基于RS和GIS的水土流失因子提取与分析——以攀枝花市为例
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摘要
水土流失造成一系列的危害，已成为中国的头号问题。及时准确地将水土流失类型、强度、分布地最新数据提供给各级政府和水土保持主管部门，是制定水土保持规划和决策的基本依据。
近年来，遥感(RS)和地理信息系统(GIS)技术得到了迅速发展并趋向于一体化和实用化。遥感技术为大范围的环境调查和监测提供了时间和空间上连续覆盖的信息源，GIS技术为空间数据的管理和分析提供了有力的工具。
本论文以1988年Landsat-5 TM、1999年Landsat-7 ETM+原始数据和1：25万地形图为主要信息源，通过遥感图像数字处理的方法，提取了对水土流失起主导作用的植被覆盖度、土地利用类型，沟谷密度及土壤成土母质等因子；在矢量化等高线数据的基础上、生成数字高程模型(DEM)，提取地形坡度；各因子经GIS空间分析，依据《土壤侵蚀分类分级标准》，提出了适合研究区的水土流失分级指标，得出研究区水土流失强度等级。通过1988年与1999年对比分析，结果表明水土流失总面积增加1573.87km~2，其中微度流失面积减少1573.87km~2，轻度流失面积增加1080.16km~2，中度流失面积增加298.39km~2，强度流失面积增加133.03km~2，极强度流失面积增加43.84km~2，剧烈流失面积增加了18.45km~2，攀枝花市水土流失呈现恶化现象。
本论文研究表明，利用RS和GIS技术进行水土流失因子提取与分析是切实可行的。本论文在以下方面取得明显进展和认识：
(1)提出了在无法获取年平均侵蚀模数的情况下，可以利用遥感图像数字处理的方法，结合地形数据，提取影响水土流失的主导因子：植被覆盖度、地形坡度、沟谷密度、土地利用类型和土壤成土母质，参考降雨量资料进行水土流失的研究，在技术上是完全可行的。
(2)根据中华人民共和国行业标准《土壤侵蚀分类分级标准》(SL 190一96)，
参考《水土保持技术规范》的有关要求，结合水土流失各因子分级定标，提出了
适合本研究区的植被覆盖度、坡度、沟谷密度和土地利用类型四因子水土流失面
蚀分级指标，得出研究区水土流失强度等级。
(3)针对研究区地理地质环境，利用RS数据和地形图，形成了一套基于RS
和Gls的从数据采集一遥感图像的处理一水土流失因子信息提取一GIS空间分析
一水土流失强度分级定标及分析，较为完整的水土流失因子提取与分析的研究技
术路线、方法体系和工作流程。这套方法体系和技术路线对中国山区水土流失的
调查、动态监测，有一定的参考借鉴价值。
Soil and water loss has resulted in a series of hazards, and it is the most serious environment problem in China. To precisely supply the type, intensity and distribution of soil and water loss in time is the principal basis for soil and water loss preservation, planning and decision-making.
Recent years, the technologies of remote sensing (RS) and geographical information system (GIS) have developed rapidly and trended to be integrated and applied widely. Remote sensing supplies continuous information sources to environment surveying and monitoring in a large region. GIS is a powerful tool to management and analysis spatial data.
In this paper, based on the original data of landsat-5 TM in 1988, landsat-7 ETM+ in 1999 and 1 ' 250000 topographic map as the main information sources, by the method of remote sensing digital image processing, the author has extracted leading factors of soil and water loss, such as vegetation cover, land-use type, gully density, parent materials of soil, and so on. On the basis of raster-to-vector contour line, digital elevation model (DEM) is got, then slope is calculated through DEM. Founding the standard for classification and gradation of soil erosion, by the spatial analysis of GIS, the author has proposed gradation index of soil and water loss of the study area, then gotten strength levels of soil and water loss of Panzhihua city. By comparing analyses between 1988 and 1999, the result are these: the whole area of soil and water loss has increased 1573.87km2, very slight loss area has reduced 1573.87km2, slight loss area has increased 1080.16 km2, moderate loss area has increased 298.39 km2, severe l
oss area has increased 133.03 km2, strongly severe loss area has increased 43.84 km2, violent loss area has increased 18.45 km2, the soil and water loss in Panzhihua city was showing in a worsened situation.
It is feasible for analysis and extraction of soil and water loss factors based on
RS and GIS. The following is the innovation and production in this paper:
(1) Under being unable to obtain average erosion modulus situation, by the method of remote sensing digital image processing to extract leading factors of soil and water loss, such as vegetation cover, land-use type, gully density, parent materials of soil, and extract slope factor by applying topographic data, it is feasible in technology to research soil and water loss.
(2) Founding the sector standard of the People's Republic of China standard for classification and gradation of soil erosion(SL 190-96), referring requirement of soil and water conservation technical specification, combining gradation calibration of soil and water loss factors, the author has proposed surface erosion gradation index of soil and water loss including vegetation cover, slope, gully density and land-use type factors, then gotten strength levels of soil and water loss of Panzhihua city.
(3) Based on the geo-environment of Panzhihua city, the author has established a RS and GIS system from data collection-remote sensing digital image processing-extraction of soil and water loss factors-spatial analysis of GIS-gradation calibration and analysis of soil and water loss intensity, shown out the study technique route, method system and work flow of analysis and extraction of soil and water loss factors, which has reference value for surveying and dynamic monitoring of soil and water loss in the mountain area of China.
近年来，遥感(RS)和地理信息系统(GIS)技术得到了迅速发展并趋向于一体化和实用化。遥感技术为大范围的环境调查和监测提供了时间和空间上连续覆盖的信息源，GIS技术为空间数据的管理和分析提供了有力的工具。
本论文以1988年Landsat-5 TM、1999年Landsat-7 ETM+原始数据和1：25万地形图为主要信息源，通过遥感图像数字处理的方法，提取了对水土流失起主导作用的植被覆盖度、土地利用类型，沟谷密度及土壤成土母质等因子；在矢量化等高线数据的基础上、生成数字高程模型(DEM)，提取地形坡度；各因子经GIS空间分析，依据《土壤侵蚀分类分级标准》，提出了适合研究区的水土流失分级指标，得出研究区水土流失强度等级。通过1988年与1999年对比分析，结果表明水土流失总面积增加1573.87km~2，其中微度流失面积减少1573.87km~2，轻度流失面积增加1080.16km~2，中度流失面积增加298.39km~2，强度流失面积增加133.03km~2，极强度流失面积增加43.84km~2，剧烈流失面积增加了18.45km~2，攀枝花市水土流失呈现恶化现象。
本论文研究表明，利用RS和GIS技术进行水土流失因子提取与分析是切实可行的。本论文在以下方面取得明显进展和认识：
(1)提出了在无法获取年平均侵蚀模数的情况下，可以利用遥感图像数字处理的方法，结合地形数据，提取影响水土流失的主导因子：植被覆盖度、地形坡度、沟谷密度、土地利用类型和土壤成土母质，参考降雨量资料进行水土流失的研究，在技术上是完全可行的。
(2)根据中华人民共和国行业标准《土壤侵蚀分类分级标准》(SL 190一96)，
参考《水土保持技术规范》的有关要求，结合水土流失各因子分级定标，提出了
适合本研究区的植被覆盖度、坡度、沟谷密度和土地利用类型四因子水土流失面
蚀分级指标，得出研究区水土流失强度等级。
(3)针对研究区地理地质环境，利用RS数据和地形图，形成了一套基于RS
和Gls的从数据采集一遥感图像的处理一水土流失因子信息提取一GIS空间分析
一水土流失强度分级定标及分析，较为完整的水土流失因子提取与分析的研究技
术路线、方法体系和工作流程。这套方法体系和技术路线对中国山区水土流失的
调查、动态监测，有一定的参考借鉴价值。
Soil and water loss has resulted in a series of hazards, and it is the most serious environment problem in China. To precisely supply the type, intensity and distribution of soil and water loss in time is the principal basis for soil and water loss preservation, planning and decision-making.
Recent years, the technologies of remote sensing (RS) and geographical information system (GIS) have developed rapidly and trended to be integrated and applied widely. Remote sensing supplies continuous information sources to environment surveying and monitoring in a large region. GIS is a powerful tool to management and analysis spatial data.
In this paper, based on the original data of landsat-5 TM in 1988, landsat-7 ETM+ in 1999 and 1 ' 250000 topographic map as the main information sources, by the method of remote sensing digital image processing, the author has extracted leading factors of soil and water loss, such as vegetation cover, land-use type, gully density, parent materials of soil, and so on. On the basis of raster-to-vector contour line, digital elevation model (DEM) is got, then slope is calculated through DEM. Founding the standard for classification and gradation of soil erosion, by the spatial analysis of GIS, the author has proposed gradation index of soil and water loss of the study area, then gotten strength levels of soil and water loss of Panzhihua city. By comparing analyses between 1988 and 1999, the result are these: the whole area of soil and water loss has increased 1573.87km2, very slight loss area has reduced 1573.87km2, slight loss area has increased 1080.16 km2, moderate loss area has increased 298.39 km2, severe l
oss area has increased 133.03 km2, strongly severe loss area has increased 43.84 km2, violent loss area has increased 18.45 km2, the soil and water loss in Panzhihua city was showing in a worsened situation.
It is feasible for analysis and extraction of soil and water loss factors based on
RS and GIS. The following is the innovation and production in this paper:
(1) Under being unable to obtain average erosion modulus situation, by the method of remote sensing digital image processing to extract leading factors of soil and water loss, such as vegetation cover, land-use type, gully density, parent materials of soil, and extract slope factor by applying topographic data, it is feasible in technology to research soil and water loss.
(2) Founding the sector standard of the People's Republic of China standard for classification and gradation of soil erosion(SL 190-96), referring requirement of soil and water conservation technical specification, combining gradation calibration of soil and water loss factors, the author has proposed surface erosion gradation index of soil and water loss including vegetation cover, slope, gully density and land-use type factors, then gotten strength levels of soil and water loss of Panzhihua city.
(3) Based on the geo-environment of Panzhihua city, the author has established a RS and GIS system from data collection-remote sensing digital image processing-extraction of soil and water loss factors-spatial analysis of GIS-gradation calibration and analysis of soil and water loss intensity, shown out the study technique route, method system and work flow of analysis and extraction of soil and water loss factors, which has reference value for surveying and dynamic monitoring of soil and water loss in the mountain area of China.
引文
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[9] Nadeem Hashem. High Spatial Resolution Soil Erosion Modelling Using Remote Sensing and GIS.
[10] M.H.Mohamed Rinos, S. P. Aggarwal, Ranjith Premalal De Silva. Application of Remote Sensing and GIS on soil erosion assessment at Bata River Basin, India.
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[2] 杨勤科等．区域水土流失快速调查研究与实践．水土保持研究(增刊)，2000，7(1)：53-57．
[3] 李锐，杨勤科，赵永安．水土流失动态监测与评价研究现状与问题．中国水土保持，1999(11)：31-33．
[4] 杨胜天．基于非结构性知识发现的土壤侵蚀信息提取方法及其应用研究．博士学位论文，2001．
[5] P.R.Stephen S.Estimating universal soil loss equation factor values with aerial photography. Journal of Soil and Water Conservation, 1985 (5): 293-296.
[6] John C.Panuska, Lan D.Moore, and Larry A, Kramer. Terrain Analysis: Integration into agricultural ninpoint source (AGNPS) polltion model. J. Soil and Water Conservation, 1991 (1): 59-64.
[7] LARRY A. COSTICK. Indexing Current Watershed Conditions Using Remote Sensing and GIS. Sierra Nevada Ecosystem Project: Final report to Congress, vol. Ⅲ: 53-58.
[8] Krishna Pahari, Jean-Pierre Delsol, Shunji Murai. Remote sensing and GIS for sustainable watershed management a study from NEPAL. Paper presented at the 4th International Symposium on High Mountain Remote Sensing Cartography, Karlstad-Kiruna-TromsΦ, 1996 (8): 195-202.
[9] Nadeem Hashem. High Spatial Resolution Soil Erosion Modelling Using Remote Sensing and GIS.
[10] M.H.Mohamed Rinos, S. P. Aggarwal, Ranjith Premalal De Silva. Application of Remote Sensing and GIS on soil erosion assessment at Bata River Basin, India.
[11] Manzul Kumar Hazarika and Kiyoshi Honda.Estimation of soil erosion using Remote Sensing and GIS, its valuation and economic implications on agricultural production. this paper was peer-reviewed for scientific content, 2001 (1): 1090-1093.
[12] 颉耀文，陈怀录，徐克斌．数字遥感影像判读法在土壤侵蚀调查中的应用．兰州大学学报(自然科学版)，2002，38(2)：157-162．
[13] 焦居仁．全国水土流失遥感成果与水保生态建设发展战略．中国水利，2002(3)：11-13．
[14] 刘宝元，史培军．WEEP水蚀预报流域模型．水土保持通报，1988，18(5)：6-12．
[15] 肖寒，欧阳志云，王效科等．GIS支持下的汉南到土壤侵蚀空间分布特征．土壤侵蚀与水土保持学报，1999，5(4)：75-80．
[16] 马超飞，马建文，布和敖斯尔．U S L E模型中植被覆盖因子的遥感数据定量估算．水土保持
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