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An Analysis of Water Environment Factors and an Evaluation of Water Quantity of Liangzi Lake 被引量:2
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作者 Hong Wang Junlan Yao Yanqiang Li 《Journal of Geoscience and Environment Protection》 2016年第7期44-51,共8页
The experiments of single factor evaluation method, principal component analysis and voronoi area weighting factor method on the sample data of Liangzi Lake in October 2012 combined with the national surface water env... The experiments of single factor evaluation method, principal component analysis and voronoi area weighting factor method on the sample data of Liangzi Lake in October 2012 combined with the national surface water environment quality standards can get the map of comprehensive water quality distribution by Kriging interpolation. The analysis shows, the grades of comprehensive water quality gained by three methods are all only class III or class IV, and the quality of water is different from east and west that the water quality of east is better. However, the percent of IV class water is higher in the result of single factor evaluation method means class IV is the main grade of water quality. The result of principal component analysis shows the percent of class Ⅲ water is higher than other classes. The result of voronoi area weighting factor method shows the percent of IV class is higher than other classes. COD<sub>Mn</sub> is the main factor that influences the method of singal factor evaluation and reduces the grade of water quality overall. The effect of single factor is reduced by principal component analysis, and the analysis on water quality is more accurate. The voronoi area weighing factor method reduces the effect of single factor and extends the content, can make a comprehensive evaluation on water quality. 展开更多
关键词 Factor Analysis PCA VORONOI Area Weighting Method Water Quality Assessment
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The impacts of climate change and human activities on grassland productivity in Qinghai Province, China 被引量:16
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作者 Fang YIN Xiangzheng DENG +2 位作者 Qin JIN Yongwei YUAN Chunhong ZHAO 《Frontiers of Earth Science》 SCIE CAS CSCD 2014年第1期93-103,共11页
Qinghai Province, which is the source of three major rivers (i.e., Yangtze River, Yellow River and Lancang River) in East Asia, has experienced severe grassland degradation in past decades. The aim of this work was ... Qinghai Province, which is the source of three major rivers (i.e., Yangtze River, Yellow River and Lancang River) in East Asia, has experienced severe grassland degradation in past decades. The aim of this work was to analyze the impacts of climate change and human activities on grassland ecosystem at different spatial and temporal scales. For this purpose, the regression and residual analysis were used based on the data from remote sensing data and meteorological stations. The results show that the effect of climate change was much greater in the areas exhibiting vigorous vegetation growth. The grassland degradation was strongly correlated with the climate factors in the study area except Haixi Prefecture. Temporal and spatial heterogeneity in the quality of grassland were also detected, which was probably mainly because of the effects of human activities. In the 1980s, human activities and grassland vegetation growth were in equilibrium, which means the influence of human activities was in balance with that of climate change. However, in the 1990s, significant grassland degradation linked to human activities was observed, primarily in the Three-River Headwaters Region. Since the 21st century, this adverse trend continued in the Qinghai Lake area and near the northern provincial boundaries, opposite to what were observed in the eastern part of study. These results are consistent with the currently status of grassland degradation in Qinghai Piovince, which could serve as a basis for the local grassland management and restoration programs. 展开更多
关键词 climate change human activities grassland degradation spatial distribution residual analysis
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A New Conception of Image Texture and Remote Sensing Image Segmentation Based on Markov Random Field 被引量:1
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作者 GONG Yan SHU Ning +2 位作者 LI Jili LIN Liqun LI Xue 《Geo-Spatial Information Science》 2010年第1期16-23,共8页
The texture analysis is often discussed in image processing domain, but most methods are limited within gray-level image or color image, and the present conception of texture is defined mainly based on gray-level imag... The texture analysis is often discussed in image processing domain, but most methods are limited within gray-level image or color image, and the present conception of texture is defined mainly based on gray-level image of single band. One of the essential characters of remote sensing image is multidimensional or even high-dimensional, and the traditional texture conception cannot contain enough information for these. Therefore, it is necessary to pursuit a proper texture definition based on remote sensing images, which is the first discussion in this paper. This paper describes the mapping model of spectral vector in two-dimensional image space using Markov random field (MRF), establishes a texture model of multiband remote sensing image based on MRF, and analyzes the calculations of Gibbs potential energy and Gibbs parameters. Further, this paper also analyzes the limitations of the traditional Gibbs model, prefers a new Gibbs model avoiding estimation of parameters, and presents a new texture segmentation algorithm for hy-perspectral remote sensing image later. 展开更多
关键词 hyperspectral multispectral MRF Gibbs model texture segmentation
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