基于遥感与GIS技术的土地利用/覆盖变换分析及土壤侵蚀风险评价的研究—从生态环境角度
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摘要
土地利用/土地覆盖(LUCC)变化在区域社会经济发展和全球环境变化中发挥着至关重要的作用。在脆弱的生态系统占主导地位的条件下,土地覆盖变化常常由于过多的人为干扰对环境造成重大的影响。因此,LULC变化分析对于了解其自然特性、程度和位置、质量、以及生产率、适宜性和各种土地利用/土地覆盖指标的局限性是必不可少的。本研究采用遥感(RS)和地理信息系统(GIS)分别评估两个不同的地区——中国丹江口和孟加拉博格拉过去14年(1991-2005)和16年(1988-2004)LULC的空间格局及其变化。另一方面,土壤侵蚀是影响人类赖以生存的土壤、土地和水资源质量的最严重的环境问题。土壤侵蚀危害图是研究侵蚀易发地区的一个重要工具,因为他们能解释并显示危害及可能受到不同程度影响的地区的位置分布。因此,它对规划者和决策者启动补救措施以及对优先区域选择是非常有用的。在本研究中,综合运用土壤侵蚀危害和风险图,遥感、地理信息系统、多标准决策分析(MCDA)和统计方法,解释了丹江口地区目前和未来侵蚀灾害有效管理预测的方法和侵蚀灾害管理全面战略。另外,本研究还试图讨论空间多标准评价(SMCE)的运用和适用于本研究区域生态环境的定量预测方法。
我们在选择的两个研究区域采用Landsat TM and IRS-P6 LISSⅢ遥感图像来分析土地利用/土地覆盖的整体变化。为了对不同土地利用/土地覆盖的卫星影像进行分类,采用了模糊神经网络监督分类的技术。然后又采用基于地理信息系统覆盖的分类比较技术获取土地利用/土地覆盖变化。研究中我们主要关注的是土地利用/土地覆盖的动态变化,包括时空变化的统计、土地利用/土地覆盖的趋势/输移,以及他们与选定的物理环境变量如土壤、坡度和海拔之间的关系。
为了评价土壤侵蚀危害,本研究以遥感和地理信息系统为主要工具基于Z-score和空间主成分分析(SPCA)构建了两个数学模型。利用上述模型,综合土壤侵蚀的危险指数(SEHI)进行土壤侵蚀危害的栅格分析。通过使用这两个模型,我们选定了9个显著影响土壤侵蚀的因素。影响土壤水侵蚀的因素有土壤可蚀性因子,坡度,土层厚度,降雨量,海拔,植被,休耕地,人口密度和现存的土壤侵蚀强度。遥感,层次分析法(AHP)和地理信息系统技术以及空间模型被用来选出有空间性的影响因素。通过层次分析法(AHP)来规范所有因素和确定因素权重。由于已使用Z-score和SPCA对选定因素进行规范化,接着运用综合土地和水文信息系统(ILWIS)软件和准备好9个独立层次(Z型分数和PCA)。然后,每个层次通过加权线性组合同他们的因素权重结合,得到每个像素的综合土壤侵蚀的危险指数。为了对不相关联的土壤侵蚀危险指数图进行分类使土壤侵蚀危害表现相当的分区性,利用相同距离集中原则划分为4个等级:非常高,高,中等,低。此外,这项研究还试图找出基于土壤流失危害和现有的土壤侵蚀程度的土壤侵蚀风险评估方法,这种方法使用风险概率来识别地区的实际风险和潜在风险。
此外,本文讨论了在生态环境评估领域中空间多重标准评估(SMCE)的应用,并设计了一个适用于确定中国丹江口生态环境状况的定量方法。使用SMCE方法结合专家知识,计算综合的生态环境状况指数(EECI),然后将EECI分为五个生态环境状态级别:差、较差、一般、好、较好。在此过程中,选用一套与生态环境的可持续标准同等重要的空间标准(15个标准)。应用RS和GIS综合技术和模型为SMCE方法生成必要的空间因子。用排序法和预期值法将所有因素标准化,另一方面,应用层次分析法(AHP)计算因素权重。支持SMCE的较新软件工具促进了整个过程的运行。
土地利用/土地覆盖变化分析表明,两个选定区域的土地利用/土地覆盖在研究期间发生了显著的变化,两个区域不同的景观、平原和山地地形的研究结果表明,尽管地表具有不同的地形和土地利用/土地覆盖类型,但土地利用/土地覆盖一直在变化。基于土地利用/土地覆盖的动态变化,结果还表明,土地利用/土地覆盖变化与物理特性、土壤、坡度和海拔关系密切。土地利用/土地覆盖变化和环境物理特性之间的关系,以及土地利用/土地覆盖变化的趋势表明研究期间发生的变化主要受人为干扰,这可能也是该地区土壤和环境退化的原因。因此,我们应该更多地关注这些地区,保护退化的土壤,尤其加强对生态环境可持续性的发展。
土壤侵蚀灾害性分析结果显示,总体来说丹江口县的土壤侵蚀总体比较缓和,在本研究中通过模拟实验(运用Z-score和空间组成成分分析)得以确定热点地区(很高的危险性)的侵蚀,需要紧急干预。风险评估进一步表明,该地区潜在的危险比实际存在的风险更高,实际和潜在的风险相对较高的是中等海拔的地区,对这些地区的保护应优先考虑。通过采取适当的管理措施可降低土壤侵蚀的危险性。因此,通过这项研究,提出全面的侵蚀灾害管理战略能够有效处理该地区目前和未来的侵蚀灾害。尽管如此,当利用RS和GIS模拟自然资源,环境和生态系统时,有必要验证建立模型每一个步骤的。当研究领域比较大时,对步骤的验证比较困难。因此,需要对灾害图(由采用Z-score的联合方法获得)和生物物理参数(植被,坡度,海拔和降雨)进行带有相关系数的回归分析,这一步骤决定了结果的正确性和有效性。预计结果与总体生态观(假设)以及使用模型表示的侵蚀危害图的有效性密切相关。
此外,对生态环境状况的分析表明,该地区总的生态环境状态处于中等(平均)水平并且存在明显的垂直带分布。区域生态环境较差和差的状况表明该地区这些部分的生态环境质量不容乐观。本研究还研究了人类活动和地区质量。同时,考虑到生态环境状况的地域特点、生态恢复的优先和实际需要,植被条件、土壤侵蚀、地形、气候和土壤条件有重要影响,按此将研究地区生态环境分为四个主要区域,这四个区域可能作为制定生态恢复、重建和保护决策的基础。因此,本研究中使用SMCE结合专家知识为解决地区生态环境状况评价中的复杂决策问题提供了一个有效的方法。
Land use/land cover (LULC) change plays a pivotal role in regional socio-economic development and global environment changes. In environment, where fragile ecosystems are dominant, the land cover change often reflects the most significant impact on the environment due to excessive human activities. So, LULC change analysis is essential to know the natural characteristics, extent and location, its quality, productivity, suitability and limitations of various land uses/covers. Therefore, to assess the spatial pattern of LULC and their changes using remote sensing (RS) and geographical information system (GIS) were describe in this study in two distinct areas, the Danjiangkou county of China and Bogra district of Bangladesh, over the last 14 years (1991-2005) and 16 years (1988-2004), respectively. On the other hand, soil erosion is the most serious environmental problem affecting the quality of soil, land, and water resources upon which humans depend for their sustenance. Soil erosion hazard maps can be an essential tool in erosion prone areas as they explain and display the distribution of hazards and areas likely to be affected to different magnitudes. Therefore, it is very useful to planners and policy makers initiating remedial measures and for prioritizing areas. Thus, soil erosion hazard and risk map applying integrated use of RS, GIS, multi-criteria decision analysis (MCDA) and statistical approaches was also explained in this study in Danjiangkou county, from which comprehensive erosion hazard management strategies were anticipated for the efficient management of present and future erosion disaster in the area. Moreover, this study was also an attempt to discuss an application of spatial multiple criteria evaluation (SMCE) and projected a quantitative method applicable to the identification of eco-environmental condition of the study area.
Landsat TM and IRS-P6 LISS III images were used to analyze the overall changes of different LULC types in the two selected areas. To classify the satellite images for LULC, a fuzzy ARTMAP neural network supervised classification technique was performed. A post classification comparison technique with GIS overlay was followed to derive the LULC changes. In this study we focused the LULC dynamics, including statistics of spatio-temporal changes, trajectories/transformations of LULC and their relations to the selected physical environmental variables such as soil, slopes and altitude.
For soil erosion hazard assessment, remote sensing (RS) and geographical information system (GIS) technologies were adopted and two numerical models were developed using Z-score and spatial principal component analysis (SPCA) along with remote sensing and GIS. Using these models, the integrated soil erosion hazard index (SEHI) was computed to carry out a raster based analysis of soil erosion hazard. For the models, nine factors which have notable impact on soil erosion were selected. The relevant factors for soil erosion by water were soil erodibility, slope, soil depth, rainfall, elevation, vegetation, fallow land, population density and presence of existing soil erosion. To generate the selected factors spatially, remote sensing, analytical hierarchy process (AHP) and GIS techniques along with spatial models were applied. To standardize all of the factors and establish the factor weights, the AHP method was adopted. For Z-score and SPCA analysis with selected standardized factors, the Integrated Land and Water Information System (ILWIS) software was used and nine individual layers (Z-scores and PCA) were prepared. Afterwards, the layers were integrated with their factor weights by means of a weighted linear combination (WLC) to derive SEHI value for each pixel. To classify the discrete SEHI map to represent a meaningful regionalization of soil erosion hazard, the equal distance cluster principle was used and graded into four levels of hazard; very high, high, moderate and low. Moreover, this study was also an attempt to find out the soil erosion risk based on soil erosion hazard and existing soil erosion, which identified the areas under actual risk and potential risk with probability of risk.'
Besides, an application of spatial multiple criteria evaluation (SMCE) in eco-environmental condition assessment was discussed and projected a quantitative method applicable to the identification of eco-environmental condition of Danjiangkou county, China. Using SMCE approach with expert's knowledge, in the method an integrated eco-environmental condition index (EECI) was computed and then EECI was classified into five levels of eco-environment condition; worse, poor, average, good and better. During the process, a set of spatial criteria was selected (15 criterions) together with the degree of importance of the criteria in sustainability of the eco-environment. To generate the necessary factors spatially for the SMCE approach, remote sensing and GIS integrated techniques and models were applied. To standardize all of the factors, the rank order (OR) along with expected value method was used and on the other hand, for factors weights, analytical hierarchy process (AHP) was applied. The entire process was facilitated by a comparatively new software tool that supports SMCE.
LULC change analysis revealed that the LULC of the two selected areas were changed dramatically during the study periods and results form two different landscapes, flat and hill terrain indicated that the LULC is changing even though different topography and LULC types are found over the land surface. Considering the LULC dynamics, the results also showed that LULC changes were related particularly to the pattern of the physical attributes; soil, slope and elevation. The relations between LULC change and physical properties of the environment, and the trajectories of the LULC depicted that the changes which took place during the study periods were mainly human induced, which might be the cause of soil and environmental degradation in the areas. Therefore, more attention should be paid in these regions to protect the degradation of soil, particularly for the eco-environmental sustainability.
Soil erosion hazard analysis depicted that in general, a moderate hazardous condition of soil erosion was found in Danjiangkou county and the modelling exercise (Z-score and SPCA) in this study made it possible to identify hot-spot areas of erosion (very high and high hazard) that require urgent intervention. Risk assessment further showed that the areas under potential risk were more extensive than that of the areas under actual risk, and both actual and potential risks were comparatively high at the mid level elevation of the area. In these areas the work for conservation and protection should be carried out according to a priority basis. The soil erosion hazard can be reduced by taking appropriate management strategies for the conservation and protection of soil erosion. Therefore, based on this study, comprehensive erosion hazard management strategies were proposed for the efficient management of present and future erosion disaster in the area. However, when natural resources, environmental and ecological systems are modelled and mapped with the aid of GIS and remotely sensed data, there is a need for validation step for the developed model. Steps for such validation are particularly difficult when the size of the study area is comparatively large. Hence, regression analysis with correlation coefficient was performed between the hazard map (obtained by integrated method with Z-score) and some selected biophysical parameters (vegetation, slope, elevation and rainfall) to determine the effectiveness and validation of the result. The predicted results are related to the general ecological perception (hypothesis) and denote the validity of the erosion hazard map using the model described.
Furthermore, the analysis of eco-environmental condition showed that the overall eco-environmental condition of the area was at moderate (average) level and presented apparent vertical-belt distribution. Area under worse and poor conditions of eco-environment indicated the eco-environmental quality was very serious in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate and soils conditions had serious influence that caused the eco-environment quality of the area. Moreover, considering the regional characteristics of eco-environmental condition and priority and practical needs for eco-recovery, the study area was regionalized into four priority areas which may serve as a base for decision making for the recovery, rebuilding and protection of the eco-environment. Therefore, the application of SMCE combined with expert's knowledge, this study has provided an effective methodology to solve the complex decisional problem for the assessment of eco-environmental condition of the area.
我们在选择的两个研究区域采用Landsat TM and IRS-P6 LISSⅢ遥感图像来分析土地利用/土地覆盖的整体变化。为了对不同土地利用/土地覆盖的卫星影像进行分类,采用了模糊神经网络监督分类的技术。然后又采用基于地理信息系统覆盖的分类比较技术获取土地利用/土地覆盖变化。研究中我们主要关注的是土地利用/土地覆盖的动态变化,包括时空变化的统计、土地利用/土地覆盖的趋势/输移,以及他们与选定的物理环境变量如土壤、坡度和海拔之间的关系。
为了评价土壤侵蚀危害,本研究以遥感和地理信息系统为主要工具基于Z-score和空间主成分分析(SPCA)构建了两个数学模型。利用上述模型,综合土壤侵蚀的危险指数(SEHI)进行土壤侵蚀危害的栅格分析。通过使用这两个模型,我们选定了9个显著影响土壤侵蚀的因素。影响土壤水侵蚀的因素有土壤可蚀性因子,坡度,土层厚度,降雨量,海拔,植被,休耕地,人口密度和现存的土壤侵蚀强度。遥感,层次分析法(AHP)和地理信息系统技术以及空间模型被用来选出有空间性的影响因素。通过层次分析法(AHP)来规范所有因素和确定因素权重。由于已使用Z-score和SPCA对选定因素进行规范化,接着运用综合土地和水文信息系统(ILWIS)软件和准备好9个独立层次(Z型分数和PCA)。然后,每个层次通过加权线性组合同他们的因素权重结合,得到每个像素的综合土壤侵蚀的危险指数。为了对不相关联的土壤侵蚀危险指数图进行分类使土壤侵蚀危害表现相当的分区性,利用相同距离集中原则划分为4个等级:非常高,高,中等,低。此外,这项研究还试图找出基于土壤流失危害和现有的土壤侵蚀程度的土壤侵蚀风险评估方法,这种方法使用风险概率来识别地区的实际风险和潜在风险。
此外,本文讨论了在生态环境评估领域中空间多重标准评估(SMCE)的应用,并设计了一个适用于确定中国丹江口生态环境状况的定量方法。使用SMCE方法结合专家知识,计算综合的生态环境状况指数(EECI),然后将EECI分为五个生态环境状态级别:差、较差、一般、好、较好。在此过程中,选用一套与生态环境的可持续标准同等重要的空间标准(15个标准)。应用RS和GIS综合技术和模型为SMCE方法生成必要的空间因子。用排序法和预期值法将所有因素标准化,另一方面,应用层次分析法(AHP)计算因素权重。支持SMCE的较新软件工具促进了整个过程的运行。
土地利用/土地覆盖变化分析表明,两个选定区域的土地利用/土地覆盖在研究期间发生了显著的变化,两个区域不同的景观、平原和山地地形的研究结果表明,尽管地表具有不同的地形和土地利用/土地覆盖类型,但土地利用/土地覆盖一直在变化。基于土地利用/土地覆盖的动态变化,结果还表明,土地利用/土地覆盖变化与物理特性、土壤、坡度和海拔关系密切。土地利用/土地覆盖变化和环境物理特性之间的关系,以及土地利用/土地覆盖变化的趋势表明研究期间发生的变化主要受人为干扰,这可能也是该地区土壤和环境退化的原因。因此,我们应该更多地关注这些地区,保护退化的土壤,尤其加强对生态环境可持续性的发展。
土壤侵蚀灾害性分析结果显示,总体来说丹江口县的土壤侵蚀总体比较缓和,在本研究中通过模拟实验(运用Z-score和空间组成成分分析)得以确定热点地区(很高的危险性)的侵蚀,需要紧急干预。风险评估进一步表明,该地区潜在的危险比实际存在的风险更高,实际和潜在的风险相对较高的是中等海拔的地区,对这些地区的保护应优先考虑。通过采取适当的管理措施可降低土壤侵蚀的危险性。因此,通过这项研究,提出全面的侵蚀灾害管理战略能够有效处理该地区目前和未来的侵蚀灾害。尽管如此,当利用RS和GIS模拟自然资源,环境和生态系统时,有必要验证建立模型每一个步骤的。当研究领域比较大时,对步骤的验证比较困难。因此,需要对灾害图(由采用Z-score的联合方法获得)和生物物理参数(植被,坡度,海拔和降雨)进行带有相关系数的回归分析,这一步骤决定了结果的正确性和有效性。预计结果与总体生态观(假设)以及使用模型表示的侵蚀危害图的有效性密切相关。
此外,对生态环境状况的分析表明,该地区总的生态环境状态处于中等(平均)水平并且存在明显的垂直带分布。区域生态环境较差和差的状况表明该地区这些部分的生态环境质量不容乐观。本研究还研究了人类活动和地区质量。同时,考虑到生态环境状况的地域特点、生态恢复的优先和实际需要,植被条件、土壤侵蚀、地形、气候和土壤条件有重要影响,按此将研究地区生态环境分为四个主要区域,这四个区域可能作为制定生态恢复、重建和保护决策的基础。因此,本研究中使用SMCE结合专家知识为解决地区生态环境状况评价中的复杂决策问题提供了一个有效的方法。
Land use/land cover (LULC) change plays a pivotal role in regional socio-economic development and global environment changes. In environment, where fragile ecosystems are dominant, the land cover change often reflects the most significant impact on the environment due to excessive human activities. So, LULC change analysis is essential to know the natural characteristics, extent and location, its quality, productivity, suitability and limitations of various land uses/covers. Therefore, to assess the spatial pattern of LULC and their changes using remote sensing (RS) and geographical information system (GIS) were describe in this study in two distinct areas, the Danjiangkou county of China and Bogra district of Bangladesh, over the last 14 years (1991-2005) and 16 years (1988-2004), respectively. On the other hand, soil erosion is the most serious environmental problem affecting the quality of soil, land, and water resources upon which humans depend for their sustenance. Soil erosion hazard maps can be an essential tool in erosion prone areas as they explain and display the distribution of hazards and areas likely to be affected to different magnitudes. Therefore, it is very useful to planners and policy makers initiating remedial measures and for prioritizing areas. Thus, soil erosion hazard and risk map applying integrated use of RS, GIS, multi-criteria decision analysis (MCDA) and statistical approaches was also explained in this study in Danjiangkou county, from which comprehensive erosion hazard management strategies were anticipated for the efficient management of present and future erosion disaster in the area. Moreover, this study was also an attempt to discuss an application of spatial multiple criteria evaluation (SMCE) and projected a quantitative method applicable to the identification of eco-environmental condition of the study area.
Landsat TM and IRS-P6 LISS III images were used to analyze the overall changes of different LULC types in the two selected areas. To classify the satellite images for LULC, a fuzzy ARTMAP neural network supervised classification technique was performed. A post classification comparison technique with GIS overlay was followed to derive the LULC changes. In this study we focused the LULC dynamics, including statistics of spatio-temporal changes, trajectories/transformations of LULC and their relations to the selected physical environmental variables such as soil, slopes and altitude.
For soil erosion hazard assessment, remote sensing (RS) and geographical information system (GIS) technologies were adopted and two numerical models were developed using Z-score and spatial principal component analysis (SPCA) along with remote sensing and GIS. Using these models, the integrated soil erosion hazard index (SEHI) was computed to carry out a raster based analysis of soil erosion hazard. For the models, nine factors which have notable impact on soil erosion were selected. The relevant factors for soil erosion by water were soil erodibility, slope, soil depth, rainfall, elevation, vegetation, fallow land, population density and presence of existing soil erosion. To generate the selected factors spatially, remote sensing, analytical hierarchy process (AHP) and GIS techniques along with spatial models were applied. To standardize all of the factors and establish the factor weights, the AHP method was adopted. For Z-score and SPCA analysis with selected standardized factors, the Integrated Land and Water Information System (ILWIS) software was used and nine individual layers (Z-scores and PCA) were prepared. Afterwards, the layers were integrated with their factor weights by means of a weighted linear combination (WLC) to derive SEHI value for each pixel. To classify the discrete SEHI map to represent a meaningful regionalization of soil erosion hazard, the equal distance cluster principle was used and graded into four levels of hazard; very high, high, moderate and low. Moreover, this study was also an attempt to find out the soil erosion risk based on soil erosion hazard and existing soil erosion, which identified the areas under actual risk and potential risk with probability of risk.'
Besides, an application of spatial multiple criteria evaluation (SMCE) in eco-environmental condition assessment was discussed and projected a quantitative method applicable to the identification of eco-environmental condition of Danjiangkou county, China. Using SMCE approach with expert's knowledge, in the method an integrated eco-environmental condition index (EECI) was computed and then EECI was classified into five levels of eco-environment condition; worse, poor, average, good and better. During the process, a set of spatial criteria was selected (15 criterions) together with the degree of importance of the criteria in sustainability of the eco-environment. To generate the necessary factors spatially for the SMCE approach, remote sensing and GIS integrated techniques and models were applied. To standardize all of the factors, the rank order (OR) along with expected value method was used and on the other hand, for factors weights, analytical hierarchy process (AHP) was applied. The entire process was facilitated by a comparatively new software tool that supports SMCE.
LULC change analysis revealed that the LULC of the two selected areas were changed dramatically during the study periods and results form two different landscapes, flat and hill terrain indicated that the LULC is changing even though different topography and LULC types are found over the land surface. Considering the LULC dynamics, the results also showed that LULC changes were related particularly to the pattern of the physical attributes; soil, slope and elevation. The relations between LULC change and physical properties of the environment, and the trajectories of the LULC depicted that the changes which took place during the study periods were mainly human induced, which might be the cause of soil and environmental degradation in the areas. Therefore, more attention should be paid in these regions to protect the degradation of soil, particularly for the eco-environmental sustainability.
Soil erosion hazard analysis depicted that in general, a moderate hazardous condition of soil erosion was found in Danjiangkou county and the modelling exercise (Z-score and SPCA) in this study made it possible to identify hot-spot areas of erosion (very high and high hazard) that require urgent intervention. Risk assessment further showed that the areas under potential risk were more extensive than that of the areas under actual risk, and both actual and potential risks were comparatively high at the mid level elevation of the area. In these areas the work for conservation and protection should be carried out according to a priority basis. The soil erosion hazard can be reduced by taking appropriate management strategies for the conservation and protection of soil erosion. Therefore, based on this study, comprehensive erosion hazard management strategies were proposed for the efficient management of present and future erosion disaster in the area. However, when natural resources, environmental and ecological systems are modelled and mapped with the aid of GIS and remotely sensed data, there is a need for validation step for the developed model. Steps for such validation are particularly difficult when the size of the study area is comparatively large. Hence, regression analysis with correlation coefficient was performed between the hazard map (obtained by integrated method with Z-score) and some selected biophysical parameters (vegetation, slope, elevation and rainfall) to determine the effectiveness and validation of the result. The predicted results are related to the general ecological perception (hypothesis) and denote the validity of the erosion hazard map using the model described.
Furthermore, the analysis of eco-environmental condition showed that the overall eco-environmental condition of the area was at moderate (average) level and presented apparent vertical-belt distribution. Area under worse and poor conditions of eco-environment indicated the eco-environmental quality was very serious in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate and soils conditions had serious influence that caused the eco-environment quality of the area. Moreover, considering the regional characteristics of eco-environmental condition and priority and practical needs for eco-recovery, the study area was regionalized into four priority areas which may serve as a base for decision making for the recovery, rebuilding and protection of the eco-environment. Therefore, the application of SMCE combined with expert's knowledge, this study has provided an effective methodology to solve the complex decisional problem for the assessment of eco-environmental condition of the area.
引文
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