Ecological vulnerability assessment of a China's representative mining city based on hyperspectral remote sensing

Dai, Xiaoai; Feng, Haipeng; Xiao, Lixiao; Zhou, Jiayun; Wang, Zekun; Fu, Tianzhang; Shan, Yunfeng; Yang, Xinrong; Ye, Yakang; Xu, Li; Jiang, Xiaoli; Fang, Shibo; Yao, Yuanzhi

doi:10.1016/j.ecolind.2022.109663

Cited by 17 publications

(3 citation statements)

References 66 publications

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“…Hyperspectral remote sensing measures radiated, emitted, and absorbed energy at hundreds of narrow and spectrally adjacent wavelengths. Hyperspectral remote sensing can span over various optical domains such as the visible (VIS; 400-700 nm), near infrared (NIR; 700-1200 nm), shortwave infrared (SWIR; 1000-2500 nm), midwave infrared (MWIR; 3000-7000 nm) and longwave infrared (LWIR; 7000-13,000 nm) [126][127][128]. The VIS-SWIR regions of the electromagnetic spectrum enable the detection and identification of hydrated minerals [129,130].…”

Section: Phytogeochemistry Integrative Exploration Approachesmentioning

confidence: 99%

Geochemistry of Terrestrial Plants in the Central African Copperbelt: Implications for Sediment Hosted Copper-Cobalt Exploration

Mukube,

Hitzman,

Machogo-Phao

et al. 2024

Minerals

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Mineral exploration has increasingly targeted areas covered by in situ or transported overburden for shallow to deep-seated orebodies. It remains critical to develop better means to detect the surficial chemical footprint of mineralized areas covered by thick regolith. In such settings, plant geochemistry could potentially be a useful exploration tool, as different plant species have varying degrees of tolerance to metal enrichment in the soil. This review provides insights into the geological and geochemical controls on metal accumulation patterns in soil–plant systems of the Central African Copperbelt. In addition, it highlights the opportunities for integrating the geochemistry of terrestrial plants in emerging exploration technologies, identifies research gaps, and suggests future directions for developing phytogeochemical sampling techniques. This review was conducted using reputable online scholarly databases targeting original research articles published between January 2005 and March 2023, from which selected articles were identified, screened, and used to explore current advances, opportunities, and future directions for the use of plant geochemistry in sediment hosted Cu–Co exploration in the Central African Copperbelt. Various plant species are recognized as ore deposit indicators through either independent phytogeochemistry or complementary approaches. In the Central African Copperbelt, the successful application of hyperaccumulator species for phytoremediation provides the basis for adopting phytogeochemistry in mineral exploration. Furthermore, current advances in remote sensing, machine learning, and deep learning techniques could enable multi-source data integration and allow for the integration of phytogeochemistry.

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Section: Phytogeochemistry Integrative Exploration Approachesmentioning

confidence: 99%

Geochemistry of Terrestrial Plants in the Central African Copperbelt: Implications for Sediment Hosted Copper-Cobalt Exploration

Mukube,

Hitzman,

Machogo-Phao

et al. 2024

Minerals

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“…The fierce global warming and human activities have had significant impacts on vegetation [1], and vegetation degradation is an important external expression of vulnerability [2]. Land use changes and intensified environmental pollution caused by human activities can both result in vegetation degradation [3,4] and further increase vegetation vulnerability. Also, continuous global warming can increase the vulnerability of 50% of vegetation on Earth [5].…”

Section: Introductionmentioning

confidence: 99%

Prediction and Transition of Vegetation Vulnerability in the Mara River Basin under Different Shared Socio-Economic Pathways (SSPs), East Africa

Zhu,

Zhang,

Feng

et al. 2024

Forests

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The Mara River basin (MRB) has a world-famous ecosystem, but the vegetation has been damaged due to economic development in recent years, and there is little known about the area that will experience severe vegetation damage in the future. Based on the vegetation vulnerability system, principal component analysis, and three Shared Socio-Economic Pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5), vegetation vulnerability was calculated for the base period (2010–2019), near future period (2020–2059) and distinct future period (2060–2099) in the MRB. The spatial cluster of vegetation vulnerability was revealed by spatial correlation analysis, and the transition of vegetation vulnerability of different periods was analyzed by stochastic matrix. The results showed that for all periods, the vulnerability showed a high–high cluster in the east, and a low–low cluster midstream and downstream. From the stochastic matrix, the area of high vulnerability increased the least under the SSP1-2.6, while it increased the most under the SSP5-8.5. The vegetation vulnerability upstream increased the most from the base period to the near future period and distinct future period in the MRB. By comparing the vegetation vulnerability under different scenarios and pointing out the areas with the highest vulnerability increase, this study can better provide comprehensive decision-making for vegetation protection in the MRB.

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“…It has provided important energy and material conditions for China's rapid economic and social development [8,9]. However, the rise and prosperity of mining cities also pose significant challenges to ecosystems [10,11]. Mining, as the most human-disturbing of human activities [12], has caused great damage to the ecosystems of mining cities in particular.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

Zeng,

Dai,

et al. 2024

Sustainability

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The environmental quality of a mining city has a direct impact on regional sustainable development and has become a key indicator for assessing the effectiveness of national environmental policies. However, against the backdrop of accelerated urbanization, increased demand for resource development, and the promotion of the concept of ecological civilization, mining cities are faced with the major challenge of balancing economic development and ecological environmental protection. This study aims to deeply investigate the spatial and temporal variations of environmental quality and its driving mechanisms of mineral resource-based cities. This study utilizes the wide coverage and multitemporal capabilities of MODIS optical and thermal infrared remote sensing data. It innovatively develops the remote sensing ecological index (RSEI) algorithm on the PIE-Engine cloud platform to quickly obtain the RSEI, which reflects the quality of the ecological environment. The spatial and temporal evolution characteristics of the environmental quality in seven typical mining cities in China from 2001 to 2022 were analyzed. Combined with the vector mine surface data, the spatial and temporal variability of the impacts of mining activities on the ecological environment were quantitatively separated and explored. In particular, the characteristics of mining cities were taken into account by creating buffer zones and zoning statistics to analyze the response relationship between RSEI and these factors, including the distance to the mining area and the percentage of the mining area. In addition, the drivers and impacts of RSEI in 2019 were analyzed through Pearson correlation coefficients pixel by pixel with 10 factors, including natural, economic, and mining. Regression modeling of RSEI in 2019 was performed using the random forest (RF) model, and these drivers were ranked in order of importance through random forest factor importance assessment. The results showed that (1) the ecological quality of mining cities changed significantly during the study period, and the negative impacts of mining activities on the ecological environment were significant. (2) The areas with low RSEI values were closely related to the mining areas and cities. (3) The RSEI in the mining areas of mining cities was generally lower than the average level of the cities. The RSEI gradually increased as the distance to the mine site increased. (4) The increase in the size of the mine area initially exacerbates the impact on the ecological environment, but the impact is weakened beyond a certain threshold. (5) The distance to the mining area is the most important factor affecting the quality of the ecological environment, followed by DEM, GDP, and precipitation. This study is of great importance for advancing sustainable development in mining cities and formulating sustainable strategies.

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Ecological vulnerability assessment of a China's representative mining city based on hyperspectral remote sensing

Cited by 17 publications

References 66 publications

Geochemistry of Terrestrial Plants in the Central African Copperbelt: Implications for Sediment Hosted Copper-Cobalt Exploration

Geochemistry of Terrestrial Plants in the Central African Copperbelt: Implications for Sediment Hosted Copper-Cobalt Exploration

Prediction and Transition of Vegetation Vulnerability in the Mara River Basin under Different Shared Socio-Economic Pathways (SSPs), East Africa

Quantifying the Impact and Importance of Natural, Economic, and Mining Activities on Environmental Quality Using the PIE-Engine Cloud Platform: A Case Study of Seven Typical Mining Cities in China

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