REFINEMENT OF CROPLAND DATA LAYER USING MACHINE LEARNING

8 citations as recorded by crossref.

1. Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold K. Tran et al. https://doi.org/10.3390/rs14225721
2. Integrating image filters and confidence thresholds to improve cropland data layer for deep learning–based cropland segmentation R. Maleki et al. https://doi.org/10.1080/22797254.2026.2631928
3. Rapid in-season mapping of corn and soybeans using machine-learned trusted pixels from Cropland Data Layer C. Zhang et al. https://doi.org/10.1016/j.jag.2021.102374
4. Remote Sensing of Urban Poverty and Gentrification L. Lin et al. https://doi.org/10.3390/rs13204022
5. Preserving local biodiversity through crop diversification E. Strobl https://doi.org/10.1111/ajae.12265
6. HarvestGRID: high-resolution harvested crop areas of the United States from 1981 to 2019 G. Lamsal & L. Marston https://doi.org/10.1088/2976-601X/ad96bf
7. Refinement of Cropland Data Layer with Effective Confidence Layer Interval and Image Filtering R. Maleki et al. https://doi.org/10.3390/agriculture14081285
8. AgKit4EE: A toolkit for agricultural land use modeling of the conterminous United States based on Google Earth Engine C. Zhang et al. https://doi.org/10.1016/j.envsoft.2020.104694