{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:04:19Z","timestamp":1774944259333,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T00:00:00Z","timestamp":1726704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42075119"],"award-info":[{"award-number":["42075119"]}]},{"name":"National Natural Science Foundation of China","award":["31770528"],"award-info":[{"award-number":["31770528"]}]},{"name":"National Natural Science Foundation of China","award":["4191101289"],"award-info":[{"award-number":["4191101289"]}]},{"name":"National Natural Science Foundation of China","award":["41975147"],"award-info":[{"award-number":["41975147"]}]},{"name":"National Natural Science Foundation of China","award":["2016YFC0502105"],"award-info":[{"award-number":["2016YFC0502105"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["42075119"],"award-info":[{"award-number":["42075119"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["31770528"],"award-info":[{"award-number":["31770528"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["4191101289"],"award-info":[{"award-number":["4191101289"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["41975147"],"award-info":[{"award-number":["41975147"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFC0502105"],"award-info":[{"award-number":["2016YFC0502105"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Savannas are widespread biomes with highly valued ecosystem services. To successfully manage savannas in the future, it is critical to better understand the long-term dynamics of their productivity and phenology. However, accurate large-scale gross primary productivity (GPP) estimation remains challenging because of the high spatial and seasonal variations in savanna GPP. China\u2019s savanna ecosystems constitute only a small part of the world\u2019s savanna ecosystems and are ecologically fragile. However, studies on GPP and phenological changes, while closely related to climate change, remain scarce. Therefore, we simulated savanna ecosystem GPP via a satellite-based vegetation photosynthesis model (VPM) with fine-resolution harmonized Landsat and Sentinel-2 (HLS) imagery and derived savanna phenophases from phenocam images. From 2015 to 2018, we compared the GPP from HLS VPM (GPPHLS-VPM) simulations and that from Moderate-Resolution Imaging Spectroradiometer (MODIS) VPM simulations (GPPMODIS-VPM) with GPP estimates from an eddy covariance (EC) flux tower (GPPEC) in Yuanjiang, China. Moreover, the consistency of the savanna ecosystem GPP was validated for a conventional MODIS product (MOD17A2). This study clearly revealed the potential of the HLS VPM for estimating savanna GPP. Compared with the MODIS VPM, the HLS VPM yielded more accurate GPP estimates with lower root-mean-square errors (RMSEs) and slopes closer to 1:1. Specifically, the annual RMSE values for the HLS VPM were 1.54 (2015), 2.65 (2016), 2.64 (2017), and 1.80 (2018), whereas those for the MODIS VPM were 3.04, 3.10, 2.62, and 2.49, respectively. The HLS VPM slopes were 1.12, 1.80, 1.65, and 1.27, indicating better agreement with the EC data than the MODIS VPM slopes of 2.04, 2.51, 2.14, and 1.54, respectively. Moreover, HLS VPM suitably indicated GPP dynamics during all phenophases, especially during the autumn green-down period. As the first study that simulates GPP involving HLS VPM and compares satellite-based and EC flux observations of the GPP in Chinese savanna ecosystems, our study enables better exploration of the Chinese savanna ecosystem GPP during different phenophases and more effective savanna management and conservation worldwide.<\/jats:p>","DOI":"10.3390\/rs16183475","type":"journal-article","created":{"date-parts":[[2024,9,19]],"date-time":"2024-09-19T08:12:27Z","timestamp":1726733547000},"page":"3475","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["GPP of a Chinese Savanna Ecosystem during Different Phenological Phases Simulated from Harmonized Landsat and Sentinel-2 Data"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2777-0489","authenticated-orcid":false,"given":"Xiang","family":"Zhang","sequence":"first","affiliation":[{"name":"CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna 666303, China"},{"name":"School of Ecology and Environmental Sciences, Yunnan University, Kunming 650500, China"},{"name":"University of the Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Shuai","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China"}]},{"given":"Yiping","family":"Zhang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna 666303, China"}]},{"given":"Qinghai","family":"Song","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna 666303, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4554-6045","authenticated-orcid":false,"given":"Gianluca","family":"Filippa","sequence":"additional","affiliation":[{"name":"Climate Change Unit, Environmental Protection Agency of Aosta Valley, ARPA Valle dAosta, 11020 Saint Christophe, Italy"}]},{"given":"Dehua","family":"Qi","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna 666303, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9835284","DOI":"10.34133\/2022\/9835284","article-title":"Fensholt. 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