Remote Sensing and Mineral Exploration in the Arabian Shield: The Wadi Bidah Mining District Example

Volesky, John C.

doi:10.1016/s1342-937x(05)70694-8

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…This water can be very acidic and laden with high concentrations of toxic heavy metals posing threats to the environment. Mining activities also cause health problems in the local communities and among wildlife by exposing them to mining waste in air, water and soil [24,[34][35][36][37][38]. The large-scale mining in the Qin-Ba mountainous area is posing direct and indirect threats to the local ecosystem [39,40].…”

Section: The Impact Of Mining On the Ecological Environmentmentioning

confidence: 99%

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Cai

Sun

et al. 2016

Sustainability

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Abstract:The Qin-Ba Ecological Functional Zone is a component of China's ecological security pattern designed to protect the regional ecosystem and maintain biodiversity. However, due to the impact of mining and urban encroachment, the plight of a sustainable ecosystem in the Qin-Ba mountainous area is deteriorating. This paper has used a remote sensing and geographic information system (GIS) to examine the impacts of mining and urban encroachment on the environment in the Qin-Ba mountainous area. The results indicate that the total mined area in 2013 was 22 km 2 and is predicted to escalate. Results also show that the ecosystems in Fengxian County, Shaanxi Province and Baokang County, Hubei Province were most severely affected by mining. Urbanization in the Qin-Ba mountainous area has seen an increase of 85.58 km 2 in urban land use from 2010 to 2013. In addition, infrastructure development including airport construction, tourism resorts and real estate development in the Qin-Ba mountainous area has intensified environmental and biodiversity disturbances since large areas of forest have been cleared. Our results should provide insight and assistance to city planners and government officials in making informed decisions.

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Section: The Impact Of Mining On the Ecological Environmentmentioning

confidence: 99%

Impacts of Mining and Urbanization on the Qin-Ba Mountainous Environment, China

Cai

Sun

et al. 2016

Sustainability

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“…Numerous studies have confirmed the importance of remote sensing technology in mining-related fields, including mineral exploration [30], detecting and monitoring coal fires [31], evaluating ground subsidence [32][33][34], mapping mined areas [35,36], quantifying the extent of mining activities [36,37], and monitoring the environmental impacts of surface coal mining [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Land Cover and Vegetation Changes in Juhugeng Coal Mining Area Based on Multi-Source Remote Sensing Data

Hong

Wang

et al. 2023

Remote Sensing

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Coal is the most prevalent energy source in China and plays an important role in ensuring energy security. The continuous monitoring of coal mining activities is helpful to clarify the incremental space of coal production and establish a rational framework for future coal production capacity. In this study, a multi-source remote sensing approach utilizing SPOT 4, GF, and Landsat data is employed to monitor land cover and vegetation changes in the Juhugeng mining area of the Muli coalfield over a span of nearly 20 years. The analysis incorporates an object-oriented classification method and a vegetation parameter to derive insights. The findings reveal that the mining operations can be divided into two periods, since their initiation in 2003 until their cessation in 2021, with a dividing point around 2013/2014. The initial phase witnessed rapid and even accelerated expansion of the mine, while the subsequent phase was characterized by more stable development and the implementation of some restorative measures for the mine environment. Although the vegetation parameter, Fractional Vegetation Cover (FVC), indicates some reclamation efforts within the mining area, the extent of the reclaimed land remains limited. This study demonstrates the effective application of object-oriented classification in conjunction with the vegetation parameter FVC for monitoring coal mining areas.

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