Abstract

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

Highlights

  • Land cover classifications based on the two satellites, significantly differed in area of the six land cover classes (MANOVA, F6, 857 = 5.53, p,0.001), with significant differences in cleared, water (F1, 862 = 5.04, p,0.001), and wetland (F1, 862 = 6.21, p,0.001) classes

  • When we included only forest patches $0.5 ha, significant differences existed between IKONOS and Landsat in three of the six patch-level metrics: shape index (t = 8.180, df = 464, p,0.001), perimeter-area index (t = 15.71, df = 464, p,0.001), and mean distance from patch centroid to all other patch centroids (t = 2.90, df = 464, p = 0.004)

  • Many types of satellite imagery are available to conservation practitioners, but based on our literature review, most current conservation research does not take full advantage of either high-resolution or low-resolution imagery

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Summary

Introduction

Since the 1972 launch of the Earth Resources Technology Satellite (renamed Landsat 1), remotely sensed imagery has been increasingly used to monitor Earth’s ecosystems [1,2,3,4,5] by quantifying land cover change [6], deforestation [7], carbon stocks and emissions [8], habitat degradation and disease [9], [10], species diversity [11], [12], invasive species [13], habitat suitability [14], and species populations [15]. Satellite imagery employed in conservation research ranges from 1000 m to ,1 m in resolution [4], [5]. Landsat imagery (30 m multispectral resolution) has been integral in scientific research since 1972 [19], in mapping and assessments of land cover change [20], and it is currently available at no cost [21]. One exception is the free, high-resolution imagery provided via Google Earth that is increasingly being used in scientific research [22], [23], can aid in the selection of field sampling locations [10], and can be used as training samples for classification [24]. Imagery analysis based on Google Earth images, is limited as the different satellite bands are not available for manipulation by the user

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