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As a result of rural settlements moving and relocation for coal mining and rural settlements expansion for new village construction, the rural settlements have been dramatically changed in the mixed mining-rural-settlement area of the Pinglu District of Shuozhou City in northern Shanxi Province of China. There are few studies that assess the characteristics and reasons of rural settlement changes in this compound area. This paper used satellite data and secondary data information on social and economic development in a mixed-method case study to analyze the characteristics and reasons of rural settlement changes in Pinglu District of Shuozhou City in northern Shanxi Province of China over the period 1986–2013. Three significant research findings were: (1) There were notable changes in the distribution of the rural settlements, and the total area of rural settlements increased by 1862.28 ha between 1986 and 2013, with the transformation of cultivated land to rural settlements being the most dominant change in land use. (2) The rural settlements increased with buffer radius increased up to 6–8 km which has become the standard boundary for rural settlement distribution. (3) The influential factors that have been identified for rural settlement changes included avoiding impacts due to coal mining, an urgency to build simple houses for the compensation, the relocation of farmers, the construction of new villages and land reclamation of abandoned rural settlements. These findings are useful for resource-based rural settlement management, providing reasonable compensation and relocation options when acquiring land in mining areas both within and beyond the study area in China. [ABSTRACT FROM AUTHOR]

• The PV potential in coal mining subsidence areas of Yangquan City was evaluated. • Effects of different deformation thresholds on the PV potential has been discussed. • The PV power potential in subsidence area can meet 30% of the electricity demand. • The LCOE considering the land price of the subsidence area is RMB 0.3934/kWh. Accurately assessing the photovoltaic (PV) power generation potential in coal mining subsiding regions is of great significance for the transformation of a resource-based city and the goal of carbon neutrality. In this paper, we proposed an assessment method for the PV power potential in coal mining subsidence areas. Both the environmental factors and ground deformation by interferometric synthetic aperture radar were fully considered. Furthermore, the levelized cost of PV electricity in subsidence areas and the benefits were predicted. Yangquan City, Shanxi province was selected as a study case. Results show that the optimal areas for PV power generation under the three-deformation rate ranges of (−40, −10), (−50, −10), and (−60, −10) mm/year in the Yangquan subsidence area are 32.13, 37.89 and 41.22 km2, respectively. The selected optimal PV construction regions agree well with the exiting PV facilities, indicating the effectiveness of the proposed method. The levelized cost of energy is estimated at 0.3934 RMB/kWh. The annual power generation can meet about 33 % of the electricity demand of Yangquan City. This work would guide the construction of PV power generation facilities in the coal mining subsidence areas for the transformation and upgrading of the mineral resource-based cities. [ABSTRACT FROM AUTHOR]

Abstract: Efforts to control aeolian desertification in China have focused on the arid and semiarid regions. However, the direct dust emission rates, sediment characteristics and local-scale controls, as well as the measures needed to combat desertification, remain poorly understood in northwest Shanxi Province. Aeolian desertification is regarded as an obstacle to local sustainable socioeconomic development. This paper investigated changes in aeolian desertification between 1975 and 2010 on the northwestern Shanxi Plateau. In this study, remote sensing images were used to classify land suffering from aeolian desertification into four categories: light, moderate, severe, and extremely severe. To evaluate the evolution and status of aeolian desertification as well as its causes, we interpreted and analyzed Landsat multi-spectral scanner (MSS) image (acquired in 1975) and Landsat Thematic Mapper (TM) images (acquired in 1991, 2000, 2006, and 2010) as well as meteorological and socioeconomic data. Results revealed 11,866km2, 13,362km2, 14,051km2, 13,613km2, and 12,318km2 of aeolian desertified land (ADL) in the above 5 periods, respectively. The spatial dynamics and patterns showed two stages: expansion during 1975–2000 at a rate of 87.37km2 a−1, and spatial transfer of affected areas during 2000–2010 with a net decrease of 173.27km2 a−1. During the evolution of aeolian desertification, areas of moderate ADL had the greatest dynamic response (11.45%). The factors controlling ADL dynamics were analyzed from the perspectives of two groups of factors: natural factors and human activities. Our results indicated that the climate-dominated natural factors contribute greatly to the occurrence and development of ADL. However, they are not the fundamental causes of its development. The human factors are the primary and direct driving forces responsible for the increase in ADL area. More thorough quantitative analysis, with more frequent remotely sensed data is needed to assess the driving forces in more detail. [Copyright &y& Elsevier]

In Shanxi Province, China, groundwater is a major problem and exploration of groundwater potential zones (GWPZs) is a great necessity. This paper contributed to integrate RS-GIS to delineate GWPZ and applied Fuzzy-AHP method in a single platform. The main objective includes delineation GWPZs with RS and geo-environmental factors using Fuzzy-AHP method. Fuzzy-AHP method was employed to calculate weight of factors. RS-GIS was used to create maps and discover groundwater availability. GWPZs were classified in five separate classes. Results indicated that 13.26%, 27.02%, 26.35%, 23.64%, and 9.71% area classified as very good, good, moderate, poor, and very poor GWPZs. The validated analytical results revealed 82.5%, 12.3%, 3.5%, and 1.7% existing water wells exhibited in very good, good, moderate, and poor/very poor GWPZs. This indicates Fuzzy-AHP model generated findings were in very good agreement with ground-truth data. This RS-GIS based Fuzzy-AHP method is proficient and efficient in identification and delineation of GWPZs. Image 1 • Groundwater potential zones (GWPZs) in semi-arid area delineated with RS-GIS. • Seven geo-environmental factors are used for GWPZ. • RS-GIS for GWPZ and Fuzzy-AHP model are used in a single platform. • Fuzzy-AHP method was employed to calculate the weight of the factors. • GWPZs are classified as very good, good, moderate, poor, and very poor GWPZ. [ABSTRACT FROM AUTHOR]