{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T08:00:05Z","timestamp":1782460805320,"version":"3.54.5"},"reference-count":86,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T00:00:00Z","timestamp":1649894400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971305"],"award-info":[{"award-number":["41971305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Europe Dragon 5 Cooperation Programme","award":["59197"],"award-info":[{"award-number":["59197"]}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20181474"],"award-info":[{"award-number":["BK20181474"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Net ecosystem productivity (NEP) plays an important role in understanding ecosystem function and the global carbon cycle. In this paper, the key parameters of the Carnegie Ames Stanford Approach (CASA) model, maximum light use efficiency (\u03b5max), was optimized by using vegetation classification data. Then, the NEP was estimated by coupling the optimized CASA model, geostatistical model of soil respiration (GSMSR) and the soil respiration\u2013soil heterotrophic respiration (Rs-Rh) relationship model. The ground observations from ChinaFLUX were used to verify the NEP estimation accuracy. The results showed that the R2 of the optimized CASA model increased from 0.411 to 0.774, and RMSE decreased from 21.425 gC\u00b7m\u22122\u00b7month\u22121 to 12.045 gC\u00b7m\u22122\u00b7month\u22121, indicating that optimizing CASA model by vegetation classification data was an effective method to improve the estimation accuracy of NEP. On this basis, the spatial and temporal distribution of NEP in China was analyzed. The research indicated that the monthly variation of NEP in China was a single peak curve with summer as the peak, which generally presented the pattern of southern region &gt; northern region &gt; Qinghai\u2013Tibet region &gt; northwest region. Furthermore, from 2001 to 2016, most regions of China showed a non-significant level upward trend, but main cropland (e.g., North China Plain and Northeast Plain) and some grassland (e.g., Ngari in Qinghai\u2013Tibet Plateau and Xilin Gol League in Inner Mongolia) showed a non-significant-level downward trend. The study can deepen the understanding of the distribution of carbon sources\/sinks in China, and provide a reference for regional carbon cycle research.<\/jats:p>","DOI":"10.3390\/rs14081902","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T02:39:31Z","timestamp":1650335971000},"page":"1902","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["Remote Sensing Estimation and Spatiotemporal Pattern Analysis of Terrestrial Net Ecosystem Productivity in China"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0331-3312","authenticated-orcid":false,"given":"Liang","family":"Liang","sequence":"first","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Geng","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyi","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyan","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuguo","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijuan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lianpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianrong","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s10661-009-1226-9","article-title":"Estimation and analysis of terrestrial net primary productivity over India by remote-sensing-driven terrestrial biosphere model","volume":"170","author":"Nayak","year":"2010","journal-title":"Environ. 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