Article ; Online: Modeling crop yield using NDVI-derived VGM metrics across different climatic regions in the USA.
International journal of biometeorology
2023 Volume 67, Issue 6, Page(s) 1051–1062
Abstract: An accurate, cost-efficient, and early crop yield projection is a national and global necessity. This study is aimed to achieve the national demands by proposing crop yield estimation models on the Google Earth Engine (GEE) platform. This study directly ... ...
Abstract | An accurate, cost-efficient, and early crop yield projection is a national and global necessity. This study is aimed to achieve the national demands by proposing crop yield estimation models on the Google Earth Engine (GEE) platform. This study directly used dynamic crop phenology metrics to model soybean crop yield by considering climatic regions in the USA (e.g., Central, East, Northeast, South, Southeast, and West North Central regions). We modeled soybean yields with vegetative growth metrics (VGMs) of NDVI narrated as VGM70 (avg. NDVI of 70 days from the emergence), VGM85 (avg. NDVI of 85 days from the emergence), VGM98T (total NDVI of 98 days from the emergence), VGM120 (avg. NDVI of 120 days from the emergence), VGM |
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MeSH term(s) | Benchmarking ; Seasons ; Temperature ; Agriculture ; Linear Models ; Glycine max |
Language | English |
Publishing date | 2023-05-17 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 280324-0 |
ISSN | 1432-1254 ; 0020-7128 |
ISSN (online) | 1432-1254 |
ISSN | 0020-7128 |
DOI | 10.1007/s00484-023-02478-4 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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