Estimating Yield from NDVI, Weather Data, and Soil Water Depletion for Sugar Beet and Potato in Northern Belgium
Crop-yield models based on vegetation indices such as the normalized difference vegetation index (NDVI) have been developed to monitor crop yield at higher spatial and temporal resolutions compared to agricultural statistical data. We evaluated the model performance of NDVI-based random forest models for sugar beet and potato farm yields in northern Belgium during 2016–2018. We also evaluated whether weather variables and root-zone soil water depletion during the growing season improved the model performance. The NDVI integral did not explain early and late potato yield variability and only pa... Mehr ...
Verfasser: | |
---|---|
Dokumenttyp: | Text |
Erscheinungsdatum: | 2022 |
Verlag/Hrsg.: |
Multidisciplinary Digital Publishing Institute
|
Schlagwörter: | root-zone soil water depletion / AquaCrop-OSPy / sugar beet / potato / crop yield / NDVI / Belgium / weather impact / random forest |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26590468 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.3390/w14081188 |