Abstract
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.
Highlights
Mining activities are an important source of soil heavy metal pollution
Time series of vegetation index data can be obtained from satellite Sentinel-2 images, with spatial resolution of 10 and 20 m according to the spectral domains and high temporal coverage (Frampton, 2013)
Zones 1 and 5 have permanent bare soil pixels with no vegetation cover regardless of the year and the season (Figure 2, Figure 3)
Summary
Mining activities are an important source of soil heavy metal pollution. Vegetation mapping and monitoring near mine sites following the end of operations could allow one to provide information on the results of rehabilitation or to detect and control residual contaminants through the vegetation health (Davids, 2018). The Normalized Difference Vegetation Index (NDVI) (Rouse, 1973) is often used to characterize canopy growth or vigour and related to LAI (Leaf Area Index) (Xue, 2017) This index, based on the absorption of light by vegetation in the red band and its reflectance in the NIR (Near InfraRed) band, is especially suitable for monitoring low to moderate density vegetation. The objective of this study is to survey vegetation cover changes many years after the closure and the revegetation of an ore processing site by using Sentinel-2 time series. A processing chain with three modules has been set up ( Figure 1) These modules are: a spectral index database to provide index maps representing built-up areas, bare soils and vegetation, a map combination module in order to provide the vegetation cover maps and a change detection module to compare vegetation cover maps and localize changes. The processing chain’s inputs are spectral reflectance images and it produces change detection maps
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