Mapping Annual Crop Residue Cover Across Global Mollisol Regions at 10-m Resolution (2019–2024)

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Abstract. Mollisol regions are among the world’s major grain-producing areas, yet intensive cultivation and residue removal threaten the long-term sustainability of these fertile soils. Retaining crop residues on the soil surface is an important conservation practice that can reduce erosion, conserve soil moisture, and sustain carbon inputs. However, spatially explicit, multi-year observations remain scarce, limiting consistent assessment of management patterns and their environmental implications. Here we present CrRUC-M (Crop ResidUe Cover across global Mollisol regions), the first annual, 10-m wall-to-wall dataset covering 2019–2024 and derived from Sentinel-2 imagery. We developed a knowledge-guided framework for mapping crop residue cover across croplands. First, annual non-growing-season Sentinel-2 composites were generated to reduce environmental interference. Second, phenological and spectral constraints were applied to screen residue-consistent candidate pixels. Third, final residue cover was mapped by applying the Multi-band Crop Residue Cover Spectral Index (MCRCSI) and region- and year-specific Otsu thresholds to these candidate pixels. The resulting maps were validated using reference samples derived from windshield surveys and visual interpretation, achieving an overall accuracy of 0.83 and F1-score of 0.81. Region-level assessments, comparisons with regional datasets and statistics, and transfer tests using Landsat archives collectively demonstrated that the resulting maps reliably captured fine-scale spatial patterns and interannual variability. Spatiotemporal analyses revealed a pronounced core-periphery gradient in residue-cover frequency, with persistent high-frequency clusters in intensively cultivated areas. Corn was the dominant residue source across Mollisol regions, whereas secondary crop contributions varied with regional cropping systems. CrRUC-M provides the first multi-year crop residue cover benchmark for global Mollisol regions. It can enrich representations of agricultural management practices in Earth system models and provide insights into the effects of crop residue cover on soil carbon dynamics and climate change. The CrRUC-M dataset is publicly available at https://doi.org/10.5281/zenodo.18773303 (Cui et al., 2025).

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