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GPP of a Chinese Savanna Ecosystem during Different Phenological Phases Simulated from Harmonized Landsat and Sentinel-2 Data
Zhang, Xiang1,2; Xie, Shuai3; Zhang, Yiping; Song, Qinghai; Filippa, Gianluca4; Qi, Dehua
2024
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume16Issue:18Pages:-
Abstract

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's savanna ecosystems constitute only a small part of the world's 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.

Keywordeddy covariance HLS MODIS GPP phenology savanna
Subject AreaEnvironmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
DOI10.3390/rs16183475
Indexed BySCI
Language英语
WOS IDWOS:001323032600001
Citation statistics
Document Type期刊论文
Identifierhttps://ir.xtbg.ac.cn/handle/353005/14450
Collection全球变化研究组
Affiliation1.Chinese Acad Sci, CAS Key Lab Trop Forest Ecol, Xishuangbanna Trop Bot Garden, Xishuangbanna 666303, Peoples R China
2.Yunnan Univ, Sch Ecol & Environm Sci, Kunming 650500, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Qingdao Univ Technol, Sch Informat & Control Engn, Qingdao 266520, Peoples R China
5.ARPA Valle dAosta, Environm Protect Agcy Aosta Valley, Climate Change Unit, I-11020 St Christophe, Italy
Recommended Citation
GB/T 7714
Zhang, Xiang,Xie, Shuai,Zhang, Yiping,et al. GPP of a Chinese Savanna Ecosystem during Different Phenological Phases Simulated from Harmonized Landsat and Sentinel-2 Data[J]. REMOTE SENSING,2024,16(18):-.
APA Zhang, Xiang,Xie, Shuai,Zhang, Yiping,Song, Qinghai,Filippa, Gianluca,&Qi, Dehua.(2024).GPP of a Chinese Savanna Ecosystem during Different Phenological Phases Simulated from Harmonized Landsat and Sentinel-2 Data.REMOTE SENSING,16(18),-.
MLA Zhang, Xiang,et al."GPP of a Chinese Savanna Ecosystem during Different Phenological Phases Simulated from Harmonized Landsat and Sentinel-2 Data".REMOTE SENSING 16.18(2024):-.
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