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ติดประกาศ ҷԵ 01 .. 07@ 06:06:33 ICT โดย admin
Ѵͻ 2006 Ҥ



Assoc. Prof. Dr. Charlchai Tanavud
Assist. Prof. Dr. Chao Yongchalermchai
Faculty of Natural Resources, Prince of Songkla University

Mr. Thudchai Sansen
Department of Environmental Quality Promotion, Ministry of Natural Resources and Environment


..................The present study assessed the amount of soil losses and sediment deposition in Songkla Lake Basin, Southern Thailand. Through the use of the Universal Soil Loss Equation (USLE) model in GIS environment, it was estimated that 22,951,339 tons of soil were lost from the basin in 2002, representing an average soil loss of 30.9 t ha-1 y-1. Further analyses revealed that 324,020, or 43.6 % of the basin's land area, were subjected to a very slight rate of soil erosion. The results also showed that 4.4 % of the land area, equivalent to 32,809 hectares, was subjected to a severe rate of soil erosion. Most of the severely eroded land was found on the mountain terrain to the west and south of the basin. The total sediment discharged into the lake systems in 2002 was estimated to be 6,885,402 tons; an average of 813.6 t km-2 of the basin, which would give a sedimentation rate of approximately 0.44 cm y-1. As a substantial proportion of the lake sediments could pass through a narrow outlet on the south of Thale Sap Songkla to the sea, the actual rate of sedimentation in the lakes could be lower. Conservation-effective measures to control soil erosion are discussed.

Key words : soil erosion, sediment deposition, Universal Soil Loss Equation, remote sensing, Geographic Information Systems.


Assoc. Prof. Dr. Charlchai Tanavud
Assist. Prof. Dr. Chao Yongchalermchai
Faculty of Natural Resources, Prince of Songkla University.


......................In Phipun Basin, southern Thailand, over-exploitation of the inherent productive natural resources base in the past has resulted in a disturbance of the finely tuned equilibrium of the basins natural ecosystems, setting the stage for the occurrence of one of the worst natural disasters in the countrys recorded history: the November 1988 massive landslides.
..................At present, the same patterns of resources exploitation which contributed to the occurrence of the disaster are continuing. As a result, the entire basin remains highly vulnerable to the occurrence of landslide disasters, thereby placing human lives, livelihoods and development activities at increasing risk to catastrophic landslides. It is therefore crucial that correction measures are undertaken to reduce landslide disaster risks. To respond to a growing threat posed by landslides, areas susceptible to landslides need to be assessed so that adequate and appropriate counter measures can be adopted and implemented.
..................In this study, susceptibility to slope movements of the Phipun Basins land areas were assessed based on factors that induce instability bedrock types, slope steepness, elevation, and land use, using GIS. The results revealed that areas of low susceptibility to landslides accounted for 15,751 ha or 35.7% of the basins total land area, 22,004 ha, 49.8% of the land area, were of moderate susceptibility, and high susceptibility areas covered an estimated 6,387 ha, or 14.5% of the total land area. These high-susceptibility areas were underlain by granite, on slopes greater than 35%, and under rubber trees. There is therefore a profound need to adopt and implement appropriate counter measures to reduce landslide risks in Phipun Basin.

Key words : landslides, landslide susceptibility, Geographic Information Systems, Phipun Basin

Land Use Zoning in Kho Tao Using Geographic Information System

Adul Bennui
Faculty of Environmental Management, Prince of Songkla University.

Asst. Prof. Payom Rattanamanee
Assoc. Prof. Udomphon Puetpaiboon
Department of Civil Engineering, Faculty of Engineering, Prince of Songkla University.


......................This research aims to allocate land use zones in Ko Tao, located in Amphoe Ko Pha-ngan, Surat Province, according to principle of area potential and natural resources by Geographic Information System (GIS). The study started with 2003 aerial photographs, 1:50,000 digital maps of Royal Thai Survey Department, together with field survey data input into a GIS. Then the overlaying technique in GIS were used for category land use zones.
..................The study revealed that existing land-use in Ko Tao can be divided into 3 zones; reservation, conservation, and development zones. Reservation zone, total area 8,124 rai, primarily covers with rainforests and open forests, lodgings, shop-houses and utilities/facilities. Conservation zone, total area 896 rai, consists of arid rainforests, open forests, areas for tourism, lodgings, agricultural and recreational activities. Development zone, total area 2,684 rai, is mainly used for agricultures, commercials, settlements and tourism activities.
..................There are 2 regulations may be issued corresponding to land-use in Ko Tao;
..................1) Since the land on Ko Tao is government statutory property, referring to Royal Decree of Government Statutory Property in 1975 - Article 6, Committees for Government Statutory Property have the right to propose Ko Toa to be "Land use Regulation Area"
..................2) Referring to Royal Decree of Promotion and Reservation for Environment in 1992 - Article 11 Paragraph 11, Article 43, and Article 44, Minister of Natural resources and Environment have the right to issue Ko Toa to be "Environment Protective Area".

Key words : GIS, Land use Zoning

Quantitative Analysis for Integrated Map Representation and the Statistical Information.

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


..................Thematic map in general is widely accepted for specific uses in a number of organizations. With the advent of mapping technology and geoinformatics, the visualization of maps and its associated statistics can be effectively performed. The objective of this study is to explore a diversity of visualizations in terms of spatial, quantitative and relative information. The methodology procedure included the study of map visualization, database establishment, statistical analysis and map creation. We used spatial information of Khon Kaen province and some of the Northeast Thailand for this study. The results obtained provide the techniques used and a diversity of map visualization. A number of maps and their associated statistics have been shown and made comparison in the senses of visualization for better meaning.

Application of GPS in Determining Integrated Water Vapour (IWV) in Thailand.

Assist. Prof. Dr. Chalermchon Satirapod
Faculty of Engineering, Chulalongkorn University

Nithiwatthn Choosakul
Faculty of Science, Chulalongkorn University


..................The use of GPS in meteorology is considered as a new application in GPS. Nowadays, any scientific GPS software package like GAMIT, GIPSY and BERNESE not only allows users to calculate precise site coordinates but also enables us to perform an estimation of tropospheric delays from GPS observations. The main purpose of this research is to estimate tropospheric delays and convert the delays into to the Integrated Water Vapour (IWV) value at the GPS site. The Bernese GPS software version 4.2 was used to process the GPS observations. The GPS-derived IWV value is compared against the IWV value obtained from the Water vapour Microwave Radiometer (MWR). The preliminary result shows that the difference is at millimeter level. The method purposed in this paper can therefore be used as an alternative to determine accurate IWV value for meteorological work.

Key words : GPS, Integrated Water Vapour, Bernese software

Forest Resource and Change Detection Using Multi-temporal Satellite Data
In Phu Khieo Wildlife Sanctuary.

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


..................ѵػʧͧ֡ ͷзӡõǨѴ¹ŧͧ鹷 ШṡͧתóࢵѡҾѹѵ ҡҾ´ Landsat - TM ªǧҹѺ ..2538 ֧ ..2548 㹡÷ἹªԹࢵѡҾѹѵ ǡѹ 2 ԸաõդҾµ Ǩ鹷͵Ǩͺ١ͧ 件֧èṡ ѹࢵѡҾѹѵ зӡºº¹ŧͧ鹷ªԹࢵѡҾѹѵ 㹾鹷ࢵѡҾѹѵǻ ջӤѭ 4 ҴԺ ҴԺ ѧͻອó л ͷҳ 50% 20% 17% 4% ӴѺ ǹ¹ŧͧ鹷ҧ ..2538 ֧ ..2548 ա¹ŧҡѡ¾鹷Һҧǹ¹Ҿ繷˭ 鹷ɵá ҡѺ 22.57 .. ǹҡ鹷ա¹ŧ͡ࢵѡҾѹѵҫ觾âµǢͧ鹷ɵá ת ҡѺ 81.17 . о鹷ǹ ҡѺ 4.01 ..

Ӥѭ : ѾҡûСõǨѴ¹ŧ ,Ŵѹ, ࢵѡҾѹѵ

Mangrove, Beach Forest, and Shoreline Mapping along the Andaman Sea Southern Thailand.

طȹ Ѳ
Ҿ ŧ
ѭѵ ͹ѹ
ҷ شѹ
ط ⾸Ҫ
ѡɳ Ҥ
Geo-Informatics and Space Technology Department Agency (Public Organization)
Ministry of Science and Technology


..................Following the Tsunami event in 2004, the disaster severely affected to human, properties, including natural resources and environment as well, along the Andaman Sea of Thailand. The mangrove, beach forest and shoreline have been critically deteriorated in 6 provinces along the Andaman Sea coast. As results, Remote Sensing technology has been used in these cases. The technology has been integrated in GIS data and field survey data with GPS on the monitoring of pre and post of the mangrove, beach forest and shoreline. Then, the outputs of these were composed and made the 1:25,000 scale map.
..................The results indicated that the mangrove forest in Phang-Nga province has mostly been decreased at Lam Kaen sub-district, Thai Muaeng district, and moderately affected area in Tha Phae district, Satun province, which the mangrove forest was replaced by agricultural area, such as shrimp farm, which the area of approximately 1,239 and 839 rai, respectively. The beach forest has been less severely affected because the physical charac-teristics of this area were consisted of a casualina tree. However, beach forest in King Amphoe Suk Samran district, Ranong province, has been mostly decreased, and the moderately affected area in Takua Pa, Phang-Nga province, with the area of approximately 22 and 16 rai, respectively. Besides, the shorelines which have mostly affected were found in Khura Buri district, Phang-Nga province, the moderately affected area in Kapoe district, Ranong province, with the area of approximately 2,264 and 2,077 rai, respectively.
..................In addition, the results of these were made the 1:25,000 scale map, totally 214 sheets. So, these maps are useful for the relevant agencies which being led to decision-making, management, and rehabilitations.

Geo-Informatics for Sugar Cane Industry Zoning in Eastern Thailand.

ѹ ÷ջԵҹѹ
ѳ بԵ
ǴзѾҡʵ ԷԴ
ʧ ʧǹ
ǹʵ Էɵʵ


..................֡Ҥ駹ѵػʧ ֡Ҿ鹷ѡҾѺû١ ֡ҡá˹ࢵѺ¢ͧçҹӵ ֡ʶҹѴʶҹբҤѹ͡кʹ Quantitative Systems for Business Plus version3.0 (QSB) 㹡ŤҢش
..................š֡ҡҾ鹷ѡҾѺû١ Ҿ鹷ѡҾѺû١Ҥѹ͡վ鹷ҳ 14,354.20 ҧ Դ 45.76 ͧ鹷 дѺѡҾ 3 дѺ 鹷֡ǹ˭Ѵ㹾鹷ѡҾѺû١дѺ٧վ鹷ҳ 7,751.81 ҧ 54.00 ͧŧҤ 鹷ѡҾѺû١дѺҹҧҳ 5,050.89 ҧ 35.19% о鹷ѡҾѺû١дѺӻҳ 1,551.51 ҧ 10.81
..................š֡ҡá˹ࢵѺ¢ͧçҹӵ 鹷ѡҾ٧վ鹷ҳ 15,665.85 ҧ 89.86 ͧŧҤ 鹷ѡҾҹҧ վ鹷ҳ 1,119.09 ҧ 6.42 й·ش 鹷ѡҾ 647.75 ҧ 3.72
..................š֡ʶҹѴʶҹբҤѹ͡ դ繵ͧѴʶҹբҤѹ͡ ͧҡçҹӵŷ 5 ç 㹾鹷֡աԡѺ¤ͺ鹷١·

Expert Classification for Age Class Identification of Oil Palm Plantation
in Krabi Province, Thailand.

Jarunya Kitiphaisannon
Sura Pattanakiat (Ph.D)
Charlie Navanugraha (Ph.D)
Faculty of Environment and Resources Studies Mahidol University.


..................The objective of this study is to apply the Geo-Information Technology including Remote Sensing, Global Positioning System, and Geographic Information System integrated with Expert System in order to generate a knowledge base system for age class identification of oil palm plantation. Rule base under the knowledge base for oil palm classification is generated from the relationship of multiple regressions related with Water Index (WI), Bare Soil Index (BI), Normalized Differential Vegetation Index (NDVI), and Advance Vegetation Index (AVI). These equations are used to define age class stage of oil palm plantation which can be divided into 4 classes: Young stage (1-3 years old), Intermediate stage (4-10 years old), Productive stage (11-20 years old), and Mature stage (more than 20 years old). The percentages of accuracy for each class using expert classification are 92.19, 50.88, 80.00, and 12.50 respectively. Meanwhile, the percentages of accuracy for maximum likelihood classification are 90.63, 42.11, 40.54, and 72.34 respectively. Therefore, the accuracy for each age class stage from the expert classification is higher than the maximum likelihood classification. Furthermore, the overall accuracy of the expert classification is about 63.11%, and the maximum likelihood classification is only about 60.33%. Thus the accuracy of the expert classification is about 2.78% higher than the maximum likelihood classification. In conclusion, application of the Geo-Information Technology and Expert System provides useful information about classification on age class of oil palm plantation.

Geographic Information System Modeling for Gorals Habitat Assessment
in Omkoi Wildlife Sanctuary, ChiangMai Province.

Vorapol Deeprasai
ӹѡ͹ѡѵ طҹ觪ҵ ѵ оѹת
Sura Pattanakiat
ǴзѾҡʵ ԷԴ

..................ἹѲɰԨѧ觪ҵԩѺ 10 Ѱ繶֧ӤѭͧúèѴ÷ѾҡøҵǴ ¡˹ǷҧطʵúèѴաþѲШѴӰҹŷѾҡøҵǴ෤ʹҧԷҾ㹡õԴǨͺШѴ÷Ѿҡøҵҧѹ ա֡ԨҧԤѹ աõԴżšзҡ¹ŧͧǴšҧἹѺѭ Ѩغѹкʹʵ (Geographic Information System : GIS) պҷҧҡ㹡ҧἹèѴ÷ѾҡøҵҧǴзѹ ʶҹóѨغѹ ͧҡöԧ鹷»ǡѹ öѴ红ҧк ʹ͢ѴਹФͺ ѺкʹʵСǨͧͷջԷҾҧҡ͡ù 㹡ûԹ觾鹷繶蹷¢ͧҧҧѴਹ
..................ӤѭзҢͧ֡㹤駹 ͧҡҧն蹷¨ӡѴ㹺ҧ鹷ͧҹ 觹ҡºѺ鹷áШ·Ƿš ѧ 㹡÷Һ֧Ѩ·դӤѭ͡͡蹷 áШ кdzվ鹷Ѻҧ ʴ͡öͧҾѴਹ 繰ҹ㹡õѴԹ㨵͡èѴ Сûͧѹ鹷ҴҨ繾鹷դӤѭ (hot spot) Ѻҧ ͹ӢŨҡ֡ҹ任ء繻ª͡Ҿ鹷 ¾ԨóҨҡѨµҧ ˹㹡û ҧ ѵҪԴ ׹ еԴ֡ҵ͹Ҥ

An Analysis of Wisdom and Skill Products for Development
and Their Geographic Distribution in Northeastern Thailand.

Rusamee Suwanwerakamtorn
Charat Mongkolsawat
Vichien Kerdsuk
Bang_onn Yommaraka
Wasana Putklang

ٹʹ͡þѲҤѹ͡§˹ Է¢͹
Ongkan Indrambarya
Sakorn keucharoen
Chadrudee Sombutham


..................The policy of Thai government focuses on strengthening the economic cornmunity of the grass-roots. As a result, the extension of local wisdom, skill of people and ways of living are essential with objectives of transferring knowledge bases and of developing the product sustainability. To accomplish these, the databases of local wisdom and skill were then established with an analysis of those skill products.
..................The databases of ways of living, wisdom and skill of people in local communities are established, based on the existing products in the communities. The data obtained from interviewing people who were original procedures or their connections. In every province of the Northeast, 5 kinds of products were selected each of which were produced from 3 villages.
..................The data set were then hierarchically categorized into 4 levels; kind of wisdom, main product, product group and product type. The databases were established and linked to geographic locations. Further analysis of each product was performed, based on local wisdom, skill required on production and market management, with a number of criteria used. The prospect of the products according to the criteria could be classified into 3 levels : high, moderate and low.
..................The geographic distribution of the information obtained was digitally performed using GIS The database establishment of the ways of living local wisdom and people skill was performed for 19 provinces in the Northeast. The classification of the products are accounted for 52.78, 45.37 and 1.85% for the applied wisdom, traditional wisdom and innovated wisdom respectively. Of the total products, about 33.23% is the hand weaving products. Moreover, in terms of the prospect of the product. in the Northeast there are 20.68, 70.37 and 8.95% of the total products (314) classified as high, moderate and low prospects respectively.
..................It is reccommented that the products with high business prospects should be preserved as a local heritage. The product with moderate prospects should be supported with research and development to strengthen the commercial values.

Key words : local wisdom, skill products , OTOP , GIS , Northeastern Thailand

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