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Target detection of mine-related flooded areas using AISA-eagle data

Millán, Virginia E.García LU ; Pakzad, Kian ; Faude, Ulrike ; Teuwsen, Sebastian and Müterthies, Andreas (2017) 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014 2014-June.
Abstract

The present research is developed in the frame of the R&D project GMES4Mining, which aims to support particular tasks within the different phases of a mining life cycle [1]. During the exploitation and after the closure of the mine, environmental and civil impacts may happen, due to changes in the compacting properties of the soil related to mining activities. In this paper, we focus in the emergence of flooded areas, due to a subsidence of the ground surface. Above-ground vegetation is affected by changes in groundwater's dynamics; at first trees suffer defoliation and senescence, and after some time, they die. Several methods have been tested, to detect changes in spectral response of forests in a mine area, which are related to... (More)

The present research is developed in the frame of the R&D project GMES4Mining, which aims to support particular tasks within the different phases of a mining life cycle [1]. During the exploitation and after the closure of the mine, environmental and civil impacts may happen, due to changes in the compacting properties of the soil related to mining activities. In this paper, we focus in the emergence of flooded areas, due to a subsidence of the ground surface. Above-ground vegetation is affected by changes in groundwater's dynamics; at first trees suffer defoliation and senescence, and after some time, they die. Several methods have been tested, to detect changes in spectral response of forests in a mine area, which are related to imminent flooding. ENVI's Target Detection Tool has been used to estimate the reflectance proportion at pixel level of four targets of interest in AISA-Eagle's data, which are present in flooded areas: water, dead trunks, senescent trees and green stands within water. Five target detection's methods have been tested: Constrained Energy Minimization (CEM), Adaptative Coherence Estimator (ACE), Spectral Angle Mapper (SAM), Target-Constrained Interference-Minimized Filter (TCIMF) and Mixture Tuned Matched Filtering (MTMF).

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
keywords
Flooding, Hyperspectral, Mining, Risk Assessment, Vegetation
host publication
2014 6th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, WHISPERS 2014 - Evolution in Remote Sensing, WHISPERS 2014
volume
2014-June
article number
8077548
publisher
IEEE Computer Society
conference name
6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2014
conference location
Lausanne, Switzerland
conference dates
2014-06-24 - 2014-06-27
external identifiers
  • scopus:85038595671
ISBN
9781467390125
DOI
10.1109/WHISPERS.2014.8077548
language
English
LU publication?
no
id
832c2314-1045-4cb5-961d-20d9dc0dddb9
date added to LUP
2019-06-12 13:21:56
date last changed
2020-09-23 07:45:33
@inproceedings{832c2314-1045-4cb5-961d-20d9dc0dddb9,
  abstract     = {<p>The present research is developed in the frame of the R&amp;D project GMES4Mining, which aims to support particular tasks within the different phases of a mining life cycle [1]. During the exploitation and after the closure of the mine, environmental and civil impacts may happen, due to changes in the compacting properties of the soil related to mining activities. In this paper, we focus in the emergence of flooded areas, due to a subsidence of the ground surface. Above-ground vegetation is affected by changes in groundwater's dynamics; at first trees suffer defoliation and senescence, and after some time, they die. Several methods have been tested, to detect changes in spectral response of forests in a mine area, which are related to imminent flooding. ENVI's Target Detection Tool has been used to estimate the reflectance proportion at pixel level of four targets of interest in AISA-Eagle's data, which are present in flooded areas: water, dead trunks, senescent trees and green stands within water. Five target detection's methods have been tested: Constrained Energy Minimization (CEM), Adaptative Coherence Estimator (ACE), Spectral Angle Mapper (SAM), Target-Constrained Interference-Minimized Filter (TCIMF) and Mixture Tuned Matched Filtering (MTMF).</p>},
  author       = {Millán, Virginia E.García and Pakzad, Kian and Faude, Ulrike and Teuwsen, Sebastian and Müterthies, Andreas},
  booktitle    = {2014 6th Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, WHISPERS 2014},
  isbn         = {9781467390125},
  language     = {eng},
  month        = {10},
  publisher    = {IEEE Computer Society},
  title        = {Target detection of mine-related flooded areas using AISA-eagle data},
  url          = {http://dx.doi.org/10.1109/WHISPERS.2014.8077548},
  doi          = {10.1109/WHISPERS.2014.8077548},
  volume       = {2014-June},
  year         = {2017},
}