Towards Sustainable Land ues through Land Evaluation :
A Case Study of Muaklek, Thailand
The FAD Framework for Land Evaluation was adopted to conduct this study. The basic source materials used for spatial analysis of suitability classification were: soil map (scale, 1:100,000), topographic map (1:50,000), geological map 19′;c (1:250,000) and meteorological data. Land use were interpreted from Landsat TM film (1:500,000) of 14 December 1989 using Procom II. The principal process involved in land suitability classification is matching the land use requirements and limitations. with land qualities. The main physical parameters considered for the spatial analysis were soil texture, effective soil depth, : surface runo.f1 permeability, soil pH; organic matter, cation exchange capacity, available phosphorus and potassium, slope, bedrock type and rainfall. Slope classes were generated from the topo map. Similarly, bedrock types were generated from the geological map. Information on other parameters were acquired from the existing secondary sources. Limitation concept combined with parametric classification approach was employed for performing physical suitability analysis. Proper weightage as per the land use requirement (LDD, 1992) for the selected crops were given to the different classes of individual parameter considered which were encoded into a digitized GIS coverage. Similarly, after proper rating of the every attribute of other maps, viz., land use, slope and geological, their respective weightage were also encoded in their individual GIS coverage’s. Suitability analysis was performed following a linear combination approach by overlaying all the coverage’s in vector-based GIS (ARC/INFO). A field survey was also conducted to collect socio-economic information and for ground truthing. Besides evaluating the soil suitability for the selected crops, the cost and return for each crop was also appraised through Benefit/ Cost , analysis to see their economic feasibility
4.0 Results and Discussion
4.1 Land Suitability Classification
The process of land suitability classification involves appraising and grouping of specific types of land in terms of their absolute or relative suitability for a specified kind of use (FAG, 1976). The suitability map produced distinguishes four different classes for the crop production, viz., highly suitable (S2), moderately suitable (S2), marginally suitable (S3), and not suitable (N) on the basis of level of limitations associated. In the “not suitable” (N) class, no further distinction between “currently not suitable” ( N 1 )and “permanently not suitable” (N2) was made, because this group constitutes natural vegetation and built-up areas. It was also observed during the field survey that some of the area with greater slope gradient are heavily eroded resulting into unsuitable for the crop cultivation. Since it is neither feasible to correct soil limitations nor is it economically feasible, these area can only be rehabilitated by protecting the top soil with vegetation cover. Based on the physical parameters, the study area have been delineated according to suitability classes for maize, cassava,orchard growing and pasture production. Such land suitability classes which are basically physical suitability are presented in Table 1.
Table 1. Soil Suitability for Maize, Cassava, Orchard and Pasture.
|Existing landuse (% of total)
Land suitability for maize: Compared to existing land use under maize (46% ), spatial analysis showed that as much as 11.3% of the total area are highly suitable for maize production. Likewise, 28.9 and 13.5% are of moderate and marginal suitability, respectively and the area under not suitable category is 46.3%.
Land suitability for cassava: Land suitability for cassava was evaluated because of the fact that the cassava was found to be the second crop after maize in terms of area coverage for the interviewed farmers. However, the cassava land use during 1989 was very insignificant (0.5%), it implies that the cultivation of cassava is increasing over time. As it is generally believed that cassava is usually grown in rather less fertile soils, it indicates that the soil fertility is decreasing over time and maize is being replaced due to loss of soil fertility .The SI’ S2 and S3 category for cassava production accounted 19.4, 18.7 and 10%, respectively.
Land suitability for orchard: Nearly one third (30.6%) area was found highly suitable for orchard growing where as 23.8 and 1.9% area were classified as moderate and marginal suitability.
Land suitability for pasture: For the pasture suitability, the proportion of the area under SI’ S2 and SJ category accounted to 32.2,21.7 and 4.4%, respectively.
Looking at the spatial representation of the suitability classes for the selected crops ( Figure 3), it is understood that the SI class is shared for all the crops in particular location with better land quality.
Figure 3. Land Suitability for the Selected Crops.
4.2 Agricultural Land Use and Management Practices
Although maize and cassava are the major crops grown in the area, their productivity of 2.05 and 5.18 ton per ha., respectively were very low compared to the average productivity of Muaklek district. The Multiple Cropping Index (MCI) of 2.4, 2.1, 1.2 and 1.1 were found for marginal, small, medium and large category fanners, respectively with an average MCI of 1.5. Majority of the farmers have adopted the monoculture/ monocropping system due to insufficient soil moisture and poor soil status. Level of management differs according to the resources affordability of the farm categories.
4.3 Farm Income and Expenditure
18.5% of the households were found having an annual income of less than 50,000 Baht (1 US$ = 25 Baht) , whereas, 13% were found having more than 400,000 Baht per annum, nevertheless, the earning from livestock was the major source of income (60% of the total income) for all farm categories. Second major source of income (25% of annual total income) was non-farm activities. The share in income from the crop constituted the least (15%) for all farm categories (Shrestha, 1993). In relation to household expenditure, expenses on livestock fanning accounted a major share (60%) of total annual expenditure of a farm household followed by expenditure on household consumption and domestic use (28%) and crop farming (12%) (Shrestha, 1993).
At this point, it is clear that the livestock production system is an important subsystem in the area. Considering this r along with the area to be the largest dairy production area, it will be desirable to discuss this aspect in rather detail.