This paper combines the principal component analysis (PCA) with a modified normalized difference water index (MNDWI) to improve the accuracy in extracting water bodies from Landsat Thematic Mapper (TM) imagery. To this end, one Landsat TM image of Taiyuan, China, obtained on 23 September 2011 was used to perform PCA and extract MNDWI. The first two principal components of the PCA and extracted MNDWI were combined to compose a false-colour image, which was then used to develop the enhanced water index (EWI). This method was applied to extract water bodies from Landsat TM imagery for both urban areas and surrounding mountain areas of Taiyuan, which resulted in an overall accuracy of 95%. EWI was also compared with other common water indices in extracting water bodies including general water index, MNDWI and new water index. The results show that the proposed method has the highest accuracy and is recommended to extract water bodies using multispectral satellite imagery for urban areas with mountains surrounded.

The soil organic carbon (SOC) pool in farmland is changing rapidly due to human activities, thereby greatly affecting the regional and global environment, as well as influencing soil fertility and crop yields. The present study investigated the effects of underground coal mining on the regional SOC pool in farmland in the Jiuli Mining Area of Xuzhou City in China as a typical coal mining region based on field sampling, chemical analysis, model construction, and spatial analysis using the software of ArcGIS. The results showed that in the mining subsidence area, spatial variations in the SOC content and soil bulk density were mainly caused by structural factors (mining subsidence, subsidence waterlogging, and other structural factors due to coal mining) at a regional scale. SOC storage in farmland soil decreased sharply in non-waterlogged subsidence farmland and seasonally waterlogged subsidence farmland in the areas with mining, whereas the SOC storage increased in waterlogged wetland after coal mining. The SOC was reduced by 102,882 tonnes (32.81%) compared with the original SOC stock as a consequence of coal mining, and thus the effect of underground coal mining on the regional SOC pool in farmland was characterized as a carbon loss process. Land-use changes, soil degradation and erosion contributed almost equally to the carbon loss process in the study area. The results of this study may facilitate evaluations of low-carbon land reclamation and ecological compensation in mining areas.

Impervious surface(s) (ISs) as an important ecological index has been widely used in the study of urban ecological environment evaluation, urban hydrology and urban vegetation mapping. In this paper, methods in feature selection, including principal component analysis (PCA) and optimum index factor (OIF), as well as indices approaches such as the normalized difference impervious surface index (NDISI) and normalized difference built-up index (NDBI) were evaluated. A new approach, experimental band combination (EBC), was proposed to extract ISs in Taiyuan city of Shanxi Province, China, using Landsat Thematic Mapper (TM) imagery. The same classification procedure was applied on original TM image, PCA image, OIF image and EBC image respectively to extract IS; the results were also compared with those extracted from the aforementioned indices approaches. Accuracy assessments were conducted on each of them using 253 randomly selected sampling points. By comparison and analysis, it was found that the EBC method obtained the highest producer’s accuracy (87.63%), user’s accuracy (90.43%) and overall accuracy (87.75%), with the Kappa statistic of 0.85 in IS extraction.

Understanding the dynamics of soil water content (SWC) is essential for effective land management, particularly in regions affected by underground mining. This study investigates the spatial and temporal patterns of SWC and its interaction with topographic and edaphic factors in coal mining and non-coal mining areas of the Chenghe watershed, located in the southeast of the Chinese Loess Plateau, which is divided by a river. Our findings revealed that the capacity to retain moisture in the top layer of coal mining areas is significantly higher (25.21%) compared to non-coal mining areas, although deeper layers exhibit lower SWC, indicating altered moisture dynamics due to underground mining disturbances. Coal mining areas show greater spatial and temporal variability in SWC, suggesting increased sensitivity to moisture fluctuations, which complicates water management practices. Additionally, underground mining activities introduce more intense effects on the relationship between SWC and topographic factors (i.e., GCVR across soil profile of 0–60 cm; slope at depth of 50 cm) or edaphic factors (i.e., soil organic matter and available potassium at depth of 30 cm; pH at depth of 50 cm) compared to non-coal mining areas. This variability is evident in the temporal shifts from positive to negative correlations, particularly in coal mining areas, reflecting modifications in both soil physical and chemical properties resulting from mining activities. In contrast, non-coal mining areas maintain a more stable moisture regime, likely due to preserved natural soil structures and processes. These contrasting findings emphasize the necessity for tailored management strategies in coal mining regions to address the unique challenges posed by altered soil characteristics and water dynamics.