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Article Dans Une Revue International Journal of Applied Earth Observation and Geoinformation Année : 2022

Spectral diversity allows remote detection of the rehabilitation status in an Amazonian iron mining complex

Résumé

Mineland rehabilitation is intended to reduce the overall impacts of mining on biodiversity and ecosystem services and requires periodic monitoring to guarantee institutional tractability and to refine rehabilitation practices. As time- and money-consuming field surveys challenge this monitoring, the aim of this study was to develop a remote sensing framework to assess the environmental quality of minelands undergoing rehabilitation based on free and open-access multispectral Sentinel-2 images. For this purpose, we linked spectral diversity, i.e., measures of spectral variation among neighboring pixels, to the field-surveyed environmental quality of a rehabilitation chronosequence covering five waste piles in the Carajas National Forest, Eastern Amazon. Field data were separated into a training data set from 2017 (54 plots) and a testing data set from 2019 (66 plots). Based on the training data set, we optimized the computational parameters of spectral diversity (separation of vegetated from nonvegetated pixels by the normalized difference vegetation index [NDVI], size of the buffer zones, number of clusters representing distinct spectral species and applied diversity metrics), maximizing the accuracy of the remote monitoring approach. Then, we validated the procedure with the testing data set and compared the number of areas undergoing rehabilitation and their quality from 2017 and 2019. The overall accuracy of our methodology was 83%, and user and producer accuracies exceeded 60% for all rehabilitation classes, enabling the remote sensing of successional advancement of rehabilitating minelands. Despite punctual losses in spectral diversity, we detected comprehensive gains in spectral diversity within the target structures. This is due to an increase in the overall rehabilitation area from 282.39 to 364.54 ha, but enhancements in the spectral diversity of already vegetated areas indicate the successional advancement of these areas with time, reducing the overall impact of mining activities on biodiversity and ecosystem services. We conclude that the remote sensing framework presented here is promising for mapping environmental quality in minelands undergoing rehabilitation, and we encourage its integration in current monitoring protocols to reduce costs and increase the transparency of a company's rehabilitation activities, as freely available satellite images and opensource software are applied.
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Dates et versions

hal-03541196 , version 1 (24-01-2022)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Markus Gastauer, Wilson R Nascimento, Cecílio Frois Caldeira, Silvio Junio Ramos, Pedro Walfir M. Souza-Filho, et al.. Spectral diversity allows remote detection of the rehabilitation status in an Amazonian iron mining complex. International Journal of Applied Earth Observation and Geoinformation, 2022, 106, pp.102653. ⟨10.1016/j.jag.2021.102653⟩. ⟨hal-03541196⟩
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