Methodology for assessing the accuracy of long-term, annual land cover monitoring at national scale: Experiences from the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative

Annual land cover monitoring using medium-resolution satellite imagery represents a transition from periodic mapping campaigns to continuous observation systems. This transition introduces accuracy assessment challenges not encountered in one-time mapping efforts, particularly when the initial monitoring period is extended forward in time. These challenges are not addressed in existing guidance, which remains largely framed around the evaluation of maps of a single date or maps showing changes between two dates. We present a set of methodological adaptations to adjust to this evolving paradigm, using as a case study the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment, and Projection (LCMAP) initiative, which generated annual land cover and land cover change products across the historical Landsat archive. Assessing the accuracy of these products was an essential component of LCMAP and resulted in an extensive reference sample dataset that may be used for accuracy estimation, area estimation, or support in the development of new algorithms or models. We review the LCMAP methodology and highlight challenges encountered and lessons learned that are transferable to other long-term, temporally dense monitoring programs. This framework demonstrates that statistically rigorous assessment can scale to operational annual land cover production, while the experiences of the project clarify where existing good practice guidance should be extended to support the needs of ongoing, continuous land cover monitoring.

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Publication Details

Journal
Remote Sensing of Environment
Published
2026-10-09
DOI
https://doi.org/10.1016/j.rse.2026.115705
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Methodology for assessing the accuracy of long-term, annual land cover monitoring at national scale: Experiences from the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative

Josephine A. Horton, Danika Wellington, Stephen V. Stehman, Bruce W. Pengra et al.
Remote Sensing of Environment
Remote Sensing in Agriculture
article

Methodology for assessing the accuracy of long-term, annual land cover monitoring at national scale: Experiences from the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative

Josephine A. Horton, Danika Wellington, Stephen V. Stehman, Bruce W. Pengra, Christopher Barber
article en

Abstract

Annual land cover monitoring using medium-resolution satellite imagery represents a transition from periodic mapping campaigns to continuous observation systems. This transition introduces accuracy assessment challenges not encountered in one-time mapping efforts, particularly when the initial monitoring period is extended forward in time. These challenges are not addressed in existing guidance, which remains largely framed around the evaluation of maps of a single date or maps showing changes between two dates. We present a set of methodological adaptations to adjust to this evolving paradigm, using as a case study the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment, and Projection (LCMAP) initiative, which generated annual land cover and land cover change products across the historical Landsat archive. Assessing the accuracy of these products was an essential component of LCMAP and resulted in an extensive reference sample dataset that may be used for accuracy estimation, area estimation, or support in the development of new algorithms or models. We review the LCMAP methodology and highlight challenges encountered and lessons learned that are transferable to other long-term, temporally dense monitoring programs. This framework demonstrates that statistically rigorous assessment can scale to operational annual land cover production, while the experiences of the project clarify where existing good practice guidance should be extended to support the needs of ongoing, continuous land cover monitoring.

Remote Sensing of EnvironmentVol. 348
United States Geological Survey (US), SUNY College of Environmental Science and Forestry (US), Earth Resources Observation and Science Center
U.S. Geological Survey
Life on land, Climate action
Openalex Percentile: Top 16%
Remote Sensing in Agriculture
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