A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
Journal of Geographical Sciences - Rainfall interception is of great significance to the fully utilization of rainfall in water limited areas. Until now, studies on rainfall partitioning process of... 相似文献
Three-dimensional urban cartography is needed for city changes’ assessment. The variety of studies using 3D calculations of urban elements grows each year. Building and vegetation volumes are necessary to assess and understand spatio-temporal urban changeable environments. However, there are technical questions as to which method can improve 3D urban cartographic accuracy. The innovative part of this current study is the creation of a six-band hybrid obtained from LIDAR and WorldView2 synergy. Two different enhancement algorithms demonstrated the most important spectral features for the urban development and vegetation classes. Results indicated an improvement in accuracy by up to 21.3%, according to the Kappa coefficient. Both infra-red band and intensity band were the most significant, according to the principal components analysis. The synergy delimited classes and polygons, as well as the direct display of information regarding heights of elements and improving the extraction of roads, buildings and vegetation classes. 相似文献
The purpose of this study is to estimate long-term SMC and find its relation with soil moisture (SM) of climate station in different depths and NDVI for the growing season. The study area is located in agricultural regions in the North of Mongolia. The Pearson’s correlation methodology was used in this study. We used MODIS and SPOT satellite data and 14 years data for precipitation, temperature and SMC of 38 climate stations. The estimated SMC from this methodology were compared with SM from climate data and NDVI. The estimated SMC was compared with SM of climate stations at a 10-cm depth (r2 = 0.58) and at a 50-cm depth (r2 = 0.38), respectively. From the analysis, it can be seen that the previous month’s SMC affects vegetation growth of the following month, especially from May to August. The methodology can be an advantageous indicator for taking further environmental analysis in the region. 相似文献
This paper focuses on the heavy metal enrichment and heavy metal pollution degree associated with mining activities in some crops and the soils of different parent materials in the Xiaoqinling Gold Belt. According to the geochemical analysis results of the soils observed in the gold belt, the soils are most highly enriched in Pb, followed by Cr, Cu, and Zn. Furthermore, they are relatively poor in Hg, Cd, and As. It is also shown that the heavy metals in all kinds of soils have the same geochemical characteristics in the gold belt. As for the crops (such as corn and wheat) in the gold belt, Zn and Cu are the most abundant elements, followed by Pb and Cr. Meanwhile, Hg, Cd, and As were found to have relatively low concentrations in the crops. The heavy metals in wheat and corn have the same geochemical characteristics in the gold belt in general. Compared to the aeolian loess soils and the crops therein, heavy metals are more enriched in diluvial and alluvial soils and the crops therein. As shown by relevant studies, the Hg, Pb, Cd, Cu, and Zn pollution are mainly caused by mining activities. Corn and wheat in the gold belt have a high tendency of risk exposure to heavy metal pollution since they are mostly affected by mining activities and feature high background values of heavy metal concentrations. Furthermore, wheat is more liable to be enriched in heavy metals than corn is grown in all types of soils. The Hg pollution in soils leads to Hg accumulation, increasing the risk of Hg uptake in crops, and further affecting human health. This study will provide a scientific basis for the control and management of heavy metals in farmland soils of mining areas. 相似文献