以山西省为研究对象,基于中国土壤流失方程(Chinese Soil Loss Equation)、遥感和GIS空间分析技术,通过合理选择CSLE中各土壤侵蚀因子的数据来源和计算方法,依据《土壤侵蚀分类分级标准》对2000—2010年山西省省市县3级行政体系的土壤...以山西省为研究对象,基于中国土壤流失方程(Chinese Soil Loss Equation)、遥感和GIS空间分析技术,通过合理选择CSLE中各土壤侵蚀因子的数据来源和计算方法,依据《土壤侵蚀分类分级标准》对2000—2010年山西省省市县3级行政体系的土壤侵蚀风险情况进行了分析,并运用地理加权回归分析方法,计算了土壤侵蚀模型中各因子对侵蚀量的贡献率。结果表明:(1)山西省年均土壤侵蚀总量达3.58×108t,平均土壤侵蚀模数为2 287t/(km^2·a)。若以土壤侵蚀强度高于微度为侵蚀风险地区,则山西省存在水土流失风险的地区约占全省面积的48%;(2)11个地级市中,轻度侵蚀城市依次为长治、晋中、晋城、太原、大同、运城和朔州,中度侵蚀依次为吕梁、临汾、阳泉和忻州。106个县级行政区中,微度侵蚀的县有14个,轻度侵蚀的县有61个,中度侵蚀的县有27个,强度侵蚀的县有4个;(3)地形因子对水力侵蚀引起的土壤侵蚀模数具有最高的贡献率,而因子取得最值的位置并不与贡献率最值的位置相一致。展开更多
Soil erosion has become a significant environmental problem that threatens eco- systems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and...Soil erosion has become a significant environmental problem that threatens eco- systems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and conservation priority level in the middle reaches of the Yellow River Basin were identified from 1978 to 2010. This study employed a multi-criteria evaluation method integrated with GIS and multi-source remote sensing data including land use, slope gradient and vegetation fractional coverage （VFC）. The erosion status in the study region improved from 1978 to 2010; areas of extremely severe, more severe, and severe soil erosion decreased from 0.05%, 0.94%, and 11.25% in 1978 to 0.04%, 0.81%, and 10.28% in 1998, respectively, and to 0.03%, 0.59%, and 6.87% in 2010, respectively. Compared to the period from 1978 to 1998, the area classed as improvement grade erosion increased by about 47,210.18 km2 from 1998 to 2010, while the area classed as deterioration grade ero- sion decreased by about 17,738.29 km2. Almost all severe erosion regions fall in the 1st and 2rid conservation priority levels, which areas accounted for 3.86% and 1.11% of the study area in the two periods, respectively. This study identified regions where soil erosion control is required and the results provide a reference for policymakers to implement soil conservation measures in the future.展开更多
Soil erosion is a major threat to sustainable agriculture. Evaluating regional erosion risk is increasingly needed by national and in-ternational environmental agencies. This study elaborates a model (using spatial pr...Soil erosion is a major threat to sustainable agriculture. Evaluating regional erosion risk is increasingly needed by national and in-ternational environmental agencies. This study elaborates a model (using spatial principal component analysis [SPCA]) method for the evaluation of soil erosion risk in a representative area of dry-hot valley (Yuanmou County) at a scale of 1:100,000 using a spatial database and GIS. The model contains seven factors: elevation, slope, annual precipitation, land use, vegetation, soil, and population density. The evaluation results show that five grades of soil erosion risk: very low, low, medium, high, and very high. These are divided in the study area, and a soil erosion risk evaluation map is created. The model may be applicable to other areas of China because it utilizes spatial data that are generally available.展开更多
Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that sa...Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that satellite data during growing season are randomly selected and used in soil erosion risk assessment. However, the effectiveness of vegetation in protecting the soil is quite different even if it is the same growing season since vegetation covers change as they grow. This article aims to provide a method of choosing optimal vegetation cover for studying soil erosion risk using remote sensing, that is, the vegetation cover in the most appropriate temporal period. Based on the temporal relationship of the two most active impact factors, rainfall and vegetation, an index of RV is developed and used to indicate the relative erosion risk during the year. The results show that annual variation of rainfall is significant, and vegetation is relatively stable, resulting in their matching relationship is different in each year. The correlation coefficient reaches 0.89 between RV and real sediment transport during the period when rainfall can cause soil erosion. In other words, RV is a good indicator of soil erosion. Therefore, there is a good correlation between RV maximum and the optimal vegetation cover, which can help facilitate erosion research in the future, showing good potential for successful application in other places.展开更多
文摘以山西省为研究对象,基于中国土壤流失方程(Chinese Soil Loss Equation)、遥感和GIS空间分析技术,通过合理选择CSLE中各土壤侵蚀因子的数据来源和计算方法,依据《土壤侵蚀分类分级标准》对2000—2010年山西省省市县3级行政体系的土壤侵蚀风险情况进行了分析,并运用地理加权回归分析方法,计算了土壤侵蚀模型中各因子对侵蚀量的贡献率。结果表明:(1)山西省年均土壤侵蚀总量达3.58×108t,平均土壤侵蚀模数为2 287t/(km^2·a)。若以土壤侵蚀强度高于微度为侵蚀风险地区,则山西省存在水土流失风险的地区约占全省面积的48%;(2)11个地级市中,轻度侵蚀城市依次为长治、晋中、晋城、太原、大同、运城和朔州,中度侵蚀依次为吕梁、临汾、阳泉和忻州。106个县级行政区中,微度侵蚀的县有14个,轻度侵蚀的县有61个,中度侵蚀的县有27个,强度侵蚀的县有4个;(3)地形因子对水力侵蚀引起的土壤侵蚀模数具有最高的贡献率,而因子取得最值的位置并不与贡献率最值的位置相一致。
基金National Natural Science Foundation of China,No.41701517National Key Project for R&D,No.2016YFC0402403,No.2016YFC0402409
文摘Soil erosion has become a significant environmental problem that threatens eco- systems globally. The risks posed by soil erosion, the trends in the spatial distribution in soil erosion, and the status, intensity, and conservation priority level in the middle reaches of the Yellow River Basin were identified from 1978 to 2010. This study employed a multi-criteria evaluation method integrated with GIS and multi-source remote sensing data including land use, slope gradient and vegetation fractional coverage （VFC）. The erosion status in the study region improved from 1978 to 2010; areas of extremely severe, more severe, and severe soil erosion decreased from 0.05%, 0.94%, and 11.25% in 1978 to 0.04%, 0.81%, and 10.28% in 1998, respectively, and to 0.03%, 0.59%, and 6.87% in 2010, respectively. Compared to the period from 1978 to 1998, the area classed as improvement grade erosion increased by about 47,210.18 km2 from 1998 to 2010, while the area classed as deterioration grade ero- sion decreased by about 17,738.29 km2. Almost all severe erosion regions fall in the 1st and 2rid conservation priority levels, which areas accounted for 3.86% and 1.11% of the study area in the two periods, respectively. This study identified regions where soil erosion control is required and the results provide a reference for policymakers to implement soil conservation measures in the future.
基金supported and funded by National Basic Research Program of China (2007CB407206)the projects of "Western Light of China" sponsored by Chinese Academy of Sciences (2005, C20609090)
文摘Soil erosion is a major threat to sustainable agriculture. Evaluating regional erosion risk is increasingly needed by national and in-ternational environmental agencies. This study elaborates a model (using spatial principal component analysis [SPCA]) method for the evaluation of soil erosion risk in a representative area of dry-hot valley (Yuanmou County) at a scale of 1:100,000 using a spatial database and GIS. The model contains seven factors: elevation, slope, annual precipitation, land use, vegetation, soil, and population density. The evaluation results show that five grades of soil erosion risk: very low, low, medium, high, and very high. These are divided in the study area, and a soil erosion risk evaluation map is created. The model may be applicable to other areas of China because it utilizes spatial data that are generally available.
文摘Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that satellite data during growing season are randomly selected and used in soil erosion risk assessment. However, the effectiveness of vegetation in protecting the soil is quite different even if it is the same growing season since vegetation covers change as they grow. This article aims to provide a method of choosing optimal vegetation cover for studying soil erosion risk using remote sensing, that is, the vegetation cover in the most appropriate temporal period. Based on the temporal relationship of the two most active impact factors, rainfall and vegetation, an index of RV is developed and used to indicate the relative erosion risk during the year. The results show that annual variation of rainfall is significant, and vegetation is relatively stable, resulting in their matching relationship is different in each year. The correlation coefficient reaches 0.89 between RV and real sediment transport during the period when rainfall can cause soil erosion. In other words, RV is a good indicator of soil erosion. Therefore, there is a good correlation between RV maximum and the optimal vegetation cover, which can help facilitate erosion research in the future, showing good potential for successful application in other places.
