4.7 Article

Towards the evaluation of regional ecosystem integrity using NDVI, brightness temperature and surface heterogeneity

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 796, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2021.148994

Keywords

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

Funding

  1. DBU (Deutsche Bundesstiftung Umwelt) MOE scholarship
  2. GAUK (Charles University Grant Agency) [546517]
  3. SVV (Specific University Research) [VS 260 471]

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Maintaining ecological integrity is a global strategic goal, yet there is no consensus on a widely usable methodology to assess it. This study proposes a comprehensive approach to quantify regional ecosystem integrity based on FAIR data obtained through satellite remote sensing. The approach focuses on three central variables and introduces a Regional Index of Ecological Integrity to represent the integrity of study areas. Results show agriculture as a significant factor reducing regional integrity and conservation areas ranking highest in integrity.
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, dimatic) to provide deeper understanding of landscape ecosystem integrity. (C) 2021 Elsevier B.V. All rights reserved.

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