Maintaining ecological integrity is globally acknowledged as a strategic goal, yet there is no consensus on a practical and widely usable methodology to assess it. This study proposes a comprehensive approach to quantify regional ecosystem integrity based on FAIR data, obtained using satellite remote sensing and image analysis. Three variables are central to this approach: normalized difference vegetation index (NDVI), at-satellite brightness temperature (BT) and vegetation surface heterogeneity (HG), corresponding to ecosystem integrity indicators exergy capture, biotic water flows and abiotic heterogeneity. The indicators are assessed across the vegetation period and a representative Regional Index of Ecological Integrity (RIEI) is proposed to express the integrity of two case study areas and representative land use types. The proposed approach proved powerful in representing the anthropogenic and autopoietic gradient within study regions in high detail. Arable lands and urban areas ranked lowest, while dense forests and wetlands highest, agriculture being the most significant factor reducing regional integrity. Areas with conservation significance ranked either having the highest integrity, when dense vegetation was present, and mediocre or even low in case of e.g., sand dunes, marches and rock formations. Limitations of the method comprise: insufficient representation of biodiversity, sensitivity to cloud cover and demanding in-situ validation. The approach can be scaled from global to local level, adapted to various remote sensing techniques and complemented by a diversity of data (e.g., ecosystem services, geomorphological, climatic) to provide deeper understanding of landscape ecosystem integrity.

Keywords: Decision-support tools; Ecological indicators; Ecosystem integrity; Remote sensing; Spatial analysis.

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