Evaluating the benefits of chlorophyll fluorescence for in-season crop productivity forecasting
نویسندگان
چکیده
Remote sensing of solar-induced chlorophyll fluorescence (SIF) shows promise for monitoring the productivity global agricultural systems. SIF-based primary metrics have demonstrated higher fidelity to large-scale patterns crop than reflectance-based vegetation indices when averaged across growing season. In-season yield forecasting typically relies upon indices, raising question whether in-season could be improved by utilizing SIF. Here, we analyze US from USDA surveys and their relationships with coarse-resolution GOME-2 SIF, high-resolution downscaled metrics, MODIS NDVI, GPP. We find that NDVI exhibit similar out-of-sample (April–July April–August) predictive ability, even spatially filtering higher-resolution data cropland areas. The SIF product performed more poorly GPP NDVI. All forecasts are incorporating county fixed effects control cross-sectional differences between counties. NDVI-based allow significantly better predictions during drought conditions suggesting limited added value early warning impacts. benefits should continually evaluated as frequency quality measurements continue improve.
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ژورنال
عنوان ژورنال: Remote Sensing of Environment
سال: 2021
ISSN: ['0034-4257', '1879-0704']
DOI: https://doi.org/10.1016/j.rse.2021.112478