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We tested the predictive power of covariates generated from satellite imagery at different resolutions and extents (focal patch sizes, 10–500 m around sample points) on estimates of occupancy patterns of six small to medium sized mammal species/species groups.
The bottom right inset (indicated by the red frame in the main map) magnifies one camera-trap location (central red point) with its habitat survey points along the 250-m transect lines (white points).
Land cover extraction radii (extent, focal patches) are overlaid (black circles).
These highly sophisticated data are, however, expensive to obtain and difficult to analyse, and thus unavailable to many wildlife studies.
Thus, both in-situ and remote sensing derived covariates have their advantages and disadvantages, but only few studies compared their usefulness in wildlife distribution and habitat modelling.
circular areas of different radii surrounding the sampling points.
Not determining the appropriate spatial scale (either grain or extent) may lead to failure to detect species habitat associations.A comparison of different focal patch sizes including remote sensing data and an in-situ measure showed that patches with a 50-m radius had most support for the target species.Thus, high-resolution satellite imagery proved to be particularly useful in heterogeneous landscapes, and can be used as a surrogate for certain in-situ measures, reducing field effort in logistically challenging environments.The main map shows the Rapid Eye land cover classification.Black dots show camera-trap locations, each with their respective 500-m radius.ground cover, floristic or phenological information) and can serve for ground truthing remote sensing data.