Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses

Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses | 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 Characteristics of the evolution of vegetation NPP in Nanchang and spatial and temporal driver analyses Jiatong Li, Hua Wu, Yue Xu, Qiyun Guo, Huishan Li, Jianwei Zhou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4642920/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 In order to determine the evolution characteristics of net primary productivity of vegetation in Nanchang City and the main driving factors influencing its spatiotemporal evolution, based on the ArcGIS and Matlab platforms, ReliefF, Random Forest (RF),BP neural network, GRNN machine learning algorithm and geographic detector were used to quantitatively evaluate the evolution characteristics and spatiotemporal driving factors of Nanchang City from 1998 to 2015.The results show: 1) From a temporal perspective, NPP overall shows a fluctuating upward trend with distinct seasonal variations; spatially, it follows a distribution pattern of higher values in the middle and lower values around the edges; 2) The ReliefF algorithm has the highest fitting accuracy and is more suitable for regression analysis of NPP, with both algorithms indicating that air temperature and precipitation have the most significant impact on NPP evolution; 3) According to the results of the geographic detector, the NPP in Nanchang City is most significantly influenced by precipitation factors spatially, while the temporal dimension is dominated by human factors. In-depth study of the evolution characteristics of NPP can provide a scientific basis for quantifying the health of regional ecosystems and the balance of the ecological environment under the background of climate change. Net Primary Productivity (NPP) of vegetation machine learning algorithms geographic detector spatiotemporal evolution driver analysis. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-4642920","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323220083,"identity":"09d5899c-28a6-444c-8b71-915db82a9895","order_by":0,"name":"Jiatong Li","email":"","orcid":"","institution":"Tibet University","correspondingAuthor":false,"prefix":"","firstName":"Jiatong","middleName":"","lastName":"Li","suffix":""},{"id":323220089,"identity":"6aec3dc2-cbbe-40a0-842c-d0d8f8299549","order_by":1,"name":"Hua 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