A GIS-BASED INTEGRATED LAND USE/COVER CHANGE MODEL FOR THAILAND 
K S Rajan* and Ryosuke Shibasaki 
Institute of Industrial Science, Univ. of Tokyo 
7-22-1, Roppongi, Minato-Ku, Tokyo 106-8558, Japan 
Phone: (81-3)-3402-6231 Ext. 2563. Fax: (81-3)-3479-2762 
*E-mail: rajan@skl.iis.u-tokyo.ac.jp 
Commission VII, Working Group 5 
KEYWORDS: Agricultural land use, GIS, Land Use, Model, Thailand, Urban land use 
ABSTRACT: 
A model to simulate the changes in land use patterns, at the national-level is presented here. The case study region 
choosen for this model is the Royal Kingdom of Thailand, as it offers a typical trend example of the shift in the land 
use/cover patterns in the last two decades, under the changing socio-economic climate of the region. 
The land use model developed here takes into account two major land uses that are influenced by humankind — 
agricultural and urban land use. It also considers the spread of deforestation to a certain extent. In the model, the 
land use changes if the benefits are greater than the existing land use within the behavioural responses of the 
landowner. After an assessment of the demand for the different land uses within the national boundaries, the final 
decisions are made at a local grid-level. A GIS platform was used to integrate the different kinds of data that was 
used to assess the changes. The important biophysical drivers considered are the climatic conditions, soil and 
terrain, water availability and existing land use and land cover maps. Other land use drivers are population, 
economic factors and level of affluence. 
The model developed here helps to understand that this kind of national-level approach can contribute more 
realistically to understanding future changes in land use patterns. It also brings forth the advantages in using the 
GIS platform for such analysis. 
1. INTRODUCTION 
Land use/cover is continuously changing, both under 
the influence of humans and nature resulting in 
various kinds of impacts on the ecosystem (Rajan, et 
al, 1997a). These impacts at local, regional and global 
levels have the potential to significantly affect the 
sustainability of the world agricultural systems and the 
forest systems. The most important factor in the 
modification of the land cover and its conversion is the 
human use component rather than the natural changes 
(Turner, et al., 1993). Changes in the land cover cannot 
be understood without a better knowledge of the land 
use changes that drive them and their links to human 
causes. The linkages between the human and 
biophysical causes or drivers to land management and 
land cover are not sufficiently understood (Rajan et al., 
1997b). This arises from the complexity in dealing with 
the considerable variations in the drivers, use and 
cover at the local, national, and regional levels. At 
present, the global models and studies of land use 
changes capture the broad sectoral trends based on the 
changes in some of the macro variables, like 
population, quality of life and technology level. The 
Statistical data shows a strong support in concluding 
that these variables may be the underlying drivers of 
Intemational Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998 
environmental changes (Bilsborrow et al, 1992). On 
the other hand, such statistical relationships do not 
hold good for long-term analysis if the trends are 
dominated more by policy options and not by the 
inherent needs of the population, as seen in Fig. 1, for 
Thailand. Around 10% of the Cassava produced is for 
domestic use, and the rest mainly for export markets. 
The modeling at a national level is more complex than 
to generate a global picture, while local case studies 
pose a separate set of problems. They not only do not 
link well with either the regional or global scale 
models, but also identify an entirely different set of 
driving variables than the global models. The 
transformations in the land cover, occurring on the 
large scale will lead to large-scale changes in the 
"global environment". These changes are complex and 
require different scales of analysis (Alcamo et al., 1994, 
Robinson, 1994) 
Land use can be looked upon as a multi-dimensional 
(24D) process which consequently poses many 
difficulties for proper description and classification. In 
the context of global change, the formal characteristics 
of land use, i.e., its effect on cover structure, phenology 
and composition, is more relevant than the purpose or 
function of landuse (Veldkamp et al., 1996). 
Thus, to model Land use/cover changes realistically, it 
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