A 30-meter resolution global land productivity dynamics dataset from 2013 to 2022
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BORIS DOI
Publisher DOI
PubMed ID
40169667
Description
Land degradation is one of the most severe environmental challenges globally. To address its adverse impacts, the United Nations endorsed the Land Degradation Neutrality (SDG 15.3) within the Sustainable Development Goals in 2015. Trends in land productivity is a key sub-indicator for reporting the progress toward SDG 15.3. Currently, the highest spatial resolution of global land productivity dynamics (LPD) products is 250-meter, which seriously hamper the SDG 15.3 reporting and intervention at the fine scale. Generating higher spatial resolution product faces significant challenges, including massive data processing, image cloud pollution, incompatible spatiotemporal resolution. This study, leveraging Google Earth Engine platform and utilizing Landsat-8 and MODIS imagery, employed the Gap-filling and Savitzky–Golay filtering algorithm and advanced spatiotemporal filtering method to obtain a high-quality 30-meter NDVI dataset, then the global 30-meter LPD product from 2013 to 2022 was generated by using the FAO-WOCAT methodology and compared against multiple datasets. This is the first global scale 30-meter LPD dataset, which provides essential data support for SDG 15.3 monitoring and reporting globally.
Date of Publication
2025-04-01
Publication Type
Article
Language(s)
en
Contributor(s)
Li, Xiaosong | |
Shen, Tong | |
Garcia, Cesar Luis | |
Chen, Yang | |
Kabo-Bah, Amos Tiereyangn | |
Yang, Ziyu | |
Jia, Xiaoxia | |
Lu, Qi | |
Nyamtseren, Mandakh |
Series
Scientific Data
Publisher
Nature Research
ISSN
2052-4463
Related Project(s)
Access(Rights)
open.access