The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1533–1537, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1533-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1533–1537, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1533-2020

  22 Aug 2020

22 Aug 2020

EXPLOITATION OF SENTINEL-2 IMAGES FOR LONG-TERM VEGETATION MONITORING AT A FORMER ORE PROCESSING SITE

S. Fabre1, A. Elger2, and T. Riviere1 S. Fabre et al.
  • 1ONERA DOTA BP74025 2 av. Edouard Belin, FR-31055 TOULOUSE CEDEX 4, France
  • 2EcoLab, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France

Keywords: Vegetation survey, Change detection, Mining site, Phytostabilization, Heavy metal, Multispectral, Multitemporal, Sentinel-2 satellite

Abstract. Excess metals in the soil or in plant tissues tend to have negative effects on plant health, growth, and biomass accumulation. The search for stressed or unusual growth patterns in cover vegetation has been enhanced by the use of vegetation index in the context of excessive exposure to heavy metals in the soil. This study aims to improve the monitoring of phyto-stabilized and natural vegetation of an ore processing site for several years after its closure by using multiple Sentinel-2 images. The time series is made up of 13 images, one image per season for four years. NDVI (Normalized Difference Vegetation Index), the most widely known and used vegetation index in the scientific literature, is used in combination with other spectral indexes identifying built-up areas and bare soils in order to enhance vegetation. A change detection technique based on absolute difference of vegetation maps is applied to detect abrupt changes related to meteorological conditions and significant environmental changes.