The Pearl River Delta Economic Zone is one of the most developed regions in China. It has been undergoing a rapid urbanization since the reformation and opening of China in 1978. This process plays a significant impact on the urban environment, particularly river water quality. The main goal of this present study is to assess the impact of urban activities especially urbanization on river water quality for the study area. Some Landsat TM images from 2000 were used to map the areas for different pollution levels of urban river sections for the study area. In addition, an improved equalized synthetic pollution index method was utilized to assess the field analytical results. The results indicate that there is a positive correlation between the rapidity of urbanization and the pollution levels of urban river water. Compared to the rural river water, urban river water was polluted more seriously. During the urban development process, urbanization and urban activities had a significant negative impact on the river water quality.
The Pearl River Delta Economic Zone is the most dynamic economic area in South China. One of the major problems in the region is the sustainable utilization of the water resources. On the basis of analysis of the water environment status and pollution sources, it is suggested that domestic sewage is the primary cause of pollution. Two new concepts "degradation coefficient" and "degradation volume" of water resources, due to pollution, which may be used to assess macroscopically the carrying capacity of the water resources and sustainability of the water environment, are proposed by the authors. The results calculated indicate that the volumes of degraded water resources will be up to 204, 352, and 537 million m3 in 2002, 2010, and 2020. It is suggested that water for daily consumption and domestic sewage must be controlled more effectively and there should be cross-regional coordination in tackling problems of water environment.
Social vulnerability assessment of natural hazards aims to identify vulnerable populations and provide decision makers with scientific basis for their disaster prevention and mitigation decisions. A new method based on remote sensing is presented here to establish a model of social vulnerability for county-scale regions that lack of relative data. To calculate population density, which is the most important indicator in social vulnerability assessment, first, a statistical model is established to estimate the population on village level. Then a new concept defined as ''population density based on land use'' is created to replace the arithmetic population density. The former has taken the dynamic human distribution related to land use into account; thus, it can map the population distribution more realistically. The other two indicators are age structure and distance to hospital. The application of this method to the Luogang District of Guangzhou, South China demonstrated its capability of providing high spatial resolution and reasonable social vulnerability for social vulnerability assessment of natural hazards.
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