Mapping oil palm expansion in the Eastern Amazon using optical and radar imagery

Palm oil, the world’s most widely consumed vegetable oil, plays a pivotal role in the food, biodiesel, and pharmaceutical industries. However, its rapid expansion in tropical regions has led to critical environmental challenges, including deforestation and biodiversity loss. This study maps oil palm plantations in the Eastern Amazon, Brazil’s largest producer, for 2014, 2017, and 2020, employing machine learning algorithms such as K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Decision Trees (DT), Support Vector Machines (SVM), and Random Forests (RF). This study integrate Landsat-8 optical spectral bands (blue, green, red, and near-infrared) with Sentinel-1 radar backscatter values (VV and VH polarizations) to map the expansion of oil palm in the Brazilian Amazon, a combination that has not been previously implemented in this region. Vegetation indices, including NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), SAVI (Soil-Adjusted Vegetation Index), DVI (Difference Vegetation Index), RVI (Ratio Vegetation Index), GI (Green Index), and texture indices derived from the gray-level co-occurrence matrix (GLCM), such as contrast, angular second moment (ASM), correlation, and entropy, were used to improve classification accuracy. A linear spectral mixing model was also applied to distinguish the spectral signatures, with the resulting end members subsequently incorporated. The RF achieved the highest classification accuracy, with overall accuracies of 94.53%, 94.28%, and 95.53% for 2014, 2017, and 2020, respectively. A land use and land cover (LULC) transition analysis revealed a substantial expansion of 72.16%, with the area growing from 1,074 km 2 in 2014 to 1,849 km 2 in 2020. Notably, 156.88 km 2 (20.24%) of this expansion occurred directly at the expense of vegetation cover, underscoring areas of significant environmental concern. This study offers valuable insights to guide the development of public and market-driven policies aimed at promoting sustainable and environmentally responsible oil palm expansion. • First to map oil palm expansion in the Eastern Amazon using radar and optical data. • Random Forest algorithm achieved an approximate accuracy of 95%. • Oil palm area in the Eastern Amazon expanded by 72.16% between 2014 and 2020. • 20.24% of oil palm expansion in the Eastern Amazon replaced natural vegetation. • Supports policies to monitor and mitigate oil palm’s environmental impact.