Integrating Unoccupied Aerial Systems and Satellite Data to Map the Patchiness of Bare Ground at a Landscape Scale

Integrating fine-scale measurements with broad-scale monitoring presents a persistent challenge in rangeland ecology, particularly when scaling detailed Unoccupied Aerial System (UAS) observations to satellite-based landscape assessments. This challenge is especially critical as rangelands face increasing climate variability, requiring reliable methods to detect and monitor ecological changes. We investigated how the Largest Patch Index (LPI) of bare ground patches, derived from 3-dimensional UAS observations, can be scaled to landscape levels for mapping bare ground patchiness across a 100 km² semi-arid rangeland in southern Arizona. Our findings reveal three key advances in landscape monitoring. First, LPI effectively captured vegetation responses to extreme climate events during 2019–2023, showing clear sensitivity to both severe drought (SPEI − 2.47) and exceptional wet periods (SPEI + 1.95). Second, LPI values were consistently 30–60% higher in lower elevations, validating the ability to detect known ecological gradients. Third, and most notably, that LPI is positively scale dependent between the 3-m and 30-m grid sizes, and that the magnitude of that difference varies with the density of data from the satellite sensors. This previously unrecognized role of data density challenges fundamental assumptions about scale effects in landscape pattern analysis. Our approach demonstrates a practical solution for integrating UAS and satellite observations, providing a new approach for supporting the detection and monitoring of ecological changes across landscapes, a critical need given increasing climate uncertainty.