Ang, Michelle Li Ern
(2023)
Characterising socio-environmental mining impacts using GIS and remote sensing:a case study in Didipio, Philippines.
MPhil thesis, University of Nottingham.
Abstract
Mining results in significant land cover changes, directly and indirectly affecting local communities and the natural landscape via complex, interrelated and often long-lasting impacts. With the impending increase in demand for mineral resources, the need for robust analyses and clear reporting of data on the local and regional changes is considered essential for mining companies to effectively detect, track, sustainably manage and mitigate impacts. Remote sensing and GIS methods hold the potential to assist and improve conventional social science approaches; they provide the means to spatially capture and triangulate data from the dynamic mining landscape to study past and ongoing socio-environmental impacts. This thesis aims to investigate the use of spatially explicit GIS and Remote Sensing methods for assessing the social and environmental impacts of mining. To achieve this, the chapters (1) extensively reviewed prior studies that integrated GIS and remote sensing with social science methodologies to evaluate socio-economic and environmental mining impacts, (2) compile recommendations on how the integration of GIS, Remote Sensing, and Social Science can be enhanced for future research on the socio-economic and environmental implications of mining, and (3) characterise the land cover changes in a mining landscape in Didipio, Philippines, and its concurrent impacts on socio-environmental land uses.
Chapter 1 of this thesis introduces the importance of this research and its relevance to present societal concerns. The aim and scope of the thesis are also outlined here.
Chapter 2 comprehensively examines past research efforts by providing a systematic review of how GIS and remote sensing approaches have been integrated with social science approaches to assess socio-economic and environmental impacts of mining on local communities. We found that the integration of GIS and remote sensing applications with social science methods is a functional step and often the only means to spatially capture and coherently assess the various and complex dimensions of mining impacts. Overall, more research is still needed to improve interdisciplinary data capture and analysis, particularly to analyse less tangible socio-economic impacts. Concerted efforts must also be made to improve data availability, quality, geographic categorisation, consistency, validation, and transparency to achieve a more spatially integrated evaluation of socio-economic mining impacts.Multidimensional approaches involving interdisciplinary methods and coordinated efforts from all stakeholders are required to effectively capture and coherently analyse the various data types needed for a full understanding of mining impacts.
In Chapter 3, land use and land cover changes in a Philippines mining landscape are classified and the concurrent impacts of mining on socio-environmental land uses were evaluated. This case study demonstrated how a range of recent and novel methods can be used to map socio-environmental mining landscapes. A time series of classified land use and land cover (LULC) maps was created using composites of multispectral Landsat images, vegetation indices and a Digital Elevation Model (DEM). Landsat historical imagery was used to successfully characterize coarse-scale high-level land covers via supervised Random Forest classification in Google Earth Engine (GEE). Web-based mapping by local experts was then used within selected zones of importance to characterise key fine thematic resolution land use categories; such fine resolution is beyond what is possible using only Landsat. Overall, the time series accurately estimated LULC change, and revealed significant temporal trends useful for studying socio-environmental indicators. The methods developed and their limitations were critically evaluated and potential ways to improve the workflow in terms of the quality and efficiency of data acquisition are proposed.
This thesis is concluded in Chapter 4, which synthesizes the contributions made in this study. Recommendations and challenges anticipated for future research towards the goal of a more spatially integrated assessment of socio-economic mining impacts are outlined.
Given the upcoming growth in demand, socioeconomic and environmental mining consequences must be handled in a multidimensional manner that involves interdisciplinary methods and coordinated efforts from all stakeholders. This research reinforces the potential that GIS and Remote Sensing holds to facilitate and optimise conventional socio-environmental impact assessments. The novel approach of stakeholder engagement via participatory GIS can be further enhanced to support successful socio-spatial data integration, inclusive analysis, and comprehensive planning throughout the mine life cycle to bring us a step closer in securing a sustainable future for mining.
Actions (Archive Staff Only)
 |
Edit View |
Tools
Tools
![[img]](/style/images/fileicons/application_pdf.png)