Use of GLOBE observer citizen science data to validate continental-scale canopy height maps derived from ICESat-2 and GEDI - Lu, Mei-Kuei; Popescu, Sorin C.; Campbell, Brian A. (Frontiers in Environmental Science, 2025)
Citizen science plays a crucial role in enhancing the spatial and temporal resolutions of environmental observations. The Global Learning and Observations to Benefit the Environment (GLOBE) Observer application is a mobile extension of the GLOBE Program that is empowering the public to collect environmental data in support of both scientific research and educational outreach. In this study, we leverage citizen science data from the GLOBE Observer program to evaluate and validate three canopy height models: the ice, cloud, and land elevation satellite-2 (ICESat-2) product, a global ecosystem dynamics investigation (GEDI)-Landsat-derived global map (GL), and a GEDI-Sentinel-2 fusion map (GS-2). Tree height measurements obtained with GLOBE were filtered for forested areas using the Landscape Fire and Resource Management Planning Tools (LANDFIRE) existing vegetation cover data and analyzed across multiple ecozones within the contiguous United States; then, manual comparisons were performed with airborne lidar data from selected sites. Our findings indicate that although GLOBE data provide extensive temporal and spatial coverage, these exhibit low general agreement with airborne lidar reference heights (R2 = 0.14) owing to geolocation inaccuracies and measurement inconsistencies inherent in citizen-collected data. Validations performed with spaceborne lidar-derived canopy height maps (ICESat-2, GL, and GS-2) showed generally low correlations (R2 = 0.08–0.17) that could be improved (up to R2 = 0.22) by filtering for greater location accuracy (0–25 m), even though challenges persist. These results underscore both the potential and limitations of using citizen science data for validating spaceborne lidar-derived canopy height maps while highlighting the need for enhanced data collection protocols to improve geolocation accuracies for future ecological monitoring efforts.