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In this paper, we selected Xilingol League in Inner Mongolia, China, as the research area, based on the land-use data of five Landsat remote sensing images taken between 1980 and 2015. Then, we calculated the complex network eigenvalues, such as the average shortest path, betweenness centrality, and degree, to identify the key land-use types, stability, and ecological environment change regularity from the perspective of the land-use system. Finally, we used the Canonical Correspondence Analysis (CCA) method to explore the main driving forces behind changes in the land-use system, to provide scientific support for the study of changing trends in land-use, and regional grassland ecological management. The findings are shown below. First, in the last 35 years, grasslands have always been the major type of change in land-use transfer matrices. Grasslands play a controlling role in the whole land-use system. Second, grassland and cultivated land are the major "transfer out" type of land in the Xilingol area, while construction land and water area belong to the major "transfer in" type of land. Third, the average shortest path values of four transition matrix networks were all less than 1.5, indicating that the land-use system becomes less stable, but the average shortest path values of these four networks present an increasing trend, leading to a more stable development of the land-use system. However, on the whole, it shows an upward trend, and the land-use system is moving in a stable direction. Fourth, the average annual rainfall, population, topographic factors, GDP, and distance from settlements play a prominent role in determining the spatial distribution of change in land-use in Xilingol. [ABSTRACT FROM AUTHOR]

Proximal sensing offers a novel means for determination of the heavy metal concentration in soil, facilitating low cost and rapid analysis over large areas. In this respect, spectral data and model variables play an important role. Thus far, no attempts have been made to estimate soil heavy metal content using continuum-removal (CR), different preprocessing and statistical methods, and different modeling variables. Considering the adsorption and retention of heavy metals in spectrally active constituents in soil, this study proposes a method for determining low heavy metal concentrations in soil using spectral bands associated with soil organic matter (SOM) and visible–near-infrared (Vis–NIR). To rapidly determine the concentration of heavy metals using hyperspectral data, partial least squares regression (PLSR), principal component regression (PCR), and support vector machine regression (SVMR) statistical methods and 16 preprocessing combinations were developed and explored to determine an optimal combination. The results showed that the multiplicative scatter correction and standard normal variate preprocessing methods evaluated with the second derivative spectral transformation method could accurately determine soil Cr and Ni concentrations. The root-mean-square error (RMSE) values of Vis–NIR model combinations with PLSR, PCR, and SVMR were 0.34, 3.42, and 2.15 for Cr, and 0.07, 1.78, and 1.14 for Ni, respectively. Soil Cr and Ni showed strong spectral responses to the Vis–NIR spectral band. The R2 value of the Vis–NIR-based PLSR model was higher than 0.99, and the RMSE value was 0.07–0.34, suggesting higher stability and accuracy. The results were more accurate for Ni than Cr, and PLSR showed the best performance, followed by SVMR and PCR. This perspective has critical implications for guiding quantitative biogeochemical analysis using proximal sensing data. [ABSTRACT FROM AUTHOR]

• DPSIRM model was used to evaluate the ecological security of Xilingol grassland. • Remote sensing, meteorology, socio-economic and survey data are used in this paper. • We use grid GIS method to obtain more accurate evaluation results. • We analyzed the spatial-temporal evolution characteristics of ecological security. • Changes in the center of gravity in different security levels are also explored. The quantitative evaluation of the ecological security can reflect the changes in the quality of ecological environment and provide a scientific basis for the formulation of land-use policy and for the construction of the ecological environment. In this study, we selected Xilingol League in Inner Mongolia, China, as the research area, and established the driving force-pressure-state-impact-response-management (DPSIRM) model to evaluate grassland ecological security. The results were as follows: (1) During 2005–2015, the overall trend of ecological security level in the study area increased, with the western region being relatively ecologically insecure and the eastern region being more secure. (2) The spatial distribution trend of ecological security level from west to east was " very serious alerts " → " serious alerts " → " moderate alerts " → " light alerts "→ " no alert ". (3) The " very serious alerts " and " serious alerts " are mainly concentrated in Sonid Left Banner and Sonid Right Banner, but from the perspective of spatial migration of ecological security, unsafe and less safe tend to shift to the northeast. This study provides a new idea for grassland ecological security evaluation research, has important practical significance for understanding the ecological security level of Xilingol grassland area, and will guide the reasonable development and utilization of Xilingol grassland. [ABSTRACT FROM AUTHOR]