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Articles | Volume XLI-B8
https://doi.org/10.5194/isprs-archives-XLI-B8-151-2016
https://doi.org/10.5194/isprs-archives-XLI-B8-151-2016
22 Jun 2016
 | 22 Jun 2016

ENVIRONMENTAL IMPACT ASSESSMENT OF ROSIA JIU OPENCAST AREA USING AN INTEGRATED SAR ANALYSIS

V. D. Poenaru, I. F. Dana Negula, A. Badea, and R. Cuculici

Keywords: Environment, Rosia Jiu mining area, DInSAR analysis, multi-temporal SAR data, TerraSAR-X Staring Spotlight Mode

Abstract. The satellite data provide a new perspective to analyse and interpret environmental impact assessment as function of topography and vegetation. The main goal of this paper is to investigate the new Staring Spotlight TerraSAR-X mode capabilities to monitor land degradation in Rosia Jiu opencast area taking into account the mining engineering standards and specifications. The second goal is to relate mining activities with spatio-temporal dynamics of land degradation by using differential Synthetic Aperture Radar interferometry (DInSAR). The experimental analysis was carried out on data acquired in the LAN_2277 scientific proposal framework during 2014-2015 period. A set of 25 very height resolution SAR data gathered in the VV polarisation mode with a resolution of 0.45 m x 0.16m and an incidence angle of 37° have been used in this study. Preliminary results showed that altered terrain topography with steep slopes and deep pits has led to the layover of radar signal. Initially, ambiguous results have been obtained due to the highly dynamic character of subsidence induced by activities which imply mass mining methods. By increasing the SAR data number, the land degradation assessment has been improved. Most of the interferometric pairs have low coherence therefore the product coherence threshold was set to 0.3. A coherent and non-coherent analysis is performed to delineate land cover changes and complement the deformation model. Thus, the environmental impact of mining activities is better studied. Moreover, the monitoring of changes in pit depths, heights of stock-piles and waste dumps and levels of tailing dumps provide additional information about production data.