home    land degradation    project outcome    Gallery Flooding Flood Hazard Assessment Pilot Area • The Pilot Areas • Climate • Cover factor (C) estimation • Digital terrain analysis • Relationship between soil properties • Relationship of soil properties with different land use/cover types Methodology • Methodologies • LISEM Results • Result Soil Properties and Land Use • Runoff rate for different land cover types • Model calibration and validation • Sensitivity analysis • Land use scenarios • Rainfall size scenarios • Flooding Scenario - 2 years return period • Flooding Scenario - 10 years return period • Flooding Scenario - 20 years return period • Flooding Scenario - 50 years return period • Summary tables for each flood characteristic • Flood hazard mapping • Conclusions and Recommendation Erosion Erosion Assessment Pilot Area • The Pilot Areas • Climate • Cover factor (C) estimation • Digital terrain analysis • Relationship between soil properties • Relationship of soil properties with different land use/cover types Methodology • Methodologies • Erosion Models Result • Results • C-Factor Mapping for erosion assessment • Soil erosion assessment • Assessment of land use/cover change effect on soil erosion • Assessing critical zones for ephemeral gully formation • Erosion Assessment by Different Models • The recommended erosion models • RMMF Landslide Case I • Landslide hazard assessment • The area (Pilot 3) • Landslide Mapping in Wang Chin using digital image analysis Techniques. • Results • Discussions Case II • Doi Ang Khang (Ang Khang) (Pilot area 4) • Landslide mapping in Ang Khang using aerial photos • Landslide Inventory Mapping • Landslide modelling and Susceptibility mapping • Landslide Susceptibility Maps from the three Scenarios (models) • Comparison between Ang Khang and Wang Chin (with respect to weights of evidence modelling using morphometric parameters) Salinization Case I • Pilot area II • Soil salinity • Salinization • Geomorphology • Soils • Geopedologic map • Results Case II • CASE II - The study of Yadav, R.D. (2005), • Methodology • Crop Simulation Model • PS 123 • Results • Mathematical (Regression) Model for Crop Yield Estimation • Conclusion Case III • Case III • Modeling Salinization • Geostatistics and Interpolation (GIS and Kriging) • Model Simulation and Prediction of Salinity • Simulated Depth to water table • Tenth Years Prediction • Twenty Years Prediction • Conclusion Runoff • Surface Runoff • Methodology • Modelling Runoff • Modelling Runoff Using Empirical Approach • Modelling runoff using the Semi-physical approach • Estimation with the Curve Number Method • Results and Discussion • Generation of Scenarios • Comparison of runoff rates with soil loss map • Conclusions • Presentation of papers based on project work at international • Workshop in Lomsak • Hua Hin seminar • Training of LDD staff • GIS and RS based predictive soil mapping • Soil erosion assessment • Landslide hazard assessment • Flood hazard assessment • Soil salinity study • List of completed MSc. theses on project RESULTS The main objective of this study is to assess erosion prone areas in inaccessible mountain areas by applying image processing and digital terrain analysis techniques. The topographic removal techniques were implemented to improve spectral reflectance of Landsat satellite images obtained in 1988, 2000 and 2007. Image classification was applied to generate land use/cover map. Trend of land use/cover change was also investigated to know the conversion between land use/cover classes in those periods. For assessing soil erosion, the erosion model played important role. An assessment of the relationship between NDVI and C-factor was done to see whether NDVI could be used as estimator of C-factor in the study area or not. Land use/cover map 2007 was used to predict soil loss rate and classified erosion prone areas. It was also used to analysis bulk density and soil organic matter distribution pattern in different land use/cover classes. The results of analysis together with trend of land use/cover change are reflected in soil erosion. Digital terrain analysis was carried out to define critical zones for gully formation which was then compared with the erosion prone areas for confirmation. In this chapter, results are summarized and discussed as follows:   Land use classification Land use/cover classification of 1988, 2000 and 2007 were done by using supervised classification with the maximum likelihood algorithm in ERDAS 9.1 software. Training samples were separated from validated data. The land use/cover maps were classified in five classes including forest, degraded forest, agriculture, grassland and orchard with total areas 6,658 hectares. In Figure 1 (a), (b) and (c) showed land use/cover classification maps in periods of 1988, 2000 and 2007 respectively. The comparison of the different land use/cover between those periods is shown in Table 1 as follows. Figure 1 : Land use/cover classification maps; (a) 1988, (b) 2000 and (c) 2007 Table 1 : Comparison the areas of land use/cover in 1988, 2000 and 2007 Land use/cover class Area in 1988 Area in 2000 Area in 2007 hectares percent hectares percent hectares percent Forest 2699 40.54 2411 21.20 857 12.87 Degraded Forest 2663 40.00 2551 38.33 2267 34.04 Agricultrure 740 11.11 1107 16.62 1686 25.32 Grassland 496 7.45 1081 16.23 778 11.70 Orchard 60 0.90 508 7.62 1070 16.07 Total 6658 100 6658 100 6658 100 Trend of land use/cover change from 1988 to 2007 From the results of classification in the periods 1988 to 2007, forest and degrades forest areas were decreasing especially forest areas loss around 1,842 hectares from 2,699 hectares within 19 years. Degraded forest areas also decreased from 2,663 hectares to 2,267 hectares. Conversely, in agriculture areas and orchard that increased 946 and 1,010 hectares respectively. These were an evident that deforestation had occurred in this area. Most of the area has rugged terrains that mean the deforestation also occurred on hill slope areas, which was replaced by agriculture. This led to soil erosion problem and severe disaster that caused heavy landslide and flooding in 2001. During field work it was observed that, orchard and agriculture areas were on the mountain slopes. Although the government policy is a forestation on sloping land but it lacked of realistic implementation and responsibility of the villagers and officers. Also the forest areas from plantation project were not permanent. Teak plantation has the objective for commercial reason; they will be cut down again when they grow up. The change of land use/cover areas in periods 1988, 2000 and 2007 is shown in the Table 2 below: Table 2 : Land use/cover change in the periods 1988 - 2007 Land use class 1988 Area in hectares 2000 Area in hectares 2007 Area in hectares Change area from 1988 to 2007 in hectares Change from the total area (%) Forest 2699 2411 857 -1842 -27.67 Degraded Forest 2663 2551 2267 -396 -5.95 Agricultrure 740 1107 1686 946 14.21 Grassland 496 1081 778 282 4.24 Orchard 60 508 1070 1010 15.17 Total 6658 6658 6658   Development of Methodologies for Land Degradation Assessment Applied to Land Use Planning in Thailand ^go to top