United States multi-sector land use and land cover base maps to support human and Earth system models

Jay Oliver & Ryan A. McManamay

Acknowledgment of support from the U.S. Department of Energy, Office of Science, MultiSector Dynamics, Earth and Environmental System Modeling (MSD), and Regional & Global Model Analysis (RGMA) program areas.

DOI: https://doi.org/10.1038/s41597-025-04713-6

Abstract

Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Caption: Flow-chart showing empirical, high-resolution land maps (including National Land Cover Dataset (NLCD) and Crop Data Layers (CDL) layers) on the far left and the processing steps taken to develop complete inventory of MSD layers (far right) compatible with GCAM, CLM, and LUH2. Some of the NLCD layers were directly mapped to the final MSD land types (Non-manipulated product). CDL Crop layers were first extracted from the NLCD cultivated crops class and were overlayed with an irrigated land mask to differentiate between irrigated and rainfed crops. The PADUS3 dataset was used to differentiate between managed and unmanaged land. Lastly, a climate and ecoregion envelope was developed to differentiate between temperate tropical and boreal landcover.

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