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Data · dataset · 2026

LP-QLC10: 25-year quarterly land change mapping in China’s Loess Plateau reveals long-term and substantial soil erosion mitigation

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The quarterly land cover maps for the Loess Plateau (LP-QLC10) provide continuous spatial coverage from 2000 to 2024 over an area of approximately 648,700 km2.

Description

The dataset is produced at a three-month interval, yielding a total of 100 temporal phases. Using the proposed CCTS framework, we processed more than 10 terabytes of multisource satellite imagery from Landsat and Sentinel missions.

The spatial resolution is 30 m for years prior to 2016 and 10 m from 2016 onward, consistent with the native resolutions of the contributing sensors.Following the standards issued by the Ministry of Ecology and Environment of China, the LP-QLC10 land cover dataset was further integrated with environmental factors to estimate the 25-year quarter-level soil erosion.User guide:Both the land cover maps and the soil erosion maps are provided in GeoTIFF format.

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Each file is named using the format Y_Q.tif, where Y denotes the year and Q denotes the quarter. The LP-QLC10 dataset contains eight land-cover categories, and the corresponding color scheme is provided in the file Land-cover colormap.clr:1: Forest2: Shrubland3: Grassland4: Cropland5: Built-up6: Bare land7: Water8: WetlandThe soil erosion maps are quantified in t/(hm2·q), where q represents the quarter. If necessary, annual soil erosion in t/(hm2·a) can be obtained by summing the four quarterly erosion values within each year, as each quarterly estimate represents cumulative erosion over that period.If you use this dataset in your research, please cite: Cheng, M., Li, Z., Li, L., He, W., Zhang, L., and Zhang, H.: 25-year, quarterly land change maps of China's Loess Plateau reveal long-term and substantial water-induced soil erosion mitigation, Earth Syst.

Sci. Data, 18, 3303–3340, doi.org/10.5194/essd-18-3303-2026, 2026. If you have any questions or technical issues, contact us at chengmofan@whu.edu.cn (Mofan Cheng)

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ScienceDB10.57760/sciencedb.336568 d agoJSON v1
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