Patterns and correlates of landscape change in northern Thailand.

摘要

Land use and land cover change are the result of a series of complex interactions between biophysical and socio-economic variables. The major driving forces in land use and land cover change include population growth and movement, technological capacity, economic development, political structures, culture, and the environment. Thailand is a developing country with enormous natural resources and great potential for development that, in the past two decades, has experienced major land cover change. The objective of this study is to measure the relationships between change in the social and economic conditions in the Mae Taeng watershed with concomitant changes in land cover of the region. The spatial units of analysis are sub-sub-district (village) administrative levels, using the national census and economic data. The temporal unit of landscape change analysis is an 8-year interval from 1989 to 1997. A post-classification comparison change detection technique was used to measure land cover changes in the watershed with Landsat Thematic Mapper (TM) data. The study area comprises approximately 1,954 km2 in rural northern Thailand. I used a geographic information system (GIS) to measure the environmental and socio-economic characteristics of the watershed. Historical aerial photography and 1:50,000-scale land-use maps were used as reference data. A change detection error matrix was used to quantitatively assess the accuracy of the change analysis. The overall accuracy of the post-classification comparison change-detection technique was 74% with a K_hat value of 0.73. I found that the patterns and rates of land cover change are a function of the biophysical characteristics of the region, especially slope and elevation; and the social and economic profiles of villages within the watershed, especially education levels. The study of land cover dynamics in the Mae Taeng watershed will serve as a model for other parts of Thailand and will be of significant value to understanding the determinants of landscape change in rural tropical environments.