『Abstract
Land degradation is still a very common problem in the mountains
of Asia because of inappropriate land use practice in steep topography.
Many studies have been carried out to map shifting cultivation
and areas susceptible to soil erosion. Mostly, estimated soil
loss is taken as the basis to classify the level of soil loss
susceptibility of area. Factors that influence soil erosion are:
rainfall erosivity, soil erodibility, slope length and steepness,
crop management and conservation practices. Thus the reliability
of estimated soil loss is based on how accurately the different
factors were estimated or prepared. As each and every small pixel
of our earth surface is different from one area to another, the
manner in which the study area was discretized into smaller homogeneous
sizes and how the most accurate and efficient technique were adopted
to estimate the soil loss are very important. The purpose of this
study is to produce erosion susceptibility maps for an area that
has suffered because of shifting cultivation located in the mountainous
regions of Northern Thailand. For this purpose, an integrated
approach using RS and GIS-based methods is proposed. Data from
the Upper Nam Wa Watershed, a mountainous area of the Northern
Thailand were used. An Earth Resources Data Analysis System (ERDAS)
imagine image processor has been used for the digital analysis
of satellite data and topographical analysis of the contour data
for deriving the land use/land cover and the topographical data
of the watershed, respectively. ARCInfo and ARCView have been
used for carrying out geographical data analysis. The watershed
was discretized into hydrologically, topographically, and geographically
homogeneous grid cells to capture the watershed heterogeneity.
The soil erosion in each cell was calculated using the universal
soil loss equation (USLE) by carefully determining its various
parameters and classifying the watershed into different levels
of soil erosion severity. Results show that during the time of
this study most of the areas under shifting cultivation fell in
the highest severity class of susceptibility.
Keywords: Land degradation; Soil loss mapping; GIS; Remote sensing』
Introduction
Study area
Methodology
Results and discussion
Conclusions
Acknowledgements
References