Utilizing Graph Theory for Ecological Planning: Enhancing Connectivity of Urban Green Spaces in Bhopal, Madhya Pradesh, India

Utilizing Graph Theory for Ecological Planning: Enhancing Connectivity of Urban Green Spaces in Bhopal, Madhya Pradesh, 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 Utilizing Graph Theory for Ecological Planning: Enhancing Connectivity of Urban Green Spaces in Bhopal, Madhya Pradesh, India pradeep kumar Rajput This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4232378/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 Graph theory and network analysis are efficient to explore landscape connectivity. Graph theory approach using in urban planning to facilities the municipal service in the urban landscape. The municipal service is an important and proper functional movement in the urban landscape. In this paper, the use of graph-theoretic approaches is operational within the urban landscape assessment, planning, and design. Urban landscape for proper planning and design of urban land without disturbance of an ecosystem. The connectivity is important to exchange their genetic material for the proper functioning of the ecosystem in the urban landscape. In particular, the network model uses to evaluate the contribution of landscape elements to uphold the connectivity. The importance of spatially and geographically area representation the network in urban & regional planning and design is stressed. The study moves the better connectivity of urban green space for the functional ecosystem. Graph theory approach identifies the Intra connectivity(IC), Betweeness centrality (BC), connector, a number of links (NL), Harry Index (HI), landscape coincide Probability (LCP), and integral index connectivity (IIC) in the urban landscape for systematic planning and order to increase the efficiency of monitoring and sustainable urban development. Using a graph theory approach for patch connectivity with integral index connectivity (IIC). Here threshold distance for connectivity is 2m, 20m, 44m, and 100m. Connectivity of urban green space for dispersal of species for one patch to the rest of other patches slightly increases and identifies the prioritize patches for ecological improvement. This paper Examine the protecting ecosystem and sustainable urban development and planning in the future prospectus Graph theory connectivity green space ecological planning and urban planning Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Connectivity is important for the dispersal of species and other ecological flows in landscape it is considered for biodiversity conservation and planning. Climate change and fragmentation of patch is an impact on the loss of native flora and fauna. Some species shift to other geographical areas caused by climate change variation they migrated in the suitable habitable patch for growth. Connectivity ensures the possibility for dispersal and gene flow both of which are crucial to avoid the metapopulation decline and extinct. Connectivity is a loss between habitat patches is a major threat to the biodiversity conservation and ecological balance. The connectivity is an increase in interest in landscape management, planning, and design. In this context, graph theory is a powerful tool for representing the landscape pattern and performing complex analysis regarding landscape connectivity. Graph theory using an ecological application for connectivity of heterogeneous landscape for conservation and planning [ 1 ]. Urban green space comprises the park playground, wasteland, and all other habitats for whose vegetation is characterized by regular mowing can capture harbor and rare grassland biodiversity. graph theory as a computationally powerful adjacent tool and dealing with a large number of data sets [ 2 ]. This is needed for analysis of landscape connectivity in large numbers for habitat patches for connectivity. One Important limitation on studies of ecological values and potential restoration of urban habitat is a question for habitat connectivity which one of the most important studies in urban ecology [ 3 ]. Connectivity is determining the degree to which organisms and processes can move. The more connectivity is possible if more movement of species. A graph is a set of nodes (vertices) and links (edges) such that each connects two nodes. Nodes represent the habitable patch and link is a distance between them for connection [ 4 ]. A set of an interconnected patch in the landscape for connectivity describing. The existences link between in each node implies the potential ability of an organism to directly dispersal of two patches and other patches. The link may have a physical corresponding on the landscape in the form corridor [ 5 ]. In ecological modeling, the link represents the functional connection between a pair of nodes(patches) and also obtained a functional distance of two nodes. Functional connectivity is not ensured in the landscape when the existing habitat units are physically contiguous but also when a permeable Matrix, a series of stepping stones or other connecting elements allow for the exchange of genetic material of particular organism between the habitat patch that might be physically distant [6 ]loss of landscape connectivity and the subsequent isolation of habitat patches can interfere with a genetic exchange, wildlife movement and seed dispersal among other ecological processes [ 7 ]. Intensify landscape connectivity is a key role in modern biodiversity conservation strategies worldwide and get the best response to counteract the potential adverse effect of habitat fragmentation and facilities change geographical location in the natural range of species due to climate change [ 8 ]. Landscape-level planning is one important for landscape monitoring and conservation planning is related to connectivity of the rest natural habitats [ 9 ] which can be promoted through highly permeable landscape matrix or establishing new habitats. Graph theory has a long tradition and was used in many fields but newcomer use in landscape ecology [ 10 ]. This study uses the approach of the habitat availability model, taking into account functional connectivity and specific of certain species [ 11 ]. The development of new graph-based landscape connectivity indices is quantifying the prioritization of habitat patch for conservation [ 12 ]. Many incides have been used and proposed in the context of connectivity analysis [ 13 , 14 , 15 ]. But there is a lack of comprehensive understanding of their sensitivity to pattern structure and their behavior to different spatial changes, which seriously limits their proper interpretation and usefulness. Method and materials Study Area Bhopal, the capital and second-largest city of Madhya Pradesh, holds the moniker of the 'city of lakes' owing to its abundant water bodies. Situated between 23°08' to 23°20' North latitude and 77°01' to 77°30' East longitude, Bhopal spans an area of 287.17 square kilometers. In 2011, its population stood at 1.796 million and is projected to surpass 3 million by 2041, as per the Census data. Administered by the Bhopal Municipal Corporation, the city is divided into 70 wards. Notably, the average elevation of Bhopal is around 500 meters, lending it a scenic charm in the central Indian landscape. One of the defining features of Bhopal's urban landscape is its extensive green spaces, including parks, playgrounds, and other recreational areas. These green zones provide essential breathing spaces amidst the urban sprawl and contribute significantly to the city's environmental well-being. The presence of lush parks and verdant playgrounds enhances the quality of life for residents, offering opportunities for leisure, exercise, and social interaction. Central to Bhopal's geography are its two iconic lakes: The Upper Lake and the Lower Lake. These water bodies not only add to the city's aesthetic appeal but also serve as vital reservoirs, supporting various ecological systems and providing a source of water for local communities. The serene ambiance surrounding these lakes makes them popular recreational spots, attracting tourists and locals alike. As Bhopal continues to grow and evolve, the preservation and expansion of its green spaces become paramount. Efforts to maintain biodiversity, mitigate pollution, and promote sustainable urban development are essential to safeguarding the city's natural heritage for future generations. By prioritizing the creation and maintenance of green infrastructure, Bhopal can uphold its reputation as a vibrant, livable city amidst the bustling landscape of central India. Figure no 1 study area map Mapping of urban green space Urban Greenland’s of Bhopal city is mapped by using the Google earth of recent images. Polygons of habitat patch area digitizing in ARC GIS software and create a shape file for further analysis in confer sensinode software for landscape connectivity of habitat patch which is presented in the Study area. We extract 110 habitat patch in the spatial area and total area of habitat patch is 1742.12 hectare. Urban Greenland, a term often used to describe green spaces within urban areas, has been mapped in Bhopal city using recent images from Google Earth. The process involved digitizing polygons to delineate habitat patch areas using ARC GIS software. This data was then utilized to create a shape file for further analysis in confer Sensinode software, focusing on landscape connectivity of these habitat patches within the study area. In total, 110 habitat patches were identified within the spatial area under investigation, covering a combined area of 1742.12 hectares. This data provides valuable insights into the distribution and characteristics of green spaces within the urban environment of Bhopal. Analyzing the connectivity of these patches can offer crucial information for urban planning and conservation efforts, aiding in the preservation and enhancement of green infrastructure within the city. By understanding how these habitat patches are interconnected, stakeholders can make informed decisions to promote biodiversity, mitigate environmental impacts, and enhance the overall quality of life for urban residents. Green Space Green spaces are fundamental components of urban environments, offering a myriad of benefits to residents and ecosystems alike. These areas, encompassing parks, gardens, urban forests, and green infrastructure, play a pivotal role in enhancing the quality of life in cities. As urbanization accelerates globally, the importance of integrating green spaces into urban planning becomes increasingly evident. This essay explores the multifaceted significance of green spaces in urban areas, addressing their impact on human well-being, environmental sustainability, and urban resilience, supported by empirical evidence and scholarly research. [ 16 ] Enhancing Human Well-being: Green spaces serve as vital sanctuaries for urban dwellers, offering opportunities for relaxation, recreation, and social interaction. Access to nature within cities has been linked to numerous psychological and physiological benefits, including stress reduction, improved mood, and enhanced cognitive function. Studies have demonstrated that exposure to greenery can alleviate symptoms of mental illnesses such as depression and anxiety, contributing to overall mental well-being. Moreover, green spaces facilitate physical activity, promoting healthier lifestyles and reducing the risk of chronic diseases such as obesity and cardiovascular conditions. As such, the presence of parks and recreational areas in urban settings not only fosters community cohesion but also supports public health initiatives, ultimately enriching the quality of life for residents [ 17 ]. Environmental Sustainability: In addition to their positive impact on human health, green spaces play a crucial role in mitigating environmental degradation and combating climate change in urban areas. Urban forests and vegetation act as natural carbon sinks, sequestering carbon dioxide from the atmosphere and mitigating the urban heat island effect. Trees and vegetation also help regulate local temperatures, reduce energy consumption for cooling purposes, and improve air quality by filtering pollutants and particulate matter. Furthermore, green infrastructure such as rain gardens and green roofs provides sustainable solutions for storm water management, reducing the risk of urban flooding and enhancing water quality. By preserving biodiversity and ecological balance, green spaces contribute to the overall resilience of urban ecosystems, safeguarding essential ecosystem services for future generations [ 18 ]. Urban Resilience: The integration of green spaces into urban planning is critical for building resilient cities capable of adapting to environmental challenges and socio-economic disruptions. Green infrastructure serves as a buffer against natural hazards such as floods, storms, and heatwaves, providing essential ecosystem services that enhance the resilience of urban communities. For instance, urban greenery absorbs excess rainfall, reduces surface runoff, and prevents soil erosion, thus minimizing the impact of extreme weather events on infrastructure and human settlements. Moreover, green spaces contribute to social resilience by fostering community cohesion, strengthening social networks, and promoting collective responses to crises. During times of crisis, such as the COVID-19 pandemic, parks and green areas have emerged as essential spaces for outdoor recreation, exercise, and mental rejuvenation, highlighting their role as resilient assets in urban environments [ 19 , 20 ]. Connectivity Utilizing the Confer Sensinode 2.6 software, connectivity analysis is conducted on various indices in conjunction with the ArcGIS extension proposed by Saura and Torne (2009). This software facilitates the quantification of habitat area importance and links for maintaining or enhancing landscape connectivity, while also assessing the impact of habitat and land use changes on connectivity. The study focuses on grassland plants within an urban setting, taking into consideration the diverse dispersal distances of different species as documented by Cain et al. (2000) and Donath et al. (2003). Notably, most seed dispersal distances exceed 100 meters, with Thomson et al. (2011) reporting a median seed dispersal distance of 2.1 meters and a mean dispersal distance of 44 meters for various dispersal types. Wind-dispersed herbs in urban areas are assumed to have a long-distance dispersal distance of 100 meters. To represent various scenarios, four dispersal distances are selected. The chosen parameters for landscape connectivity include the number of links, the number of components, and the Integral Index of Connectivity (IIC), which are calculated using a binary model. These parameters elucidate the landscape connection of habitat patches within heterogeneous land, with links denoting connections between nodes at different threshold distances in urban green spaces, and the number of connected regions (NC) indicating the number of connected regions. Given the research objective's fusion of ecological planning and sustainable development principles, the IIC is selected for habitat patch connectivity, as recommended by Pascual-Hortal and Saura (2006), emphasizing the shortest path. Confer Sensinode offers two types of connection models: a binary model index and a probabilistic model index. For this study, the binary model index is employed to assess the importance of each habitat patch in maintaining connectivity. Each patch is assigned a dIIC value, representing its significance for connectivity in percentage terms. Results and discussion Network and connectivity indices In this paper binary network type connectivity indices are analyzed, the connectivity indices are integral index connectivity (IIC) are calculated for the ecosystem balance. A graph theory representation of nodes and links in components. IIC a habitat availability index based on a binary network, assessing the possibilities of dispersal between all pairs of patches. The connectivity calculated at different threshold distances 2km, 20km. 44 km, and 100km. Table no 1 overall indices of number of component (NC), Number of links(NL) and Integral index connectivity of urban grassland Measure Connectivity Dispersal distance 2km 20km 44km 100km NL 93 1381 3570 5834 NC 44 3 1 1 IIC 378564.40 953445.00 1403858.00 1650246.00 Figure no 2 All over indices value in different threshold distance (NL number of links, NC NC Number of Component, IIC Integral Index Connectivity) Figure no 3 Number of Link at different threshold distance Figure no 4 Integral Index connectivity at different threshold distance Figure no 5 Number of component at different threshold distance Table 1 presents the overall indices pertaining to the connectivity analysis of urban grassland, focusing on dispersal distances ranging from 2 kilometers to 100 kilometers. The table includes three key indices: Number of Links (NL), Number of Components (NC), and Integral Index Connectivity (IIC). NL represents the total number of links connecting habitat patches within the landscape. As the dispersal distance increases, NL also tends to increase, indicating a greater number of connections established between patches. For instance, at a dispersal distance of 2 kilometers, there are 93 links, whereas at 100 kilometers, this number rises significantly to 5,834, highlighting the extensive connectivity across the landscape at longer dispersal distances. NC denotes the number of distinct connected regions within the landscape. A lower NC value suggests a more fragmented landscape with fewer connected regions. In this study, NC decreases substantially as dispersal distance increases. At shorter dispersal distances (2 kilometers), there are 44 connected regions, whereas at longer dispersal distances (100 kilometers), only one connected region is observed. This indicates that as dispersal distances increase, the landscape becomes more interconnected, resulting in fewer distinct regions. IIC, the Integral Index Connectivity, provides a comprehensive measure of habitat patch connectivity considering both NL and NC. It reflects the overall connectivity and landscape permeability for species movement. As dispersal distance increases, IIC values also increase, indicating higher levels of landscape connectivity. This suggests that larger dispersal distances facilitate greater connectivity among habitat patches, thereby enhancing overall landscape integrity and ecological functionality. In summary, the table demonstrates how dispersal distance influences landscape connectivity indices, with longer distances generally associated with increased connectivity, fewer distinct regions, and higher overall connectivity values as measured by IIC. These findings have implications for ecological planning and conservation efforts aimed at maintaining or enhancing landscape connectivity for urban grassland ecosystems. Figure no 6 Integral index connectivity (a) 2 km, (b) 20 km, (c) 44 km, (d) 100 km The total area of Bhopal city spans approximately 287.17 square kilometers, equivalent to 28717 hectares. Within this urban landscape, there exists a vital component known as urban green spaces, comprising an area of 17.421 square kilometers or 1742.12 hectares. These green spaces serve as essential ecological and recreational hubs within the urban fabric. To better understand the interconnectedness and accessibility of these urban green spaces, an assessment utilizing the Integral Index Connectivity was conducted. This index provides a comprehensive measure that reacts to various changes in a consistent and desirable manner, making it an ideal tool for evaluating connectivity within urban environments. The findings revealed that the importance of Integral Index Connectivity varied across the urban green spaces, with the highest significance observed in the larger expanses of greenery. This underscores the critical role played by these larger green spaces in maintaining connectivity within the urban ecosystem. Furthermore, the evaluation of current urban green space connectivity across dispersal distances ranging from 2 kilometers to 100 kilometers unveiled noteworthy insights. Particularly, species with a dispersal capacity of 20 kilometers were identified as being significantly impacted by the current distribution of habitat patches. This emphasizes the urgent need to safeguard and protect the larger green spaces to enhance the connectivity of isolated green patches within the urban landscape. In essence, the study underscores the importance of preserving and enhancing connectivity within urban green spaces, especially by prioritizing the protection of larger green areas. By doing so, cities like Bhopal can ensure the sustainability and resilience of their urban ecosystems for generations to come. Integral index connectivity The calculation of the DIIC (Derived IIC) value provides a specific measure for each patch within a habitat landscape. Patches with a high IIC value are crucial for maintaining existing connectivity. These high IIC value patches serve as vital hubs within the ecological network, facilitating the movement and exchange of species between various habitats. They play a fundamental role in preserving the ecological integrity of the landscape by ensuring that different patches remain well-connected. In addition to prioritizing the protection of high IIC value patches, it's essential to also consider patches with lower IIC values in nature conservation efforts. While these patches may not serve as central hubs, they still hold significance, particularly as potential stepping stones for species that disperse over long distances. Including these patches in conservation strategies can enhance overall habitat connectivity and support biodiversity conservation. When assessing ecological improvements such as the introduction of native plant species, it's important to focus on well-connected sites. This approach ensures that the benefits of such interventions extend throughout the landscape. However, it's crucial to acknowledge the significance of patches across the entire city, as even those with lower connectivity have value in maintaining ecological processes. Considering all patches in habitat connectivity efforts helps minimize the risk of isolation and enhances the resilience of the overall ecosystem. To effectively enhance habitat connectivity, it's essential to characterize both patches and the gaps between them within the landscape. This comprehensive understanding of the spatial distribution and connectivity of patches allows for targeted conservation actions and interventions aimed at bridging gaps and strengthening ecological networks across the landscape. Conclusion In urban environments, the movement of species between patches of habitat is often hindered by the presence of manmade structures, which act as barriers. Research by Beninde et al. (2015) underscores the critical importance of patch size in urban biodiversity. They suggest that, in contrast to patch connectivity, larger patches play a more significant role in sustaining species populations. This is supported by the findings of Crook and Sanjayan (2006), who highlight that the isolation of species populations significantly increases their susceptibility to extinction. Our study, however, did not identify effective green spaces within the city. Instead, we observed that larger distances between patches tended to be well connected, while smaller distances often led to isolated green spaces. To better understand and prioritize habitat patches, we employed a graph theory approach, which considers both intra-patch and inter-patch connectivity. This method provided invaluable insights into the landscape's structure and enabled us to identify key areas for conservation and restoration efforts. In our study area, we recognized the absence of existing well-connected green spaces, suggesting a need for conservation and restoration initiatives. By adopting a community-based approach, we aim to enhance biodiversity by focusing on increasing patch sizes and improving connectivity between habitats. This underscores the paramount importance of maintaining ecological integrity in urban green spaces. Urban green spaces are crucial not only for maintaining ecosystem balance but also for enhancing the well-being of both nature and human communities. Through our research, we emphasize the significance of preserving and restoring these vital habitats, recognizing their immense value for both biodiversity conservation and human enjoyment. Declarations Author Contribution single authorship paper so all credit to correspondence author References Andreas Zetterberg∗, U. M. M. B. B., 2010. Making graph theory operational for landscape ecological assessments, Landscape and Urban Planning, p. 181–191. Aversa1, E. V. a. J., 2013. A Graph theory approach for geovisualization of land use change: An application to Lisbon. Geography Publications and Research, p. 48. Bunn, A. U. D. K. T., 2000. a conservation application of graph theory. Landscape connectivity: a conservation , 59(Environ. manage), pp. 256–278. chow WTL, P. R. M. C. e. a., 2011. Observing and modeling the nocturnal park cool island of an arid city: Horizontal and vertical impacts. Theoretical and applied Climatology, pp. 197–211. Gabriella Baranyia, S. S. J. P. F. J., 2011. Contribution of habitat patches to network connectivity: Redundancy and uniqueness of topological indices. Gabriella Baranyia, Santiago Saurab, János Podanic, Ferenc Jordánd, ∗ , 11(Ecological Indicators), p. 1301–1310. Green, M. A. S. D. M., 2005. Dispersal and the metapopulation paradigm in amphibian ecology and conservation: are all amphibian populations met populations? Ecography , 28(1), pp. 110–128. Jasson C, J. P. G. D., 2007. Near Surface climate in an vegetated park and its surroundings. Theoretical and Applied Climatology, pp. 185–193. Keitt, D. U. T., 2001. LANDSCAPE CONNECTIVITY: A GRAPH-THEORETIC PERSPECTIVE. ecological society of America, 82(5), pp. 1205–1218. Laita A, K. J. M. M., 2011. Graph theoretic connectivity measures: what do they tell us about connectivity? Landscape Ecology , Volume 26, p. 951–967. Örjan Bodina, b. S. S., 2010. Ranking individual habitat patches as connectivity providers: Integrating network analysis and patch removal experiments. Elsevier, 221(Ecological Modelling), p. 2393–2405. Rubio, S. S. a. L., 2010. A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography, Volume 33, pp. 523–537. Santiago Saura ∗, L. P.-H., 2007. A new habitat availability index to integrate connectivity in landscape conservation planning: Comparison with existing indices and application to a case study. Elsevier, 83(Landscape and Urban Planning), p. 91–103. Santiago Saura a, b. J. T. a., 2009. Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity. Elsevier , 24(Environmental Modelling & Software), p. 135–139. Santiago Sauraa, ∗. C. E. C. M. M. R.-F., 2011. Network analysis to assess landscape connectivity trends: Application to European forests (1990–2000). Elsevier , 11(Ecological Indicators), p. 407–416. Saura*, L. P.-H. a. S., 2006. Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Springer , 21(Landscape Ecology), p. 959–967. Schick, D. L. U. E. S. M. E. A. T. R. S., 2009. Graph models of habitat mosaics. Ecology letters, 12(3), pp. 260–273. Beatley, T. (2011). Biophilic cities: Integrating nature into urban design and planning. Island Press. Bratman, G. N., et al. (2019). Nature and mental health: An ecosystem service perspective. Science Advances, 5(7), eaax0903. Escobedo, F. J., et al. (2011). The socio-economic contribution of green spaces to public health and well-being: A multi-scale analysis in Panama City. Environmental Science & Policy, 14(8), 797–805. United Nations. (2018). World Urbanization Prospects: The 2018 Revision. United Nations Department of Economic and Social Affairs, Population Division. Additional Declarations No competing interests reported. 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India","fulltext":[{"header":"Introduction","content":"\u003cp\u003eConnectivity is important for the dispersal of species and other ecological flows in landscape it is considered for biodiversity conservation and planning. Climate change and fragmentation of patch is an impact on the loss of native flora and fauna. Some species shift to other geographical areas caused by climate change variation they migrated in the suitable habitable patch for growth. Connectivity ensures the possibility for dispersal and gene flow both of which are crucial to avoid the metapopulation decline and extinct. Connectivity is a loss between habitat patches is a major threat to the biodiversity conservation and ecological balance. The connectivity is an increase in interest in landscape management, planning, and design.\u003c/p\u003e \u003cp\u003eIn this context, graph theory is a powerful tool for representing the landscape pattern and performing complex analysis regarding landscape connectivity. Graph theory using an ecological application for connectivity of heterogeneous landscape for conservation and planning [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Urban green space comprises the park playground, wasteland, and all other habitats for whose vegetation is characterized by regular mowing can capture harbor and rare grassland biodiversity. graph theory as a computationally powerful adjacent tool and dealing with a large number of data sets [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This is needed for analysis of landscape connectivity in large numbers for habitat patches for connectivity. One Important limitation on studies of ecological values and potential restoration of urban habitat is a question for habitat connectivity which one of the most important studies in urban ecology [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Connectivity is determining the degree to which organisms and processes can move. The more connectivity is possible if more movement of species.\u003c/p\u003e \u003cp\u003eA graph is a set of nodes (vertices) and links (edges) such that each connects two nodes. Nodes represent the habitable patch and link is a distance between them for connection [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A set of an interconnected patch in the landscape for connectivity describing. The existences link between in each node implies the potential ability of an organism to directly dispersal of two patches and other patches. The link may have a physical corresponding on the landscape in the form corridor [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In ecological modeling, the link represents the functional connection between a pair of nodes(patches) and also obtained a functional distance of two nodes. Functional connectivity is not ensured in the landscape when the existing habitat units are physically contiguous but also when a permeable Matrix, a series of stepping stones or other connecting elements allow for the exchange of genetic material of particular organism between the habitat patch that might be physically distant [6 ]loss of landscape connectivity and the subsequent isolation of habitat patches can interfere with a genetic exchange, wildlife movement and seed dispersal among other ecological processes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Intensify landscape connectivity is a key role in modern biodiversity conservation strategies worldwide and get the best response to counteract the potential adverse effect of habitat fragmentation and facilities change geographical location in the natural range of species due to climate change [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Landscape-level planning is one important for landscape monitoring and conservation planning is related to connectivity of the rest natural habitats [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] which can be promoted through highly permeable landscape matrix or establishing new habitats.\u003c/p\u003e \u003cp\u003eGraph theory has a long tradition and was used in many fields but newcomer use in landscape ecology [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This study uses the approach of the habitat availability model, taking into account functional connectivity and specific of certain species [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The development of new graph-based landscape connectivity indices is quantifying the prioritization of habitat patch for conservation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Many incides have been used and proposed in the context of connectivity analysis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. But there is a lack of comprehensive understanding of their sensitivity to pattern structure and their behavior to different spatial changes, which seriously limits their proper interpretation and usefulness.\u003c/p\u003e"},{"header":"Method and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area\u003c/h2\u003e \u003cp\u003eBhopal, the capital and second-largest city of Madhya Pradesh, holds the moniker of the 'city of lakes' owing to its abundant water bodies. Situated between 23\u0026deg;08' to 23\u0026deg;20' North latitude and 77\u0026deg;01' to 77\u0026deg;30' East longitude, Bhopal spans an area of 287.17 square kilometers. In 2011, its population stood at 1.796\u0026nbsp;million and is projected to surpass 3\u0026nbsp;million by 2041, as per the Census data. Administered by the Bhopal Municipal Corporation, the city is divided into 70 wards. Notably, the average elevation of Bhopal is around 500 meters, lending it a scenic charm in the central Indian landscape.\u003c/p\u003e \u003cp\u003eOne of the defining features of Bhopal's urban landscape is its extensive green spaces, including parks, playgrounds, and other recreational areas. These green zones provide essential breathing spaces amidst the urban sprawl and contribute significantly to the city's environmental well-being. The presence of lush parks and verdant playgrounds enhances the quality of life for residents, offering opportunities for leisure, exercise, and social interaction.\u003c/p\u003e \u003cp\u003eCentral to Bhopal's geography are its two iconic lakes: The Upper Lake and the Lower Lake. These water bodies not only add to the city's aesthetic appeal but also serve as vital reservoirs, supporting various ecological systems and providing a source of water for local communities. The serene ambiance surrounding these lakes makes them popular recreational spots, attracting tourists and locals alike.\u003c/p\u003e \u003cp\u003eAs Bhopal continues to grow and evolve, the preservation and expansion of its green spaces become paramount. Efforts to maintain biodiversity, mitigate pollution, and promote sustainable urban development are essential to safeguarding the city's natural heritage for future generations. By prioritizing the creation and maintenance of green infrastructure, Bhopal can uphold its reputation as a vibrant, livable city amidst the bustling landscape of central India.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFigure no\u003c/strong\u003e \u003cp\u003e1 study area map\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMapping of urban green space\u003c/h2\u003e \u003cp\u003eUrban Greenland\u0026rsquo;s of Bhopal city is mapped by using the Google earth of recent images. Polygons of habitat patch area digitizing in ARC GIS software and create a shape file for further analysis in confer sensinode software for landscape connectivity of habitat patch which is presented in the Study area. We extract 110 habitat patch in the spatial area and total area of habitat patch is 1742.12 hectare.\u003c/p\u003e \u003cp\u003eUrban Greenland, a term often used to describe green spaces within urban areas, has been mapped in Bhopal city using recent images from Google Earth. The process involved digitizing polygons to delineate habitat patch areas using ARC GIS software. This data was then utilized to create a shape file for further analysis in confer Sensinode software, focusing on landscape connectivity of these habitat patches within the study area.\u003c/p\u003e \u003cp\u003eIn total, 110 habitat patches were identified within the spatial area under investigation, covering a combined area of 1742.12 hectares. This data provides valuable insights into the distribution and characteristics of green spaces within the urban environment of Bhopal. Analyzing the connectivity of these patches can offer crucial information for urban planning and conservation efforts, aiding in the preservation and enhancement of green infrastructure within the city. By understanding how these habitat patches are interconnected, stakeholders can make informed decisions to promote biodiversity, mitigate environmental impacts, and enhance the overall quality of life for urban residents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGreen Space\u003c/h2\u003e \u003cp\u003eGreen spaces are fundamental components of urban environments, offering a myriad of benefits to residents and ecosystems alike. These areas, encompassing parks, gardens, urban forests, and green infrastructure, play a pivotal role in enhancing the quality of life in cities. As urbanization accelerates globally, the importance of integrating green spaces into urban planning becomes increasingly evident. This essay explores the multifaceted significance of green spaces in urban areas, addressing their impact on human well-being, environmental sustainability, and urban resilience, supported by empirical evidence and scholarly research. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eEnhancing Human Well-being: Green spaces serve as vital sanctuaries for urban dwellers, offering opportunities for relaxation, recreation, and social interaction. Access to nature within cities has been linked to numerous psychological and physiological benefits, including stress reduction, improved mood, and enhanced cognitive function. Studies have demonstrated that exposure to greenery can alleviate symptoms of mental illnesses such as depression and anxiety, contributing to overall mental well-being. Moreover, green spaces facilitate physical activity, promoting healthier lifestyles and reducing the risk of chronic diseases such as obesity and cardiovascular conditions. As such, the presence of parks and recreational areas in urban settings not only fosters community cohesion but also supports public health initiatives, ultimately enriching the quality of life for residents [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEnvironmental Sustainability: In addition to their positive impact on human health, green spaces play a crucial role in mitigating environmental degradation and combating climate change in urban areas. Urban forests and vegetation act as natural carbon sinks, sequestering carbon dioxide from the atmosphere and mitigating the urban heat island effect. Trees and vegetation also help regulate local temperatures, reduce energy consumption for cooling purposes, and improve air quality by filtering pollutants and particulate matter. Furthermore, green infrastructure such as rain gardens and green roofs provides sustainable solutions for storm water management, reducing the risk of urban flooding and enhancing water quality. By preserving biodiversity and ecological balance, green spaces contribute to the overall resilience of urban ecosystems, safeguarding essential ecosystem services for future generations [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUrban Resilience: The integration of green spaces into urban planning is critical for building resilient cities capable of adapting to environmental challenges and socio-economic disruptions. Green infrastructure serves as a buffer against natural hazards such as floods, storms, and heatwaves, providing essential ecosystem services that enhance the resilience of urban communities. For instance, urban greenery absorbs excess rainfall, reduces surface runoff, and prevents soil erosion, thus minimizing the impact of extreme weather events on infrastructure and human settlements. Moreover, green spaces contribute to social resilience by fostering community cohesion, strengthening social networks, and promoting collective responses to crises. During times of crisis, such as the COVID-19 pandemic, parks and green areas have emerged as essential spaces for outdoor recreation, exercise, and mental rejuvenation, highlighting their role as resilient assets in urban environments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eConnectivity\u003c/h2\u003e \u003cp\u003eUtilizing the Confer Sensinode 2.6 software, connectivity analysis is conducted on various indices in conjunction with the ArcGIS extension proposed by Saura and Torne (2009). This software facilitates the quantification of habitat area importance and links for maintaining or enhancing landscape connectivity, while also assessing the impact of habitat and land use changes on connectivity. The study focuses on grassland plants within an urban setting, taking into consideration the diverse dispersal distances of different species as documented by Cain et al. (2000) and Donath et al. (2003). Notably, most seed dispersal distances exceed 100 meters, with Thomson et al. (2011) reporting a median seed dispersal distance of 2.1 meters and a mean dispersal distance of 44 meters for various dispersal types. Wind-dispersed herbs in urban areas are assumed to have a long-distance dispersal distance of 100 meters.\u003c/p\u003e \u003cp\u003eTo represent various scenarios, four dispersal distances are selected. The chosen parameters for landscape connectivity include the number of links, the number of components, and the Integral Index of Connectivity (IIC), which are calculated using a binary model. These parameters elucidate the landscape connection of habitat patches within heterogeneous land, with links denoting connections between nodes at different threshold distances in urban green spaces, and the number of connected regions (NC) indicating the number of connected regions.\u003c/p\u003e \u003cp\u003eGiven the research objective's fusion of ecological planning and sustainable development principles, the IIC is selected for habitat patch connectivity, as recommended by Pascual-Hortal and Saura (2006), emphasizing the shortest path. Confer Sensinode offers two types of connection models: a binary model index and a probabilistic model index. For this study, the binary model index is employed to assess the importance of each habitat patch in maintaining connectivity. Each patch is assigned a dIIC value, representing its significance for connectivity in percentage terms.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eNetwork and connectivity indices\u003c/h2\u003e\n \u003cp\u003eIn this paper binary network type connectivity indices are analyzed, the connectivity indices are integral index connectivity (IIC) are calculated for the ecosystem balance. A graph theory representation of nodes and links in components. IIC a habitat availability index based on a binary network, assessing the possibilities of dispersal between all pairs of patches. The connectivity calculated at different threshold distances 2km, 20km. 44 km, and 100km.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable no\u0026nbsp;\u003c/strong\u003e1 overall indices of number of component (NC), Number of links(NL) and Integral index connectivity of urban grassland\u003c/p\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eMeasure Connectivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eDispersal distance\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2km\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e20km\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e44km\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e100km\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5834\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e378564.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e953445.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1403858.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1650246.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure no\u0026nbsp;\u003c/strong\u003e2 All over indices value in different threshold distance (NL number of links, NC\u003c/p\u003e\n \u003cp\u003eNC Number of Component, IIC Integral Index Connectivity)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure no\u0026nbsp;\u003c/strong\u003e3 Number of Link at different threshold distance\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure no\u0026nbsp;\u003c/strong\u003e4 Integral Index connectivity at different threshold distance\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure no\u0026nbsp;\u003c/strong\u003e5 Number of component at different threshold distance\u003c/p\u003e\n \u003cp\u003eTable\u0026nbsp;1 presents the overall indices pertaining to the connectivity analysis of urban grassland, focusing on dispersal distances ranging from 2 kilometers to 100 kilometers. The table includes three key indices: Number of Links (NL), Number of Components (NC), and Integral Index Connectivity (IIC).\u003c/p\u003e\n \u003cp\u003eNL represents the total number of links connecting habitat patches within the landscape. As the dispersal distance increases, NL also tends to increase, indicating a greater number of connections established between patches. For instance, at a dispersal distance of 2 kilometers, there are 93 links, whereas at 100 kilometers, this number rises significantly to 5,834, highlighting the extensive connectivity across the landscape at longer dispersal distances.\u003c/p\u003e\n \u003cp\u003eNC denotes the number of distinct connected regions within the landscape. A lower NC value suggests a more fragmented landscape with fewer connected regions. In this study, NC decreases substantially as dispersal distance increases. At shorter dispersal distances (2 kilometers), there are 44 connected regions, whereas at longer dispersal distances (100 kilometers), only one connected region is observed. This indicates that as dispersal distances increase, the landscape becomes more interconnected, resulting in fewer distinct regions.\u003c/p\u003e\n \u003cp\u003eIIC, the Integral Index Connectivity, provides a comprehensive measure of habitat patch connectivity considering both NL and NC. It reflects the overall connectivity and landscape permeability for species movement. As dispersal distance increases, IIC values also increase, indicating higher levels of landscape connectivity. This suggests that larger dispersal distances facilitate greater connectivity among habitat patches, thereby enhancing overall landscape integrity and ecological functionality.\u003c/p\u003e\n \u003cp\u003eIn summary, the table demonstrates how dispersal distance influences landscape connectivity indices, with longer distances generally associated with increased connectivity, fewer distinct regions, and higher overall connectivity values as measured by IIC. These findings have implications for ecological planning and conservation efforts aimed at maintaining or enhancing landscape connectivity for urban grassland ecosystems.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure no\u0026nbsp;\u003c/strong\u003e6 Integral index connectivity (a) 2 km, (b) 20 km, (c) 44 km, (d) 100 km\u003c/p\u003e\n \u003cp\u003eThe total area of Bhopal city spans approximately 287.17 square kilometers, equivalent to 28717 hectares. Within this urban landscape, there exists a vital component known as urban green spaces, comprising an area of 17.421 square kilometers or 1742.12 hectares. These green spaces serve as essential ecological and recreational hubs within the urban fabric.\u003c/p\u003e\n \u003cp\u003eTo better understand the interconnectedness and accessibility of these urban green spaces, an assessment utilizing the Integral Index Connectivity was conducted. This index provides a comprehensive measure that reacts to various changes in a consistent and desirable manner, making it an ideal tool for evaluating connectivity within urban environments.\u003c/p\u003e\n \u003cp\u003eThe findings revealed that the importance of Integral Index Connectivity varied across the urban green spaces, with the highest significance observed in the larger expanses of greenery. This underscores the critical role played by these larger green spaces in maintaining connectivity within the urban ecosystem.\u003c/p\u003e\n \u003cp\u003eFurthermore, the evaluation of current urban green space connectivity across dispersal distances ranging from 2 kilometers to 100 kilometers unveiled noteworthy insights. Particularly, species with a dispersal capacity of 20 kilometers were identified as being significantly impacted by the current distribution of habitat patches. This emphasizes the urgent need to safeguard and protect the larger green spaces to enhance the connectivity of isolated green patches within the urban landscape.\u003c/p\u003e\n \u003cp\u003eIn essence, the study underscores the importance of preserving and enhancing connectivity within urban green spaces, especially by prioritizing the protection of larger green areas. By doing so, cities like Bhopal can ensure the sustainability and resilience of their urban ecosystems for generations to come.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eIntegral index connectivity\u003c/h2\u003e\n \u003cp\u003eThe calculation of the DIIC (Derived IIC) value provides a specific measure for each patch within a habitat landscape. Patches with a high IIC value are crucial for maintaining existing connectivity. These high IIC value patches serve as vital hubs within the ecological network, facilitating the movement and exchange of species between various habitats. They play a fundamental role in preserving the ecological integrity of the landscape by ensuring that different patches remain well-connected.\u003c/p\u003e\n \u003cp\u003eIn addition to prioritizing the protection of high IIC value patches, it\u0026apos;s essential to also consider patches with lower IIC values in nature conservation efforts. While these patches may not serve as central hubs, they still hold significance, particularly as potential stepping stones for species that disperse over long distances. Including these patches in conservation strategies can enhance overall habitat connectivity and support biodiversity conservation.\u003c/p\u003e\n \u003cp\u003eWhen assessing ecological improvements such as the introduction of native plant species, it\u0026apos;s important to focus on well-connected sites. This approach ensures that the benefits of such interventions extend throughout the landscape. However, it\u0026apos;s crucial to acknowledge the significance of patches across the entire city, as even those with lower connectivity have value in maintaining ecological processes. Considering all patches in habitat connectivity efforts helps minimize the risk of isolation and enhances the resilience of the overall ecosystem.\u003c/p\u003e\n \u003cp\u003eTo effectively enhance habitat connectivity, it\u0026apos;s essential to characterize both patches and the gaps between them within the landscape. This comprehensive understanding of the spatial distribution and connectivity of patches allows for targeted conservation actions and interventions aimed at bridging gaps and strengthening ecological networks across the landscape.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn urban environments, the movement of species between patches of habitat is often hindered by the presence of manmade structures, which act as barriers. Research by Beninde et al. (2015) underscores the critical importance of patch size in urban biodiversity. They suggest that, in contrast to patch connectivity, larger patches play a more significant role in sustaining species populations. This is supported by the findings of Crook and Sanjayan (2006), who highlight that the isolation of species populations significantly increases their susceptibility to extinction.\u003c/p\u003e \u003cp\u003eOur study, however, did not identify effective green spaces within the city. Instead, we observed that larger distances between patches tended to be well connected, while smaller distances often led to isolated green spaces. To better understand and prioritize habitat patches, we employed a graph theory approach, which considers both intra-patch and inter-patch connectivity. This method provided invaluable insights into the landscape's structure and enabled us to identify key areas for conservation and restoration efforts.\u003c/p\u003e \u003cp\u003eIn our study area, we recognized the absence of existing well-connected green spaces, suggesting a need for conservation and restoration initiatives. By adopting a community-based approach, we aim to enhance biodiversity by focusing on increasing patch sizes and improving connectivity between habitats. This underscores the paramount importance of maintaining ecological integrity in urban green spaces.\u003c/p\u003e \u003cp\u003eUrban green spaces are crucial not only for maintaining ecosystem balance but also for enhancing the well-being of both nature and human communities. Through our research, we emphasize the significance of preserving and restoring these vital habitats, recognizing their immense value for both biodiversity conservation and human enjoyment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003esingle authorship paper so all credit to correspondence author\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndreas Zetterberg\u0026lowast;, U. M. M. B. B., 2010. Making graph theory operational for landscape ecological assessments, Landscape and Urban Planning, p. 181\u0026ndash;191.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAversa1, E. V. a. J., 2013. A Graph theory approach for geovisualization of land use change: An application to Lisbon. Geography Publications and Research, p. 48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBunn, A. U. D. K. T., 2000. a conservation application of graph theory. \u003cem\u003eLandscape connectivity: a conservation\u003c/em\u003e, 59(Environ. manage), pp. 256\u0026ndash;278.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003echow WTL, P. R. M. C. e. a., 2011. Observing and modeling the nocturnal park cool island of an arid city: Horizontal and vertical impacts. Theoretical and applied Climatology, pp. 197\u0026ndash;211.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGabriella Baranyia, S. S. J. P. F. J., 2011. Contribution of habitat patches to network connectivity: Redundancy and uniqueness of topological indices. \u003cem\u003eGabriella Baranyia, Santiago Saurab, J\u0026aacute;nos Podanic, Ferenc Jord\u0026aacute;nd, \u0026lowast;\u003c/em\u003e, 11(Ecological Indicators), p. 1301\u0026ndash;1310.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreen, M. A. S. D. M., 2005. Dispersal and the metapopulation paradigm in amphibian ecology and conservation: are all amphibian populations met populations? \u003cem\u003eEcography\u003c/em\u003e, 28(1), pp. 110\u0026ndash;128.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJasson C, J. P. G. D., 2007. Near Surface climate in an vegetated park and its surroundings. Theoretical and Applied Climatology, pp. 185\u0026ndash;193.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeitt, D. U. T., 2001. LANDSCAPE CONNECTIVITY: A GRAPH-THEORETIC PERSPECTIVE. ecological society of America, 82(5), pp. 1205\u0026ndash;1218.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaita A, K. J. M. M., 2011. Graph theoretic connectivity measures: what do they tell us about connectivity? \u003cem\u003eLandscape Ecology\u003c/em\u003e, Volume 26, p. 951\u0026ndash;967.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;rjan Bodina, b. S. S., 2010. Ranking individual habitat patches as connectivity providers: Integrating network analysis and patch removal experiments. Elsevier, 221(Ecological Modelling), p. 2393\u0026ndash;2405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubio, S. S. a. L., 2010. A common currency for the different ways in which patches and links can contribute to habitat availability and connectivity in the landscape. Ecography, Volume 33, pp. 523\u0026ndash;537.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantiago Saura \u0026lowast;, L. P.-H., 2007. A new habitat availability index to integrate connectivity in landscape conservation planning: Comparison with existing indices and application to a case study. Elsevier, 83(Landscape and Urban Planning), p. 91\u0026ndash;103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantiago Saura a, b. J. T. a., 2009. Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity. \u003cem\u003eElsevier\u003c/em\u003e, 24(Environmental Modelling \u0026amp; Software), p. 135\u0026ndash;139.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantiago Sauraa, \u0026lowast;. C. E. C. M. M. R.-F., 2011. Network analysis to assess landscape connectivity trends: Application to European forests (1990\u0026ndash;2000). \u003cem\u003eElsevier\u003c/em\u003e, 11(Ecological Indicators), p. 407\u0026ndash;416.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaura*, L. P.-H. a. S., 2006. Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. \u003cem\u003eSpringer\u003c/em\u003e, 21(Landscape Ecology), p. 959\u0026ndash;967.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchick, D. L. U. E. S. M. E. A. T. R. S., 2009. Graph models of habitat mosaics. Ecology letters, 12(3), pp. 260\u0026ndash;273.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeatley, T. (2011). Biophilic cities: Integrating nature into urban design and planning. Island Press.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBratman, G. N., et al. (2019). Nature and mental health: An ecosystem service perspective. Science Advances, 5(7), eaax0903.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEscobedo, F. J., et al. (2011). The socio-economic contribution of green spaces to public health and well-being: A multi-scale analysis in Panama City. Environmental Science \u0026amp; Policy, 14(8), 797\u0026ndash;805.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited Nations. (2018). World Urbanization Prospects: The 2018 Revision. United Nations Department of Economic and Social Affairs, Population Division.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Graph theory, connectivity, green space, ecological planning, and urban planning","lastPublishedDoi":"10.21203/rs.3.rs-4232378/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4232378/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGraph theory and network analysis are efficient to explore landscape connectivity. Graph theory approach using in urban planning to facilities the municipal service in the urban landscape. The municipal service is an important and proper functional movement in the urban landscape. In this paper, the use of graph-theoretic approaches is operational within the urban landscape assessment, planning, and design. Urban landscape for proper planning and design of urban land without disturbance of an ecosystem. The connectivity is important to exchange their genetic material for the proper functioning of the ecosystem in the urban landscape. In particular, the network model uses to evaluate the contribution of landscape elements to uphold the connectivity. The importance of spatially and geographically area representation the network in urban \u0026amp; regional planning and design is stressed. The study moves the better connectivity of urban green space for the functional ecosystem. Graph theory approach identifies the Intra connectivity(IC), Betweeness centrality (BC), connector, a number of links (NL), Harry Index (HI), landscape coincide Probability (LCP), and integral index connectivity (IIC) in the urban landscape for systematic planning and order to increase the efficiency of monitoring and sustainable urban development. Using a graph theory approach for patch connectivity with integral index connectivity (IIC). Here threshold distance for connectivity is 2m, 20m, 44m, and 100m. Connectivity of urban green space for dispersal of species for one patch to the rest of other patches slightly increases and identifies the prioritize patches for ecological improvement. This paper Examine the protecting ecosystem and sustainable urban development and planning in the future prospectus\u003c/p\u003e","manuscriptTitle":"Utilizing Graph Theory for Ecological Planning: Enhancing Connectivity of Urban Green Spaces in Bhopal, Madhya Pradesh, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-12 05:01:48","doi":"10.21203/rs.3.rs-4232378/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":"d363367c-2dd9-444c-a5e1-7a55ca1ee14b","owner":[],"postedDate":"April 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-12T05:01:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-12 05:01:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4232378","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4232378","identity":"rs-4232378","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}