This repository contains the implementation of Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA) for mapping fallow lands in Ukraine using satellite imagery data.
The FANTA algorithm was developed by Wallace et al. (2017) to distinguish between planted and fallowed croplands using temporal and spatial anomalies in vegetation indices. This implementation adapts the FANTA approach for high-resolution NDVI data in Ukraine, focusing on detecting fallow lands during 2020–2023.
- Q1 & Q2: TANDVI and TANDVIrange-based fallow detection.
- Q3 & Q4: NDVI and NDVI Range-based fallow detection.
- Final Output: Aggregation of multiple fallow detection criteria to produce a final fallow land map.
- Satellite Imagery: High-resolution NDVI data for Ukraine (2013–2023).
- Boundary Data: Administrative boundaries for Ukraine from FAO GAUL dataset.
Wallace, C. S., Thenkabail, P., Rodriguez, J. R., & Brown, M. K. (2017).
Fallow-land Algorithm based on Neighborhood and Temporal Anomalies (FANTA)
to map planted versus fallowed croplands using MODIS data to assist in
drought studies leading to water and food security assessments.
GIScience & Remote Sensing, 54(2), 258-282.
https://doi.org/10.1080/15481603.2017.1290913