Assessment of soil fertility degradation affected by mining disturbance and land use in a coalfield via machine learning

Wang, Ziguan; Wang, Guangcai; Ren, Tingyu; Wang, Haibo; Xu, Qingyu; Zhang, Guanghui

doi:10.1016/j.ecolind.2021.107608

Cited by 31 publications

(17 citation statements)

References 38 publications

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“…In mining sites, it is suggested that SOM recovery may take decades to reach natural soils, or even not show complete recovery [46,47]. However, as observed in this study, Trindade et al [22] also found the maintenance of carbon cycling during the early stages in the progress of environmental rehabilitation by analyzing enzymes such as cellulase and beta-amylase.…”

Section: Soc Stock and Rehabilitationmentioning

confidence: 63%

Spectral and Soil Quality Index for Monitoring Environmental Rehabilitation and Soil Carbon Stock in an Amazonian Sandstone Mine

et al. 2022

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Rehabilitation is the key factor for improving soil quality and soil carbon stock after mining operations. Monitoring is necessary to evaluate the progress of rehabilitation and its success, but the use of repeated field surveys is costly and time-consuming at a large scale. This study aimed to monitor the environmental/soil rehabilitation process of an Amazonian sandstone mine by applying spectral indices for predicting soil organic carbon (SOC) stock and comparing them to soil quality index. The studied area has different chronological rehabilitation stages: initial, intermediate, and advanced with 2, 10, and 12 years of onset rehabilitation activities, respectively. Non-rehabilitated (NR) and two native forest areas (RA) were used as controls. Soil samples were analyzed for physical, chemical, and biological attributes. After determination of Normalized Difference Vegetation Index and Bare Soil Index, simple regression analysis comparing these indices with SOC stock showed a good fit (R2 = 0.82). Rehabilitated areas presented higher soil quality index (~1.50-fold) and SOC stock (~10.6-fold) than NR; however, they did not differ of RA. The use of spectral indices was effective for monitoring the soil quality in this study, with a positive correlation between the predicted SOC stock and the calculated soil quality index.

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Section: Soc Stock and Rehabilitationmentioning

confidence: 63%

Spectral and Soil Quality Index for Monitoring Environmental Rehabilitation and Soil Carbon Stock in an Amazonian Sandstone Mine

et al. 2022

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“…However, mining activities eliminate the first soil horizon, an essential site for nutrient storage and exchange. Therefore, the nutrient holding capacity is drastically reduced after mining disturbance [57,58].…”

Section: Discussionmentioning

confidence: 99%

Soil Quality Assessment in Response to Water Erosion and Mining Activity

et al. 2023

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Erosion significantly decreases the depth of a soil, the nutrients available for plants, the organic matter and, consequently, the productivity of the edaphic environment. Due to the above considerations, the objective of this study was to evaluate, through various properties, the quality of two eroded soils, one eroded by water and the other by mining activity, amended with biosolids. The quality for both soils was estimated through the selection of a minimum set of data by means of principal component analysis (PCA) and the subsequent realization of correlations, multiple regressions and finally calculations of normalized values (Vn) of those properties considered as indicators of soil quality. According to the results, inorganic nitrogen (NI) and respiratory activity (RA) were the properties selected as indicators to assess quality. For soil eroded by water and by mining activity, NI presented a low and very low quality, respectively (class 4 and 5 of quality according to the calculation of Vn). The quality of RA in soil eroded by mining extraction was very high (quality class 1 according to Vn), and thus it can be considered an ideal indicator for the evaluation of soil quality due to its sensitivity to anthropogenic changes (mining) in soil.

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“…Currently, around 30% of mining regions in China reached a stage of maturity and decline following an extended period of mining activity. Inefficient utilization of land resources can lead to significant wastage, necessitating the implementation of reclamation as a viable strategy for safeguarding these resources [ 1 ]. Simultaneously, it can enhance the land use rate within the mining region, so playing a crucial role in the adjustment of the mining area’s economic structure and the transformation of its growth patterns [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Predication of the post mining land use based on random forest and DBSCAN

Bo,

Lv,

Wang

et al. 2024

PLoS ONE

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Mine reclamation is one of the most important stages of the mining activities in line with the basic principles of sustainable development. In this study, different post-mining land uses are evaluated in the Hongliulin mining area, which is located in Shen mu country of China. 145 soil samples were collected in the May,2021 by using the soil auger, and the sampling depths were 0–20 cm. The sampling points contains 45 to be reclaimed samples and 100 existing classification land use types. 14 environmental factors including soil organic matter (SOM), total nitrogen (TN), available phosphate (AP), available potassium (AK), K, Slope steepness, curvatures, aspect, length, Topographic Wetness Index (TWI), NDVI and elevation were extracted and calculated based on laboratory test and digital elevation map. The random forest classier showed a great prediction capability, with only 1 miss-classified sample in the validation data-set, the accuracy of the classification model was 95%. The content of TN of C1 is 5 times more than C2 and 4 times more than C3. Also, the K value of C1 column is maximum and over 0.4, which means the soil particle is relatively smaller and the soil texture of it is sandy loam. In terms of the 45 to be reclaimed samples, 15 samples were classified into C1, 23 samples were classified into C2, 5 samples were classified into C3, 2 samples were classified into C4. The value of K and content of soil nutrients of the samples classified to be C1 column(C1-C) is maximum. The soybean and murphy were suggested based on the soil nutrients index and with the mining disturbance on cluster 2 of C1, the ground subsidence filling as well as soil nutrients increased strategy should be applied. The result may contribute to the land use planning and idle land utilization strategy.

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Assessment of soil fertility degradation affected by mining disturbance and land use in a coalfield via machine learning

Cited by 31 publications

References 38 publications

Spectral and Soil Quality Index for Monitoring Environmental Rehabilitation and Soil Carbon Stock in an Amazonian Sandstone Mine

Spectral and Soil Quality Index for Monitoring Environmental Rehabilitation and Soil Carbon Stock in an Amazonian Sandstone Mine

Soil Quality Assessment in Response to Water Erosion and Mining Activity

Predication of the post mining land use based on random forest and DBSCAN

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