Soil magnetic characteristics are correlated with soil pH and organic matter content. Analyzing soil magnetic characteristics, organic matter content and pH can indirectly evaluate soil pollution caused by human activities. This study analyzed the soil magnetic characteristics, organic matter content and pH in surface soil samples from different land use types in Shihezi city, a newly and rapidly developing oasis city in Xinjiang of China. The aims of this study were to explore the possible relationships among the soil magnetic parameters and thereby improve the understanding of influence of urbanization on soil properties. Eighty surface soil samples at the depth of 0-10 cm were collected from 29 July to 4 August 2013. The results showed that the magnetic minerals in surface soil were dominated by ferromagnetic minerals. Spatially, the magnetic susceptibility (χ LF ), anhysteretic remanent magnetization susceptibility (χ ARM ), saturation isothermal remanent magnetization (SIRM) and "soft" isothermal remanent magnetization (SOFT) were found to be most dominant in the new northern urban area B (N-B), followed by built-up areas (U), suburban agricultural land (F), and then the new northern urban area A (N-A). The values of χ LF , χ ARM , SIRM and SOFT were higher in the areas with high intensities of human activities and around the main roads. Meanwhile, the property "hard" isothermal remanent magnetization (HIRM) followed the order of U>N-B>F>N-A. Built-up areas had an average pH value of 7.93, which was much higher than that in the new northern urban areas as well as in suburban agricultural land, due to the increased urban pollutant emissions. The average value of soil organic matter content in the whole study area was 34.69 g/kg, and the values in the new northern urban areas were much higher than those in the suburban agricultural land and built-up areas. For suburban agricultural land, soil organic matter content was significantly negatively correlated with χ LF , and had no correlation with other magnetic parameters, since the soil was frequently ploughed. In the new northern urban areas (N-A and N-B), there were significant positive correlations of soil organic matter contents with χ ARM , SIRM, SOFT and HIRM, because natural grasslands were not frequently turned over. For the built-up areas, soil organic matter contents were significantly positively correlated with χ LF , χ ARM , SIRM and SOFT, but not significantly correlated with frequency-dependent susceptibility (χ FD , expressed as a percentage) and HIRM, because the soil was not frequently turned over or influenced by human activities. The results showed that soil magnetic characteristics are related to the soil turnover time.Citation: YANG Han, XIONG Heigang, CHEN Xuegang, WANG Yaqi, ZHANG Fang. 2015. Identifying the influence of urbanization on soil organic matter content and pH from soil magnetic characteristics. Journal of Arid Land,

Vegetation indexes have been widely used to qualitatively and quantitatively evaluate vegetation cover and its growth vigor. To further extend the study of vegetation indexes, this paper proposes to study the spatial and temporal distribution characteristics and specific driving mechanisms of vegetation indexes based on the example of Yunnan Province, China, and also adds the study of spatial and temporal prediction methods of vegetation indexes. This paper used data on this region’s normalized vegetation index (NDVI), three meteorological factors, and eight social factors from 1998 to 2019. The dynamic change in and driving mechanism of the NDVI were studied using mean value analysis, univariate linear trend regression analysis, and partial correlation analysis. In addition, the Fourier function model and the CA–Markov model were also used to predict the NDVI of Yunnan Province from 2020 to 2030 in time and space. The results show that: (1) The NDVI value in Yunnan Province is high, showing a significant growth trend. The increased vegetation coverage area has increased in the past 22 years without substantial vegetation degradation. (2) The positive promotion of meteorological factors is greater than the negative inhibition. The partial correlation of relative humidity among meteorological factors is the highest, which is the main driving factor. (3) The NDVI value is significantly positively correlated with population and economy and negatively correlated with pasture land and agricultural area. (4) The NDVI values are predicted well in time (R = 0.64) and space (Kappa = 0.8086 and 0.806), satisfying the accuracy requirements. This paper aims to enrich the theoretical and technical system of ecological environment research by studying the dynamic change, driving mechanism, and spatiotemporal prediction of the normalized vegetation index. Its results can provide the necessary theoretical basis for the simulation and prediction of vegetation indexes.

It is important to determine long-term changes in vegetation cover, and the associated driving forces, to better understand the natural and human-induced factors affecting vegetation growth. We calculated the fractional vegetation coverage (FVC) of the Urumqi River basin and selected seven natural factors (the clay and sand contents of surface soils, elevation, aspect, slope, precipitation and temperature) and one human factor (land use type). We then used the Sen–Man–Kendall method to calculate the changing trend of the FVC from 2000 to 2020. We used the optimal parameters-based geographical detector (OPGD) model to quantitatively analyze the influence of each factor on the change in vegetation coverage in the basin. The FVC of the Urumqi River basin fluctuated from 2000 to 2020, with average values between 0.22 and 0.33. The areas with no and low vegetation coverage accounted for two-thirds of the total area, whereas the areas with a medium, medium–high and high FVC accounted for one-third of the total area. The upper reaches of the river basin are glacial and forest areas with no vegetation coverage and a high FVC. The middle reaches are concentrated in areas of urban construction with a medium FVC. The lower reaches are in unstable farmland with a medium and high FVC and deserts with a low FVC and no vegetation. From the perspective of the change trend, the areas with an improved FVC accounted for 62.54% of the basin, stable areas accounted for 5.66% and degraded areas accounted for 31.8%. The FVC showed an increasing trend in the study area. The improvement was mainly in the areas of urban construction and desert. Degradation occurred in the high-elevation areas, whereas the transitional zone was unchanged. The analysis of driving forces showed that the human factor explained more of the changes in the FVC than the natural factors in the order: land use type (0.244) > temperature (0.216) > elevation (0.205) > soil clay content (0.172) > precipitation (0.163) > soil sand content (0.138) > slope (0.059) > aspect (0.014). Apart from aspect, the explanatory power (Q value) of the interaction of each factor was higher than that of the single factor. Risk detection showed that each factor had an interval in which the change in the FVC was inhibited or promoted. The optimum elevation interval of the study area was 1300–2700 m and the greatest inhibition of the FVC was seen above 3540 m. Too much or too little precipitation inhibited vegetation coverage.