Temporal integration of remote-sensing land cover maps to identify crop rotation patterns in a semiarid region of Argentina

Abstract

Crop rotations are key agronomic tools to enhance farm productivity, preserve soil, and ensure provision of ecosystem services. Knowledge of the spatio-temporal distribution of crops over regions is essential to characterize rotations at field scale and estimate their impacts on several outcomes. Our objectives were to: (a) determine the diversity of cropping systems practiced in a semiarid region of central Argentina during an 8-yr period and (b) use the generated high-resolution crop rotation map jointly with estimates of soil erosion to evaluate the potential linkage between cropping sequences and water erosion intensity. Temporally aggregated seasonal land-cover maps were used to derive spatially explicit crop rotations during 2011–2018 across a 6,000 km2 semiarid agricultural region in Argentina. Soybean (Sy) [Glycine max (L.) Merr.] and maize (Mz) (Zea mays L.) defined the major crop rotations of the study area. Sorghum [Sorghum bicolor (L.) Moench] and peanut (Arachis hypogaea L.) occupied minor areas and thus were assimilated into the dominant summer cropping systems. Only seven sequences of summer crops, most of them including soybean and maize, accounted for >90% of the spatio-temporal variability. Soybean monoculture was the dominant cropping system (28.5%), followed by a 3-yr Sy–Sy–Mz rotation (23.9%), and other soybean-dominated rotation patterns. In winter, the prevailing land cover was stubble (96.6%). The generated high-resolution maps illustrate the low diversity of crops in the study area. Mapping the spatio-temporal distribution of land cover allowed for quantification of land transformations and the examination of linkages between soybean monocropping and erosion.