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Please use this identifier to cite or link to this item: http://hdl.handle.net/10386/557

Title: Satellite-derived monitoring of asbestos mine rehabilitation in the post mining environments of Mafefe and Mathabatha, Limpopo Province, South Africa
Authors: Petja, Brilliant Mareme
Advisors: Tengbeh, G.T.
Other Contributors: Twumasi, Y.A.
Keywords: Asbestos mine
Rehabilitation
Issue Date: 2009
Abstract: Mining of the environment leaves scars of environmental damage and associated health consequences resulting from exploration, extraction and processing of minerals. These impacts tend to get worse during the post closure period on the abandoned derelict mines. The South African government is conducting environmental remediation on the mines which were abandoned by colonial mining companies. In this situation, monitoring and evaluation of such projects becomes a necessity to ensure sustainability of the mine rehabilitation process. However, the government did not have any plan and/or capacity to monitor the rehabilitation process. This study therefore utilizes remote sensing techniques to monitor the asbestos mine rehabilitation process at Mafefe and Mathabatha and to assess its effectiveness as short and long term strategies of environmental management. This research used Landsat Thematic Mapper (TM) images (1989 - 2004) to assess and monitor mine degradation and rehabilitation efforts in the study area. Two scenes were acquired for each year, representing both low peak and high peak growing periods. An image differencing method (NDVI) was used to assess the condition of vegetation in the study area.Results showed both positive and negative trends in vegetation growth. In order to understand the dynamics depicted from satellite images in the post mining phase, a field campaign was conducted to understand the reflective properties of the variables (vegetation species) used for mine rehabilitation. Results using leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) provides a proper reasoning for the type of positive environmental change reflected from satellite images. This therefore makes remote sensing an important tool for the limited field monitoring capacity for observing the dynamics of mining environments in the post closure phase. The image differencing method also helped in identifying areas that needs further rehabilitation.Despite the rehabilitation efforts, field evidence shows that traces of different asbestos minerals appear scattered even after the rehabilitation process has been conducted. This has not been properly reported since there was no effectively coordinated monitoring procedure in place to assess the progress of mine rehabilitation in mitigating asbestos pollution. This study therefore used in situ remote sensing techniques to spectrally differentiate various types of asbestos minerals with the aim of determining its potential in assessing asbestos pollution.Data generated from an X-Ray Diffraction and Scanning Electron Microscopy were also utilized for the identification and characterization of asbestos minerals in soil and water of the rehabilitated environments which were also examined using in situ remote sensing. An Analytical Spectral Devices (ASD) Field Spectrometer was used to collect spectra of asbestos minerals and that of soil and water samples for comparative analysis with laboratory results. Results showed that in situ remote sensing can play a significant role in monitoring the distribution of the asbestos minerals over rehabilitated surface areas. However, the spectral characteristics of asbestos minerals in the water bodies were not conclusive enough when compared to laboratory methods.Within the context of South Africa as a developing country, remote sensing is recommended as an important tool for periodic assessment and monitoring of mine rehabilitation. This will fill the gap created from the limited capacity within the government for monitoring and evaluation of asbestos mine rehabilitation. It is also the most cost effective method of conducting natural resource monitoring.
Description: Thesis (Ph.D. (Geography)(GIS and remote sensing)) --University of Limpopo, 2009
URI: http://hdl.handle.net/10386/557
Library of Congress Subject Headings: Asbestos mine and mining
Appears in Collections:Theses and Dissertations (Agriculture)

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