Rapid and large-scale estimation of soil salt content (SSC) and organic matter (SOM) using multi-source remote sensing is of great significance for the real-time monitoring of arable land quality. In this study, we simultaneously predicted SSC and SOM on arable land in the Yellow River Delta (YRD), based on ground measurement data, unmanned aerial vehicle (UAV) hyperspectral imagery, and Landsat-8 multispectral imagery. The reflectance averaging method was used to resample UAV hyperspectra to simulate the Landsat-8 OLI data (referred to as fitted multispectra). Correlation analyses and the multiple regression method were used to construct SSC and SOM hyperspectral/fitted multispectral estimation models. Then, the best SSC and SOM fitted multispectral estimation models based on UAV images were applied to a reflectance-corrected Landsat-8 image, and SSC and SOM distributions were obtained for the YRD. The estimation results revealed that moderately salinized arable land accounted for the largest proportion of area in the YRD (48.44%), with the SOM of most arable land (60.31%) at medium or lower levels. A significant negative spatial correlation was detected between SSC and SOM in most regions. This study integrates the advantages of UAV hyperspectral and satellite multispectral data, thereby realizing rapid and accurate estimation of SSC and SOM for a large-scale area, which is of great significance for the targeted improvement of arable land in the YRD.
The chemical reaction between calcium ions (Ca2+) and phosphate in the soil is the main way to maintain the availability of soil phosphorus. Thus, we believe stimulating coal gangue with Ca2+ solution would be an effective way to improve its adsorption and desorption capacity toward phosphate. In order to explore the effects of different pH of Ca2+ solution on the modified effect of coal gangue, we conducted mechanical grinding (<1 mm), high temperature calcination (800 °C), and the stimulation of Ca2+ solution with different pH (2, 7, 13), to prepare acidic calcium-modified coal gangue (Ac-CG) (Ac-CG, acidic calcium-modified coal gangue; Ne-CG, neutral calcium-modified coal gangue; Al-CG, alkali calcium-modified coal gangue; RCG, raw coal gangue), neutral calcium-modified coal gangue (Ne-CG), and alkali calcium-modified coal gangue (Al-CG); raw coal gangue (RCG) was regarded as the control. The results indicated that Al-CG had better phosphate adsorption (3.599 mg g−1); this favorable adsorption performance of Al-CG was related to the formation of hydrated calcium silicate gel and ettringite, which provided more Ca2+, Al3+, and hydroxyl groups, and a larger specific surface area (9.497 m2 g−1). Moreover, Al-CG not only held more phosphate but also maintained its availability longer for plants. It is suggested that stimulating coal gangue with Ca2+ solution under alkaline conditions is a perfect way to enhance its adsorption and desorption capacity toward phosphate; the Al-CG we prepared could be used as filling material and soil conditioner in the reclamation area.
Mining areas characterized by high underground water levels are one of the most important types of coal mining areas in China. In regions with high groundwater levels, the soil ecological environment is destroyed due to surface subsidence induced by coal mining and soil disturbances. There are a variety of soil factors each with different degrees of spatial variation, and the impact on soil microbial communities is particularly severe. In order to explore the change and driving mechanism of soil microbial community structure in coal mining subsidence areas with high underground water levels, we sought to elucidate these mechanisms by studying soil samples collected at different depths (SL: 0-20 cm, ML: 20-40 cm, DL: 40-60 cm) of a deep coal seam subsidence area (T1) and shallow coal seam subsidence area (T2) and their control non-subsidence areas (W1 and W2) within a typical coal mine area with high underground water levels in southwest Shandong Province. These soil samples were used for determination and analysis of their physicochemical properties and microbial diversity. The results show that coal mining subsidence has significant effects on the soil physicochemical properties and soil microbial community. With the increase in sampling depth, the soil water content (SWC), bulk density (BD), and soil pH increased, whereas the contents of soil alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil organic matter (SOM) decreased. Compared with the non-subsidence area, the soil alkalinity in the subsidence area was lower and the soil moisture content, affected by the underground water level, was higher; the richness and diversity of the microbial community was lower in the subsidence area despite its higher relative abundance of Actinobacteria, Chloroflexi, and Myxomycota species. In addition, species of Thelebolales and Pleosporales were dominant in T1 and T2, respectively. Soil pH was observed to be the most important physicochemical factor affecting microbial communities, followed by AN and AP. The results of our study provide a theoretical basis for soil ecological restoration and land reclamation in mining areas with high underground water levels.
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