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Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

Earth and Life Institute—Environment, Université catholique de Louvain, Croix du Sud 2, Louvain-la-Neuve 1348, Belgium
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Clement Atzberger and Prasad S. Thenkabail
Remote Sens. 2016, 8(6), 488;
Received: 17 March 2016 / Revised: 28 May 2016 / Accepted: 2 June 2016 / Published: 9 June 2016
PDF [1363 KB, uploaded 9 June 2016]


Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications. View Full-Text
Keywords: Sentinel-2; Landsat-8; SPOT-5; sub-pixel detection; spatial resolution; spectral resolution; point spread function Sentinel-2; Landsat-8; SPOT-5; sub-pixel detection; spatial resolution; spectral resolution; point spread function

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Radoux, J.; Chomé, G.; Jacques, D.C.; Waldner, F.; Bellemans, N.; Matton, N.; Lamarche, C.; D’Andrimont, R.; Defourny, P. Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection. Remote Sens. 2016, 8, 488.

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