{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T05:42:35Z","timestamp":1776490955652,"version":"3.51.2"},"reference-count":74,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:00:00Z","timestamp":1565308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Precise quantification of terrestrial gross primary production (GPP) has been recognized as one of the most important components in understanding the carbon balance between the biosphere and the atmosphere. In recent years, although many large-scale GPP estimates from satellite data and ecosystem models have been generated, few attempts have been made to compare the different GPP products at national scales, particularly for various climate zones. In this study, two of the most widely-used GPP datasets were systematically compared over the eight climate zones across China\u2019s terrestrial ecosystems from 2001 to 2015, which included the moderate resolution imaging spectroradiometer (MODIS) GPP and the breathing Earth system simulator (BESS) GPP products. Additionally, the coarse (0.05o) GPP estimates from the vegetation photosynthesis model (VPM) at the same time scale were used for auxiliary analysis with the two products. Both MODIS and BESS products exhibited a decreasing trend from the southeast region to the northwest inland. The largest GPP was found in the tropical humid region with 5.49 g C m\u22122 d\u22121 and 5.07 g C m\u22122 d\u22121 for MODIS and BESS, respectively, while the lowest GPP was distributed in the warm temperate arid region, midtemperate semiarid region and plateau zone. Meanwhile, the work confirmed that all these GPP products showed apparent seasonality with the peaks in the summertime. However, large differences were found in the interannual variations across the three GPP products over different climate regions. Generally, the BESS GPP agreed better than the MODIS GPP when compared to the seasonal and interannual variations of VPM GPP. Furthermore, the spatial correlation analysis between terrestrial GPP and the climatic factors, including temperature and precipitation, indicated that natural rainfall dominated the variability in GPP of Northern China, such as the midtemperate semiarid region, while temperature was a key controlling factor in the Southern China and the Tibet Plateau area.<\/jats:p>","DOI":"10.3390\/rs11161855","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T11:11:31Z","timestamp":1565349091000},"page":"1855","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Contrasting Performance of the Remotely-Derived GPP Products over Different Climate Zones across China"],"prefix":"10.3390","volume":"11","author":[{"given":"Yanan","family":"Chen","sequence":"first","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"given":"Hongfan","family":"Gu","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"given":"Munan","family":"Wang","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"given":"Qing","family":"Gu","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"given":"Zhi","family":"Ding","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3783-8363","authenticated-orcid":false,"given":"Mingguo","family":"Ma","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]},{"given":"Rongyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 10083, China"}]},{"given":"Xuguang","family":"Tang","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Kaster Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing 400715, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10215","DOI":"10.3390\/rs61010215","article-title":"Comparison of Different GPP Models in China Using MODIS Image and ChinaFLUX Data","volume":"6","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1111\/gcb.12079","article-title":"Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China","volume":"19","author":"Yu","year":"2013","journal-title":"Glob. 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