Uncovering Shifting Cultivation Dynamics in the Amazon: the Synergy Between Field Dataand Remote Sensing Image Time Series Classificationme Series Classification
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This study evaluates the Compound Maximum a posteriori (CMAP) classification of Landsat imagery to reconstruct the land-use history of shifting cultivation areas across the Amazon. We estimated agricultural cycles and secondary forest age near the Juruá, Tefé, and Tapajós rivers using annual Landsat composites (1984–2024) classified with CMAP and a generalized training strategy. Comparison with local landowner interviews showed that CMAP effectively estimates these parameters (55% within ±1 for cycles and 93% within ±3 years for age). These results demonstrate CMAP’s potential for land-use history reconstruction, with field data integration likely improving the detailing of information.
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