rapidly developing economies are predominantly under the brunt of this trend compared to the developed nations now and are driven by the complex connections of various social, demographic, economic, cultural, institutional, technological, and meteorological parameters (Lambin and Meyfroidt, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eKerala, the state located on the southwestern end of the Indian subcontinent, is undergoing a transition from a traditional backward agrarian economy to a modern flourishing economy (Shinoj, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The structural transformation that the state witnesses comprise four characteristics including a reduced share of agriculture in employment generation and economic development, enhanced share of industries and other sectors in the economy, increased rural to urban migration in search of jobs (Shinoj, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and a demographic transition in the rates of birth and death leading to an increase in population prior to arriving at an equilibrium state (Sanitha, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As a result, two major and divergent trends are being observed in the recent land use history of Kerala. The first one is an intensification of human activities and sprawling of urban centres along the \u003cem\u003eurban-rural\u003c/em\u003e continuum (Kumar, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and the second one is the fallowing and abandonment of land due to low economic return in the agricultural sector compared to other sectors. During early 2000s, Kochi urban agglomeration was the only city having more than a million population of the 18 urban agglomerations, but by 2011, it increased to seven cities, namely, Kozhikode, Thrissur, Malappuram, Thiruvananthapuram, Kannur and Kollam. Between 2001 and 2011, there has been a dramatic increase in the urban population owing to the reclassification of numerous rural areas to urban (i.e., into census towns), and there has been rapid increment of census towns from 99 in 2001 to 461 in 2011, i.e., an increase of almost 366% (Thaickavil, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The urbanisation witnessed in Kerala is different from other parts of the country as it is characterised not just by the migration of rural population to urban areas (Bhagat, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), yet additionally a decrease in the area of agricultural fields and their conversion for other economic activities (Thomas, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the other hand, the drastic reduction of human labour and the increase in the labour cost leaves much of the marginal lands to the process of fallowing and abandonment (Sreya and Vidhyavathi, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recently, the aspirant young populations tend to migrate to metro cities and major towns in search of white- and blue-collar jobs kept no or less human resources for agricultural practices, resulting in a surge in labour costs in the rural areas (Jose and Padmanabhan, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Extreme climatic events, and changes in the weather patterns have increased the risk of marginalised farmers, acting as an impetus that pace up the land diversion to other economically profitable land uses or leaving the land uncultivated. Though various laws were introduced to enhance the agricultural sector, it was found beneficial only to rich and influential farmers leaving behind marginal farmers, forcing them to leave the land fallow (Viswanathan, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Land abandonment can be a significant deterrent to attaining Sustainable Development Goals (SDGs) primarily goals 1 (no poverty), 2 (zero hunger) and 3 (good health and well-being) (Hobbs and Cramer, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Plieninger et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Filho et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mbow et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently, the land use in growing economies like Kerala can be sketched along the gradient of transitioning from rural to urban landscapes with varying characteristics (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Firstly, the commercial business and urban centers where intensive human activities take place, the price of the land shoot up in no time. The city/urban centers and the roadways of the major national and state highways are examples of such areas. These regions have high population density alongside corresponding infrastructures in association with the increasing rate of urbanization. The second one is the suburban area where a transition from rural to urban is expected in the near future. Such areas are predominantly characterized by small holder land use systems with houses, homesteads, and small-scale industries/business establishments. The level of human activities in those areas are medium and the prices of land are more or less same or slightly on the upward side over the years. The third represents predominantly agricultural landscapes in the rural areas where the level of human interventions on land is low compared to the urban and suburban areas and characterized by lower population density and less economic activities. The low economic returns compared to investment in agriculture makes such areas less attractive for investors, and the price of the land is on a negative trend. The impending danger of land fallowing, and the resultant land abandonment is threatening the very existence of agricultural sustainability in those areas.\u003c/p\u003e \u003cp\u003eOur present study aims to develop empirical evidence of changes in land use along the rural to urban continuum in a rapidly developing city of Kerala, Kochi, over the last one and half decades. The study also addresses the major factors that drive the changes in land use, both land use intensification, and land fallowing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study area\u003c/h2\u003e \u003cp\u003eThe study was carried out in the most populous metropolitan city in Kerala, i.e., Kochi, also known as the industrial, financial and economic capital of Kerala (Fig.\u0026nbsp;2). The city comprises an area of 87.5 square kilometer with its major portion lying at the sea level and having a coastline of 48 km. The city has a larger network of backwaters enveloping the northern tip of the peninsula, various islands and the mainland. Laccadive sea is present at the west while the eastern region comprises the urban mainland. The urban agglomeration population marked tremendous growth with the number rising from 0.8\u0026nbsp;million to 2.1\u0026nbsp;million from the year 1981 to 2011. The region has a flat elevation with a warm and humid climate having a temperature range between 20\u003csup\u003eo\u003c/sup\u003eC to 35\u003csup\u003eo\u003c/sup\u003eC (Murali and Kumar, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The average annual rainfall is 3100 mm with 132 average annual rainy days. The economic growth of the city began with the economic reforms brought about by the Central government during the early 1990s. The service sector played a central role in boosting the economy with the establishment of numerous IT parks and port-based infrastructures which triggered the construction and developmental boom in the city. Kochi witnessed rapid commercialisation over the years and has now developed into the commercial hub of Kerala (Ernakulam District Administration, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) primarily because of an all-weather harbour, good quality water, and access to cheap hydro-electric power (George and Rajan, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Remote Sensing Data Analysis\u003c/h2\u003e \u003cp\u003eThe remote sensing and GIS analysis was carried out in Google Earth Pro (GEP) as well as ArcGIS \u003cem\u003ever\u003c/em\u003e 25.1 (ESRI 2021). Headquarters of the Cochin Corporation was taken as the center point of the study, around which 10, 20 and 30km buffers were created to represent urban, suburban and rural areas respectively. The buffered area was then gridded into 1km grids using a fishnet grid in ArcGIS for its delineation into urban, suburban, and rural grids. Intensive study grids were randomly selected and time-series satellite data for these grids for the years 2005, 2010, 2015 and 2020 were analysed using GEP. Special care was given to opt data which are cloud free, clear and geometrical registration error is less than one pixel. Manual digitization was done in these grids for these years by fixing an eye elevation of 50m in GEP. For digitizing the data, various classes like buildings, mixed orchards, water bodies, tarred roads, muddy roads, railway tracks, barren areas, fallow lands, and paddy fields were considered depending on the respective grid. As the digitization was done manually, the chances of occurrence of errors were high, thus topology was run. Topology is generally used to display topological relationships, exceptions, and errors. LU/LC maps for the years 2005, 2010, 2015 and 2020 were obtained post error correction which was further used for the analysis of changes that occurred over the years.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Household Survey\u003c/h2\u003e \u003cp\u003eGround truthing and household survey was carried out to validate whether the changes detected in the remote sensing analysis over the years is consistent with the actual ground situation. A semi-structured interview at the household level was conducted in the grids pertaining to Vyttila in the urban area, Edathala in the suburban area, and Maravanthuruthu in the rural area. The survey was limited to those households who have been residing in the region for at least 20 years or more. Ten such households from each urban, suburban, and rural areas were surveyed randomly during the period August to November 2021. The questionnaire included sessions on how the land use changed over the years, and what were the major reasons for the change in those areas. \u003cem\u003eA priori\u003c/em\u003e list of drivers of land use change was prepared in consultation with academicians, researchers, and practitioners. The drivers included were urbanization and infrastructure development, industrialization, uncertain markets and less profitability from agriculture produce, labour availability and increased cost of labour, soil degradation and reduced fertility of the soil, values, beliefs, less interest and lack of respect in agriculture as a profession, migration of youth to urban areas in search of white and blue-collar jobs, unexpected rain, flood, drought, and other meteorological events, absence of government-backed schemes, policies and support, and absence of science-driven practices in agriculture sector. The responses were recorded on paper and then entered separately in excel worksheets for further analyses. The flow chart depicting the entire methodology is given in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eIn general, of the 900 ha of the study area, buildings have shown an increasing trend in all the 3 regions where the initial value of 139 ha rose to 227 ha by 2020 (i.e., 15\u0026ndash;25% of the total geographical area studied) with drastic changes happening in the urban area. The mixed vegetation showed a decreasing trend from 547.1 ha in 2005 (i.e., 61% of the geographical area) to 467.3 ha in 2020 (i.e., 52% of the area), particularly in the urban grids as a result of the expansion in buildings. The case of paddy fields is similar to that of mixed orchards in terms of the decrease in the area with the change being highly critical in certain suburban and rural areas. It was found that the area occupied by paddy fields diminished from 155 ha to 111 ha by 2020. When fallow lands are taken into consideration, they have shown an increasing trend in rural and suburban areas. The value expanded to 29 ha by 2020 from nearly zero in 2005.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. LU/LC Change in Urban Areas\u003c/h2\u003e \u003cp\u003eWhile considering the case of the urban area, of the total area of 300 ha (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e), 124 ha of land were occupied by buildings in 2005 which expanded to 174 ha by 2020, i.e., an increment of almost 16.6%. Mixed vegetation occupied an area of 145 ha in 2005 which decreased to 93 ha by 2020, a reduction of 17.3% while the water bodies decreased from 9 ha to 8 ha by 2010 and thereafter remained the same until 2020. The urban area witnessed an expansion of tarred roads from 14 ha in 2005 to 19 ha by 2020, almost an increment of 1.6%. During the initial years, 1ha of land were muddy roads, which reduced to zero by 2020 as all the muddy roads got converted to tarred roads as a part of urban development. The changes in other land cover classes were nominal. Of the three study areas, the Vyttila grid showed maximum land area conversion between 2005 and 2020.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use/ land cover change in urban area from 2005\u0026ndash;2020 in hectares\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLULC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2005\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2010\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2015\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2020\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed vegetation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuildings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuddy roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarred roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRailway track\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther barren areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaterbody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. LU/LC Change in Suburban Areas\u003c/h2\u003e \u003cp\u003eOn account of the suburban area, the area occupied by buildings was only 7 ha in 2005 which increased to 25 ha by 2020 (i.e., an increase of 6%). The mixed vegetation showed a slight increase from 199.6 ha in 2005 to 203.4 ha by 2010, but thereafter the area shrank to 189.4 ha by 2020. In the suburban area, paddy cultivation exhibited a diminishing pattern over the last one and half decades. In 2005, 85 ha of land were devoted to paddy which declined to 63 ha by 2020, a change of about 7.3% net reduction in area was observed. In the case of fallow lands, there were no fallow lands at the beginning of the study period which got increased to 12 ha by 2020 (i.e., 4% of the area studied). Tarred roads had undergone an escalation from 4 ha to 8 ha during 2005 to 2020. In 2005, 2 ha of muddy roads were found which gradually decreased to 0.2 ha by 2020. Classes like buildings, mixed orchards, paddy fields, and fallow lands had witnessed major changes in terms of area of occupancy, primarily in the grid pertaining to Edathala which was once an agrarian region as it is clearly visible from Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use/ land cover change in suburban area from 2005\u0026ndash;2020 in hectares.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLULC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2005\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2010\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2015\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2020\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed vegetation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e196.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaddy fields\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuildings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFallow lands\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuddy roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarred roads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther barren areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaterbody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. LU/LC Change in Rural Areas\u003c/h2\u003e \u003cp\u003eA positive trend in the area of buildings was witnessed in the rural areas. The buildings expanded to 28 ha in 2020 from 8 ha in 2005, i.e., an expansion of 6.6%. While the extent of mixed vegetation is decreased to 184.9 ha by 2020 from 202.5 ha in 2005. A drastic decline in the area of paddy fields was also observed from 2005 to 2020, i.e., a decrease from 70 ha to 48 ha which is close to 7.3% in the net area. This was very prominent in the grid pertaining to Nedumbasserry. The fallow lands also showed a sharp increase in the extent of the area from zero to 17 ha in the last one and half decades (i.e., approximately 6% of the total geographical area studied in the category of rural is fallowed currently), indicating serious consequences on the agricultural sector. Tarred roads expanded from 2 ha to 6 ha during 2005 to 2020. Critical changes had taken place in the case of paddy fields, fallow lands, mixed orchards and buildings (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLand use/ land cover in rural area from 2005\u0026ndash;2020 in hectares.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLULC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eYEAR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2005\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2010\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2015\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2020\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed vegetation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e184.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaddy field\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFallow land\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuddy road\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarred road\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther barren area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaterbody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRailway track\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Rate of change in land use intensification and fallowing\u003c/h2\u003e \u003cp\u003eThe buildings, roads and railways constituted only 47% in the urban area in 2005 which was increased to 65% by 2020 (i.e., an increase of 18%). The annual rate of change was 1.2%. No fallowing was observed in the urban areas. For the suburban areas, buildings and other infrastructures accounted for 4.3% in 2005 which was increased to 5.7% in 2010, 7% in 2015, and 11% in 2020. Annually, the rate of change observed was 0.84% from 2005 to 2010, 0.99% from 2010 to 2015, and 2.21% from 2015 to 2020, averaging an annual rate of land use intensification of 1.35%. When considering the case of land fallowing, no fallow or abandoned agriculture areas were observed in 2005 whereas this rose to 12 ha in 2020 (4% of the suburban study area). The annual rate of land fallowing was 0.27% in 15 years. A similar trend in land use intensification and land fallowing was observed in the rural areas as well. During 2005, the land occupied by buildings, railways and roads in the rural areas was only 4% which was increased to nearly 12% in 2020, almost three times the initial value. Annually, the land use intensification activities and the resultant conversion were at the pace of 1.57%. The fallowing of the land was also prominent in the rural grids where 5.67% of the total area was kept fallowed or abandoned in the year 2020 from nil at the beginning of the study period. The rate of fallowing was 0.38% per annum. Altogether, the urban, suburban, and rural grids in the study area showed the land use intensification activities at the rate of 1.37% per annum and land fallowing and abandonment at the rate of 0.21% per annum.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Drivers of LU/LC Change\u003c/h2\u003e \u003cp\u003eAll the major factors that contributed to the LU/LC change in the study area, specifically in urban, suburban, and rural areas are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e. In the urban area, urbanisation and infrastructure development showed the highest-ranking in LULC changes. This was followed by the migration of youth in search of white and blue-collar jobs, and the changes in the values, beliefs, less interests and lack of respect to agriculture as a profession. All the respondents were of the opinion that the policies developed by the government had nothing to do with the stagnation of the agricultural sector. The factor that received the lowest ranking was industrialisation, indicating the irrelevance of industrial development in LU/LC change in the highly populated urban grids.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe case of suburban areas reveals the pertinence of labour availability and increased labour cost in changing the land use pattern. Uncertain markets and less profitability from agricultural produce emerged as second ranking. Lack of interest, changing values, beliefs, and lack of respect for agriculture as a profession alongside large-scale migration of individuals to urban areas in search of other demanding jobs were ranked third and fourth respectively. Urbanisation and infrastructural development received the fifth ranking. Similar to urban areas, factors related to the quality of soil, meteorological parameters, government policies, science-driven practices, and industrialisation obtained lower ranks.\u003c/p\u003e \u003cp\u003eIn the rural area, the most critical factor that drove the LULC change was unexpected rain, flood, drought, and other meteorological events. Uncertain market and reduced profit was the second highest while shortages in the availability of labour and labour costs gained the third highest ranking. The fourth and fifth ranking was given for the factors related to changing values of youth and their subsequent migration to urban centres respectively. Similar to urban and suburban areas, all other factors played only nominal roles in LU/LC change.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eMomentous changes have taken place in LU/LC in the study area over the years in terms of intensification of land use activities as well as fallowing of lands. The rate at which urbanisation as well as infrastructural development is taking place in Kochi is surprisingly high that side-lines several traditional practices and results in changes or abandonment of natural habitats even in the peri-urban areas of Kochi. More than one-third of the land cover grids considered for the present study is now constituted by urban features, leaving little land for vegetation, and other land covers. The fallowing and abandonment of land was not found in the urban grids as every piece of the land is worth of thousands of dollars and is under the radar of the lucrative real-estate business. The growth of the urban consumer class has a close relationship with land use change which is greatly influenced by the globalized flow of people, capital, commodities, and so on (Meyfroidt et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe pace at which land utilization changes in the rural and suburban grids is also remarkable. During the early 2000s, agriculture was a major source of income for individuals dwelling in suburban and rural areas. A major portion of the land in these regions was devoted to paddy cultivation along with the cultivation of other crops like rubber, coconut, nutmeg, and so on. Over the years, agriculture lost its charm as a source of living which prompted its conversion to other purposes. People likewise lost interest in agriculture due to abridged profit from agricultural produce alongside uncertain markets which ultimately led to their migration to urban agglomerations in search of white- and blue-collar jobs. These results are well aligned with the global literature that uncertain markets, less profitability, urbanization, infrastructural expansion, migration of rural population to urban areas, lack of enough employment in rural areas, and attitudes, values, beliefs, and individual perceptions of people primarily drive changes in agricultural practices, and the land system dynamics (Oslon et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Benayas et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lasanta et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ranganathan and Pandey, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Castro et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Chaudhary et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, extreme weather conditions and the periodic occurrence of floods in the recent history of Kerala have aggravated the situation which forced the farmers to leave their land fallow as the recurring losses were dreadful and irrevocable.\u003c/p\u003e \u003cp\u003eThe present study reveals that agriculture is losing its aesthetic as well as economic value, persuading increased dependence on other Indian states for meeting the dietary requirements. A large portion of people in suburban, as well as rural regions, are unable to do cultivation on their lands due to reduced availability of labour as well as increased labour cost even after having the desire to do cultivation. This trend is actually forcing them to leave their land fallow. A greater number of farmers gave it their best attempt to continue cultivation on their land yet continuous yield and profit loss constrained them to refrain from cultivation.\u003c/p\u003e \u003cp\u003eLikewise, with the development of corporate jobs with higher pay and living standards, the youth got attracted to it, losing interest in cultivation, leaving behind agriculture as a source of income and consequently permitting their land to fallow. This further prompted the migration of suburban and rural population to cities for a better standard of living and thus posing a serious problem in the agri-labour market in Kerala. Despite the fact that there was large-scale migration of immigrants from other Indian states, they weren\u0026rsquo;t found fit to do cultivation on these lands as they came from an entirely different cultural and linguistic background (Priya et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) with different skills other than the agriculture practices in the study area. Though institutional factors like lack of appropriate land use policies were considered insignificant factors in LU/LC change, there were situations which depicted its inability to forestall the fallowing of lands. The farmers were left with no choice except to abandon their land and convert it for other purposes reluctantly with the hope that at least it could give them a stable income.\u003c/p\u003e \u003cp\u003eRegardless of acknowledging the significance of agriculture in guaranteeing food security of the state, absence of labour, and good quality agricultural practices pose a deterrent in its formative pathway. The study found that the older generation is as yet keen on returning to the older tradition of cultivation if provided with prominent support from the government primarily in the form of appropriate land use policies, financial support and other beneficial social and agricultural interventions. It was additionally found that some were of the opinion of promoting cultivation in their own households which involve the practice of roof top cultivation, vertical gardening etc. that could be beneficial for at least meeting the food requirements of that specific household. Hence, for the advancement of the agricultural sector as well as for the prevention of land fallowing, an urgent call has to be made to develop appropriate interventions from the side of government by considering all the necessary aspects including societal, ecological and economic.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe present study analysed the changes on land use and land cover along the urbanization gradient in the most agglomerative city of Kerala, Kochi, from 2005 to 2020. Two major and divergent trends were observed; the first one is the intensification of land use activities, and the second one is the fallowing and abandonment of land. Significant changes in the areas occupied by buildings, mixed vegetation, paddy fields and fallow lands were observed. Both buildings and fallow lands depicted an expanding trend while paddy fields and mixed vegetation represented a diminishing trend. These changes were more or less similar in urban, suburban and rural areas. In the urban area, the major factor which contributed towards LU/LC change during 2005 to 2020 was urbanisation and infrastructure development which got the highest ranking followed by the sectoral transition from agriculture to white- and blue-collar jobs as a result of lack of interest and changing values and beliefs of the youth. While considering the case of suburban areas, the prominent factor which led to LU/LC change was labour availability and increased cost of labour followed by uncertain markets and less profitability from agricultural produce. In the rural area, the most critical factor of change was unexpected rain, flood, drought and other meteorological events followed by uncertain markets and reduced profit prompting huge losses to the farmers. The study calls for immediate interventions in reducing the rate of fallowing, and re-establishing agriculture in the fallow lands with appropriate socio-economic and institutional interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Hon\u0026rsquo;ble Vice Chancellors of Kerala University of Fisheries and Ocean Studies (KUFOS) and Kerala Agricultural University (KAU) for permitting and providing necessary facilities to conduct the study. We also acknowledge the co-operation of all the respondents of survey of Kochi, Kerala.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResearch framework, material preparation, data collection and analysis were performed by\u0026nbsp;\u003c/em\u003eAkshara Thekkeyil\u003cem\u003e\u0026nbsp;and Shijo Joseph. The first draft of the manuscript was written by\u0026nbsp;\u003c/em\u003eAkshara Thekkeyil\u003cem\u003e\u0026nbsp;and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad, W., Iqbal, J., Nasir, M. J., Ahmad, B., Khan, M. T., Khan, S. N., Adnan, S. 2021. Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan. Sci. 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Res\u003cem\u003e.\u003c/em\u003e 21: 890-896. https://doi.org/10.1007/s11284-006-0048-2\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Remote Sensing, Land use/land cover change, Land Fallowing and Abandonment, Sustainable Development Goals","lastPublishedDoi":"10.21203/rs.3.rs-2164710/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2164710/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe land use/land cover change is a local driver of environmental change having cascading impacts and implications at the global level and therefore requires appreciable consideration when perceived from sustainability perspectives. Kerala, the southernmost state of India has undergone a dramatic transition from a traditional agrarian economy to a modern thriving economy involving the irrational exploitation of natural resources, precisely, land and its components. The present study addresses how land is being changed along an urbanization gradient in the most agglomerative city in the state, Kochi, during the last one and half decades. High-resolution remote sensing data available from the Google Earth Engine pertaining to the four time periods, i.e., 2005, 2010, 2015, and 2020, representing urban, suburban, and rural areas, were analysed to estimate the changes in land use land cover. A semi-structured interview was conducted at the household level to identify the major drivers of land use change. The results indicated the presence of two major and divergent trends; the first one is the intensification of land use activities at the rate of 1.37% per annum, primarily driven by urbanization and infrastructure developments, and the second one is the fallowing and abandonment of land (at the rate of 0.21% per annum) driven by the increased cost of cultivation and unexpected changes in meteorological events frequently reported in the recent history of Kerala. The rates of change are more prominent in the rural areas while the urban grids are nearing saturation occupying nearly two-third of the area with urban features at the expense of greenery. Though the progression with respect to urbanization and infrastructure developments is expected, the fallowing and abandonment of land is unanticipated, raising serious questions in the developmental pathways to achieve Sustainable Development Goals in the State of Kerala.\u003c/p\u003e","manuscriptTitle":"Land use change in rapidly developing economies – A case study on land use intensification and land fallowing in Kerala, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-10-18 15:23:49","doi":"10.21203/rs.3.rs-2164710/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d734d3a-0367-495b-99c5-f28405e3abfb","owner":[],"postedDate":"October 18th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-11-12T08:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2022-10-18 15:23:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2164710","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2164710","identity":"rs-2164710","version":["v1"]},"buildId":"ehx78VzkSd0WSzXnipQa-","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}