{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T19:13:39Z","timestamp":1774379619116,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,22]],"date-time":"2023-12-22T00:00:00Z","timestamp":1703203200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Research Plan in Key Areas of Xin jiang Production and Construction Corps","award":["2022AB016"],"award-info":[{"award-number":["2022AB016"]}]},{"name":"Science and Technology Research Plan in Key Areas of Xin jiang Production and Construction Corps","award":["2022NY03"],"award-info":[{"award-number":["2022NY03"]}]},{"name":"Science and the Technology Research Plan in Key Areas of Shihezi City","award":["2022AB016"],"award-info":[{"award-number":["2022AB016"]}]},{"name":"Science and the Technology Research Plan in Key Areas of Shihezi City","award":["2022NY03"],"award-info":[{"award-number":["2022NY03"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the net ecosystem productivity (NEP) is essential for understanding ecosystem functioning and the global carbon cycle. Utilizing meteorological and The Advanced Very High Resolution Radiometer (AVHRR) remote sensing data, this study employed the Carnegie\u2013Ames\u2013Stanford Approach (CASA) and the Geostatistical Model of Soil Respiration (GSMSR) to map a monthly vegetation NEP in China from 1982 to 2020. Then, we examined the spatiotemporal trends of NEP and identified the drivers of NEP changes using the Geodetector model. The mean NEP over the 39-year period amounted to 265.38 gC\u00b7m\u22122. Additionally, the average annual carbon sequestration amounted to 1.89 PgC, indicating a large carbon sink effect. From 1982 to 2020, there was a general fluctuating increasing trend observed in the annual mean NEP, exhibiting an overall average growth rate of 4.69 gC\u00b7m\u22122\u00b7a\u22121. The analysis revealed that the majority of the vegetation region in China, accounting for 93.45% of the entirety, exhibited increasing trends in NEP. According to the Geodetector analysis, precipitation change rate, solar radiation change rate, and altitude were the key driving factors in NEP change rate. Furthermore, the interaction between the precipitation change rate and altitude demonstrated the most significant effect.<\/jats:p>","DOI":"10.3390\/rs16010060","type":"journal-article","created":{"date-parts":[[2023,12,24]],"date-time":"2023-12-24T20:48:37Z","timestamp":1703450917000},"page":"60","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Exploring the Spatiotemporal Dynamics and Driving Factors of Net Ecosystem Productivity in China from 1982 to 2020"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2643-7496","authenticated-orcid":false,"given":"Yang","family":"Chen","sequence":"first","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"},{"name":"Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4032-8759","authenticated-orcid":false,"given":"Yongming","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1388-6588","authenticated-orcid":false,"given":"Tianyu","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"School of Advanced Technology, Xi\u2019an Jiaotong-Liverpool University, Suzhou 215123, China"}]},{"given":"Fei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"}]},{"given":"Shanyou","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1016\/j.scitotenv.2018.04.230","article-title":"Net ecosystem productivity and carbon dynamics of the traditionally managed Imperata grasslands of North East India","volume":"635","author":"Pathak","year":"2018","journal-title":"Sci. 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