P1-5-5 
Here the potentiality of remote sensing and GIS will 
be utilized to generate some of required data. Land 
covers dynamics will help to see the soil loss pattern. 
From soil loss, the agriculture productivity dynamics 
can be studied which leads for the estimation of the 
rural wage trend in real sense. This will help to see 
the rural urban (will be fetch out from secondary 
data) wage difference. The regional and/or provincial 
flow of migration, socioeconomic status, natural and 
artificial regional development potential and 
amenities will be analyzed with the help of secondary 
data. This will leads to establish and formulate the 
model. The data, which will be used in this study, 
are: 
• Land use map, 1990, 1:500,000, Dept, of Land 
Development (DLD). 
• Land use map, 1980, Global Engineering lab, 
IIS, The University of Tokyo. 
• Land use map, 1999, will be derived from 
NOAA LAC AVHRR data. 
• Digital Elevation Model, Road and River 
network from 1:250,000 RTSD Topo Maps, Soil 
Information from soil map (varied scale) of DLD 
• Meteorological data and other various 
socioeconomic statistical data form different 
government and INGOs institutes. 
In most of the developing countries, including 
Thailand, there is always lack of suitable data for 
desirable studies. In this study, the lack of temporal 
variation in the land use pattern and the updated soil 
fertility assessment are the main data constraint. As 
explained earlier, the rural income largely depends 
upon the soil fertility. 
5 PRELIMINARY RESULTS 
At present stage, small volume of data has been 
analyzed to see the preliminary trend of some 
variables, which are going to be used in the proposed 
model. The analysis has been done by taking the 
provinces (CHANGWAT) as a unit and the results 
are summarized by the region. According TEI 
(1997), Thailand is divided into 76 provinces and six 
regions NRD2C coding scheme (Fig.3). 
There are lots of variations among the regions. For 
example, the per capita income gap between the 
regions is considerably high. The northern and 
northeastern regions have wider gap as compared to 
other regions. The central region enjoyed the highest 
rate of per capita income (Fig. 4) 
The provincial migration pattern has been analyzed 
from 1955 to 1990. The total net in migration has 
been observed at the central and eastern regional 
provinces, which seems to be taken out from north 
and northeastern provinces. The west and southern 
provinces has little overall share in the in and out 
flow. The share of the movement fluctuates largely 
with the time but the general pattern showed the 
widening up the migration. The summarized 
migration is shown in Figure 5. 
The all time increase in the provincial wage rate 
(present value) has been observed through out the 
country. The central, southern and eastern provinces 
lie above the national average, while northern and 
northeastern provinces lie, considerably, below. The 
western provinces are at the margin of the national 
average (Figure 6). 
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Figure 3: Map of the Thailand Showing Regions 
Figure 4: Per Capita Income by Region, 1994 (NSO, 1996)