Systematic Review of Satellite-Based Earth Observation Applications for Wildlife Ecology Research in Terrestrial Polar and Mountain Regions

The extreme conditions of polar and mountain regions foster uniquely adapted wildlife. Given that climate shifts are more extreme in those regions, monitoring animal species is essential for effective conservation measures. Earth observation data offer considerable advantages in areas that are difficult to reach using traditional ground-based methods. This systematic review, based on 145 SCI-journal publications between 2000 and 2024, examines how Earth observation is used in wildlife ecology research in these regions. We give an extensive overview of the Earth observation sensors used, spatial and temporal resolution of studies, studied animal species, methods used, amount of aerial imagery linked to satellite-based Earth observation, and research objectives. Bird (52 studies) and ungulate (38 studies) species are primarily investigated in relation to animal monitoring, distribution and foraging behavior. Products of Landsat (63 studies) and MODIS (52 studies) are used in most reviewed studies, but the potential of freely available, higher spatial and temporal resolution data like Sentinel-2 (seven studies), as well as AI methods are not yet fully utilized. Linking Earth observation data in polar and mountain regions to wildlife ecology research should be facilitated by encouraging interdisciplinary working groups. Two major crises can be tackled at once, climate change and biodiversity loss.

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Publication Details

Journal
Remote Sensing
Published
2025-08-11
DOI
https://doi.org/10.3390/rs17162780
Citations
2
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
3.68

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article

Systematic Review of Satellite-Based Earth Observation Applications for Wildlife Ecology Research in Terrestrial Polar and Mountain Regions

Samuel Kounev, A.J. Dietz, Helena Wehner, Claudia Kuenzer
2 citations
Remote Sensing
Species Distribution and Climate Change
3.68
article

Systematic Review of Satellite-Based Earth Observation Applications for Wildlife Ecology Research in Terrestrial Polar and Mountain Regions

Samuel Kounev, A.J. Dietz, Helena Wehner, Claudia Kuenzer
article en
2 citations

Abstract

The extreme conditions of polar and mountain regions foster uniquely adapted wildlife. Given that climate shifts are more extreme in those regions, monitoring animal species is essential for effective conservation measures. Earth observation data offer considerable advantages in areas that are difficult to reach using traditional ground-based methods. This systematic review, based on 145 SCI-journal publications between 2000 and 2024, examines how Earth observation is used in wildlife ecology research in these regions. We give an extensive overview of the Earth observation sensors used, spatial and temporal resolution of studies, studied animal species, methods used, amount of aerial imagery linked to satellite-based Earth observation, and research objectives. Bird (52 studies) and ungulate (38 studies) species are primarily investigated in relation to animal monitoring, distribution and foraging behavior. Products of Landsat (63 studies) and MODIS (52 studies) are used in most reviewed studies, but the potential of freely available, higher spatial and temporal resolution data like Sentinel-2 (seven studies), as well as AI methods are not yet fully utilized. Linking Earth observation data in polar and mountain regions to wildlife ecology research should be facilitated by encouraging interdisciplinary working groups. Two major crises can be tackled at once, climate change and biodiversity loss.

Remote SensingVol. 17(16)
University of Würzburg (DE), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 7%
Species Distribution and Climate Change
3.68
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Systematic Review of Satellite-Based Earth Observation Applications for Wildlife Ecology Research in Terrestrial Polar and Mountain Regions — Samuel Kounev, A.J. Dietz, et al. · Remote Sensing (2025) | TGRS Research Map | TGRS