Climate Change Data Portal
| DOI | 10.1029/2023JG007728 |
| Evaluation of Selected Sentinel-2 Remotely Sensed Vegetation Indices and MODIS GPP in Representing Productivity in Semi-Arid South African Ecosystems | |
| 发表日期 | 2024 |
| ISSN | 2169-8953 |
| EISSN | 2169-8961 |
| 起始页码 | 129 |
| 结束页码 | 4 |
| 卷号 | 129期号:4 |
| 英文摘要 | The ability to validate satellite observations with ground-based data sets is vital for the spatiotemporal assessment of productivity trends in semi-arid ecosystems. Modeling ecosystem scale parameters such as gross primary production (GPP) with the combination of satellite and ground-based data however requires a comprehensive understanding of the associated drivers of how the carbon balance of these ecosystems is impacted under climate change. We used GPP estimates from the partitioning of net ecosystem measurements (net ecosystem exchange) from three Eddy Covariance (EC) flux tower sites and applied linear regressions to evaluate the ability of Sentinel-2 vegetation indices (VIs) retrieved from Google Earth Engine to estimate GPP in semi-arid ecosystems. The Sentinel-2 normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and the land surface water index (LSWI) were each assessed separately, and also in combination with selected meteorological variables (incoming radiation, soil water content, air temperature, vapor pressure deficit) using a bi-directional stepwise linear regression to test whether this can improve GPP estimates. The performance of the MOD17AH2 8-day GPP was also tested across the sites. NDVI, EVI and LSWI were able to track the phase and amplitude patterns of EC estimated gross primary production (GPPEC) across all sites, albeit with phase delays observed especially at the Benfontein Savanna site (Ben_Sav). In all cases, the VI estimates improved with the addition of meteorological variables except for LSWI at Middleburg Karoo (Mid_Kar). The least improvement in R2 was observed in all EVI-based estimates-indicating the suitability of EVI as a single VI to estimate GPP. Our results suggest that while productivity assessments using a single VI may be more favorable, the inclusion of meteorological variables can be applied to improve single VIs estimates to accurately detect and characterize changes in GPP. In addition, we found that standard MODIS products better represent the phase than amplitude of productivity in semi-arid ecosystems, explaining between 68% and 83% of GPP variability. The study suggests that there is continued potential in estimating gross primary production in semi-arid ecosystems using satellite data in simple regression-based methods. While there are still some uncertainties in their performance, some of these can be reduced by combining satellite data and site-based meteorological variables in estimating gross primary production. Regarding the standard MODIS GPP product, this showed to better represent the phase than the amplitude of GPP in three semi-arid sites in South Africa. Sentinel-2 vegetation indices (VIs) have the potential to estimate gross primary production in semi-arid ecosystems Inclusion of meteorological variables improves the performance of VI based models to predict gross primary production Standard satellite gross primary production products better represent the phase than amplitude of gross primary production in semi-arid ecosystems |
| 英文关键词 | eddy covariance; semi-arid ecosystems; vegetation indices; gross primary production; meteorological variables |
| 语种 | 英语 |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology |
| WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary |
| WOS记录号 | WOS:001194323200001 |
| 来源期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/294953 |
| 作者单位 | Stellenbosch University; National Research Foundation - South Africa; South African Environmental Observation Network (SAEON); University of Pretoria; Johann Heinrich von Thunen Institute |
| 推荐引用方式 GB/T 7714 | . Evaluation of Selected Sentinel-2 Remotely Sensed Vegetation Indices and MODIS GPP in Representing Productivity in Semi-Arid South African Ecosystems[J],2024,129(4). |
| APA | (2024).Evaluation of Selected Sentinel-2 Remotely Sensed Vegetation Indices and MODIS GPP in Representing Productivity in Semi-Arid South African Ecosystems.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,129(4). |
| MLA | "Evaluation of Selected Sentinel-2 Remotely Sensed Vegetation Indices and MODIS GPP in Representing Productivity in Semi-Arid South African Ecosystems".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 129.4(2024). |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
