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ติดประกาศ 31 .. 07@ 06:02:21 ICT โดย admin
Ѵͧ͢ 2004 Ҥ


Land Use Patterns and Landslide Hazard in Pak Phanang Basin

Assoc. Prof. Dr. Charlchai Tanavud
Faculty of Natural Resources,
Prince of Songkla University, Thailand.

Abdollah Bennui
Research and Development Office,
Prince of Songkla University, Thailand


..............Information derived from satellite imagery revealed that there was appreciable deforestation in the headwater source areas in Pak Phanange Basin. Indeed, it was found that 2,293 hectares of the headwater areas lost converted to rubber plantation and mixed orchards. This misuse of land resources could contribute to the occurrence of natural disasters, particularly landslides. With the use of the Geographic Information Systems (GIS), it was estimated that, of the basin's total land areas, 8,085.00, 24,370.00 and 278,062.00 hectares, respectively, were subjected to high, moderate and low landslide hazards. Areas subject to high hazards are mostly found on mountain ranges in the west of the basin in Lansaka and Ronpibun districts. Land use patterns which have contributed to the occurrence of landslides are continuing and, if unmodified, will further increase hazard and vulnerability levels. Measures to decrease landslide hazard and reduce vulnerability of element at risk are discussed.

Application of GIS to the Protection of Agricultural Areas
in Northeast Thailand

Sathaporn Paiboonsak
Faculty of Agriculture, Khon Kaen University, Thailand

Assoc.Prof.Dr. Charat Mongkolsawat,

Theeraya Uttha,

and Urawan Chanket
Computer Center Khon Kaen University, Thailand.


..................The objective of this study is to establish the spatial database for supporting the delineation of the agricultural area protection.The study area, Northeast Thailand, covers an area of about 105.5 million rais (170,000 km 2 ) of one-third area of the kingdom. An integration with GIS modeling of the thematic layers is an approach used. An area analysis with consideration of conservation areas and agricultural suitability of land is concept methodology. The methodology steps included the establishment of spatial database, overlay analysis and output creation. The thematic layers concerned consist of the forest reserve area, future urban land use, irrigated areas and suitability of land for rice, field crop and fruit tree. The overlay analysis was performed with the selection criteria that the protection areas should be the areas outside the conservation area or the highly suitable land for agriculture or within irrigated areas. As the result the protection area is accounted to 3.27 and 13.03% of the total area for the first and second classes respectively. It should be noted that with GIS modeling effective and reliable identification of the agricultural protection areas can be digitally performed. As a consequence the result should be used in support of the legal measure for the sustainability of the land use planning.

Soil Water Modeling Using Geographic Information System

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...........The objective of this study was to create a model of weekly soil water content by using the water balance equation in Geographic Information System (GIS). The main variables used in the computation were rainfall, evaporation, slope, and soil texture. The study area was the whole area of Phitsanulok province. Spatial resolution was 40*40 meter 2 and temporal resolution was 52 weeks. The results showed that average rainfall, average actual evaporation, and average runoff were 2,093, 1,428, 515 m 3 /rai/year, respectively. These three variables were later calculated with percolation, estimated from 7 methods, in soil water balance equation. The analysis showed that the selected SW (B) model, calculated from variation of soil type, gave average soil water content of 97 m 3 /rai/year. The soil water content was accumulated starting from week 18 th to week 3 rd of the next year and maximized in week 37 th (75.5 m3/rai).

Correction of Raw Satellite Image Data for Quantitative Analyses

Assist. Prof. Dr. Thaworn Onprapai
Department of Soil Science and Conservation & Multiple Cropping Center
Faculty of Agriculture, Chiang Mai University


..................The electromagnetic energy remote sensing sensors record from the earths surface does not represent absolute spectral reflectances (R) due to atmospheric effects. Gases, fog, smoke and dust absorb and scatter the electromagnetic energy on its way through the atmosphere. Therefore it is very important to carry out quantitative analyses of satellite data on the basis of the absolute spectral reflectance in each spectral band. This is, for instance, necessary when images from different orbital paths are required to cover a study area, when a time series of images is used to compare spectral properties of surfaces at different times, or when spectral response parameters are used as input parameters for models.
..................Radiometric sensor calibration and atmospheric correction allow the derivation of absolute spectral reflectances in each band from the raw satellite image. In this paper, a strategy to convert raw satellite images to absolute spectral reflectance data sets is being presented. The application of this procedure allows the comparison of features in images acquired under different conditions and at different dates. Absolute spectral reflectance data sets allow the quantitative analysis of satellite images and can be used as spectral reference. Absolute spectral reflectance values can also be utilised as parameters in statistical models to precisely predict crop yields and production.
..................The procedure presented in this paper comprises the following 3 steps: (1) Transformation of Digital Numbers: DN to At-Satellite Spectral Radiance: L?, (2) Conversion of At-Satellite Spectral Radiance: L? to Ex-Atmospheric Spectral Reflectance: ?, and (3) Adjustment of Ex-Atmospheric Spectral Reflectance: ? to Absolute Spectral Reflectance: R. The effects of these transformation steps can be verified by comparing Vegetation Index (VI) values calculated at different stages of the transformation procedure.

Identification of Teak Plantation Area Using Remote Sensing Technique in Pasak Watershed

Prasong Thammapala
Faculty of Science and Technology, Thailand.

Assist. Prof. Dr. Siripun Taweesuk
Thammasat University, Rangsit Campus, Thailand.


..................This paper presents an analysis of teak plantation (Tectona grandis) using remote sensing techniques in Pasak Watershed area. Four image classification techniques, namely, unsupervised (ISODATA), supervised (maximum likelihood), hybrid and principal component analysis (PCA) classifications were analyzed and compared in order to determine teak plantation classification accuracy. LANDSAT-5 TM and LANDSAT-7 ETM+ digital data acquired on November 19 and January 11 in 2003 were used as the experimental data. The overall accuracy, kappa statistic, producers and users accuracy were computed from error matrices. These data are then used to evaluate the accuracy of the teak plantation classification. The analysis of pair wise significant test and Z-test were also employed for statistical interpretation.
..................The result indicated that the teak plantation areas classified by principal component analysis technique, yielded the highest producers and users accuracy of 94.0 and 71.8 percent, respectively. The hybrid classification techniques produced the second best classification accuracy results. However, the complication of an analytical procedure, processing time, cost of analysis, knowledge and experience of the data analysts should be taken into consideration for users. The results showed no significant difference in accuracy from supervised, hybrid and PCA techniques. However, the unsupervised classification technique gave a lower accuracy level.
..................Other conclusions have been drawn from our study; the areas of forest plantation in Pasak watershed have declined in the past ten years. Based on the study, hybrid and PCA techniques can be applied to discriminate Teak plantation areas from other land cover types with Teak that have an average height of more than 7.0 m. and diameter at breast height (dbh) of more than 9.0 cm.

An Application of GIS and Hydraulic Model to Flood Plain Inundation

Naruemol Taragsa
Department of Computer Science, Faculty of Science
Khon Kaen University, Thailand.

Assoc.Prof.Dr. Charat Mongkolsawat
Center of Geoinformatics for the Development of Northeast Thailand
Computer Center, Khon Kaen University, Thailand

Assistant Prof. Chalermchai Pawattana
Department of Civil Engineering, Faculty of Engineering
Khon Kaen University, Thailand.

Miss Rasamee Suwanweerakamtorn
Center of Geoinformatics for the Development of Northeast Thailand
Computer Center, Khon Kaen University, Thailand.


..................Flood plain inundation modeling is commonly done on the topographic map by a calculation of water surface profile (WSP) using hydrologic program. Water surface profile was plotted and drawn a flood plain inundation on the topographic map. However, there are some limitations of method such as; difficulty in the identification floodplains roughness coefficients in small area with variable land covers. Therefore, the objectives of this study were to create floodplain inundation model for represent flood extents and flood depth. The study area, Chi basin partly Maha Sarakham, Kalasin and Roiet provinces cover an area of about 1,500 square kilometers and is found high risk and annually flood area. To prepare cross section of the area, a set of theme layers were reviewed and prepared. These thematic layers include elevation, water body, land use, stream center line, bank line, flow path, river profile and cross section.
..................Each of the layers with associated attribute was digitally encoded in GIS to eventually create the thematic layers. Water surface profile was calculated using the cross section, stream center line and flow rate. This was performed by the hydrologic program (HEC RAS 3.1.1). WSP was interpolated to create WSP raster layer. The overlay operation of WSP layer and digital terrain model (DTM) was performed to produce flood depth and extent. To evaluate the result, the resultant flood extent was checked against the data acquired by RADARSAT. The percent fit is about 52%. To enhance the model capability be more reliable detail of the thematic layer is needed.

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