Land use change detection
Three SPOT multi-spectral band satellite images were used to detect land use change. Supervised classification was performed for each image. Field surveys, digital topographic maps, and land use maps were combined to evaluate land use coverage and other information. This procedure allowed for identifying training samples to be selected based on land use types. Three classified land use images were combined to determine the changes during three periods of 1994-1998, 1994-2002, and 1998-2002 (Fig 2). The classified image in 2002 was calculated for accuracy through field survey based on Kappa analysis (Congalton and Green, 1999). Two other classified images in 1994 and 1998 were not evaluated for their accuracy because they were short of accurately reference data.

F 2 .Analysis method for land use changes.

Land suitability evaluation for watershed pond
Criteria of land suitability were divided into two types: factors and constraints. A factor is a criterion that enhances or detracts from the suitability of the specific alternative under consideration. A constraint is a land type or use that restricts or makes it impossible to develop watershed aquaculture ponds, such as land that is currently natural forest, road, river or large water bodies.

Weightings and suitability ratings were based on the level of importance of a factor that influences aquaculture. Suitability ratings were established according to FAO classification (FAO, 1977) in terms of suitability of land for defined uses, and the similar methodology had been successfully used in aquaculture (Hajek, and Boyd, 1994, Aguilar-Manjarrez and Ross, 1995; Salam et al., 2003). The interpretation of suitability classes for each factor was classified on a scale from 4 to 1 as follows. Highly suitable (4) provides a situation in which minimum time or investment is required in order to develop fish farming. Suitable (3) requires a modest time and investment. Moderately suitable (2) requires significant interventions before fish farming operations can be conducted. Unsuitable (1) requires a time or cost or both that is too great to be worthwhile for fish farming (Table 1). Constraints (rivers, roads, natural forests, large water bodies) were coded as 0 and others were coded as 1 to exclude the constraint areas from suitability maps (Nath et al., 2000).

The weight for each factor was determined by pair-wise comparisons in context of decision-making process known as the analytical hierarchy process (Saaty, 1990; Canada et al.1996). The suitability rating for each level of a factor was determined from the result of the survey and expert opinions (Table 2). Suitability scores were calculated as:

Table 2:-The pair-wise comparison matrix for assessing the relative importance of land characteristic factors for each land use requirements (numbers show the ratings of the row factor relative to the column factor).
For Potential for pond construction

	Slope	Land cover	Soil thickness	Elevation	Weights
Slope	1				0.40
Land cover	2/3	1			0.27
Soil thickness	½	2/3	1		0.16
Elevation	1/3	½	3/2	1	0.17

Consistency ratio (C.R.) = 0.03

For Soil quality

	Soil types	Soil pH	Clay content	Weights
Soil types	1			0.46
Soil pH	2/3	1		0.32
Clay content	½	2/3	1	0.22

Consistency ratio (C.R.) = 0.00

For Water availability

	Distance to water	Water sources	Precipitation	Weights
Distance to water	1			0.50
Water sources	2/3	1		0.33
Precipitation	1/3	½	1	0.17

Consistency ratio (C.R.) = 0.00
For Geographical and social economic

	Distanceto road	PopulationDensity	Distanceto market	Distanceto hatchery	Weights
Distance to road	1				0.46
Population density	½	1			0.28
Distance to market	1/3	½	1		0.16
Distance to hatchery	¼	1/3	½	1	0.10

Consistency ratio (C.R.) = 0.01

For four land use requirement factors for assessment of site suitability for watershed pond aquaculture

	Potential for pond construction	Soil quality	Water availability	Geographical and social economic	Weights
Potential for pond construction	1				0.45
Soil quality	½	1			0.26
Water availability	1/3	½	1		0.17
Geographical and social economic	1/3	½	½	1	0.12

Score = (w1r1 + w2r2 +… + wnrn) / n x 100
Where, wn and rn are weight and rating score each factor n.

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