| 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.
|
PDF Full Text Request