30 Years of simultaneous crop & land cover land use maps for Middle Rio Grande from 1994 to 2024.

ABSTRACT: This study introduces the crop and land cover land use (CLCLU) dataset, a 30 m resolution product providing annual maps of CLCLU across the transnational Middle Rio Grande (MRG) region, spanning both the U.S. and Mexico from 1994 to 2024. The model was trained using the Cropland Data Layer (CDL) on the US side. Dual-month (July and December) Landsat composites and a semantic segmentation model, MANet with ResNeXt-101 encoder, under four strategies were used to address sensor and temporal variability. This model architecture was chosen for its intrinsic ability to capture detailed spatial patterns and contextual dependencies through its attention-based design and ResNeXt-101 encoder, which demonstrated strong performance, particularly in generalizing across data-scarce regions in Mexico. Th

SUBMITTER: Ebrahimi S 

PROVIDER: S-EPMC12370968 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature