The GFSADO30 Project is a NASA funded project (2023-2028) to provide highest-resolution global cropland data and their water use that contributes towards global food-and-water security in the twenty-first century. The GFSAD products are derived through multi-sensor remote sensing data (e.g., Landsat-series, Sentinel-series, MODIS, AVHRR), secondary data, and field-plot data and aims at documenting cropland dynamics from 2000 to 2030.
This module focuses on analyzing crop growth cycles to determine the number of harvestable crop cycles within a year. Using temporal and spatial data from HLSL30 and CDL, this process identifies crop intensity patterns.
This module maps different crop types within a region using neural network classification techniques applied to HLSL30 and CDL datasets.
Preprocessing steps for generating training and validation data.
This section provides additional tools and scripts.
- ASD File Parser: Parses data dumps from handleheld ASD Spectroradiometer.
- AppEEARS (WIP): Uses the NASA AppEEARS interface to pull data from LPDAAC.
- HLSL30: Harmonized Landsat and Sentinel-2 data at 30-meter resolution.
- CDL: Cropland Data Layer providing annual crop-specific land cover.
Contributions are welcome! Please create a pull request or open an issue if you have suggestions or improvements.
This project is licensed under the MIT License.