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ติดประกาศ ʺ 08 .. 07@ 15:40:28 ICT โดย admin
ҹԨ ʷ.շ7 Ѻ 3(1)
Ѵ


èѴἹҪŹ ҪҴ ǪҴdz½觷ѹѹͧ
Mangrove, Beach Forest, and Shoreline Mapping along the Andaman Sea Southern Thailand

طȹ Ѳ
Ѿҡ÷ҧЪ½觡зǧѾҡøҵǴ


Ҿ ŧ
ѭѵ ͹ѹ
ҷ شѹ
ط ⾸Ҫ
Ǵ ԾҹԪ ѡɳ Ҥ
ӹѡҹѲ෤ǡʹȡзǧԷʵ෤

Abstract
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.

Ѵ
ѧҡ˵ءóֹͻ» 2547 ҧԵзѾԹ繨ӹǹҡ 駷ѾҡøҵǴ㹺dzǪ½觷ѹѹͧ 鹷ҪŹ ҪҴ ǪҴ ա鹷˹觷Ѻ¨ҡ˵ءó駹 ѧ ෤աǨźóҡѺкʹʵ (GIS) ʹŷҡǨҤʹ ͧ˹˹觺š (GPS) ͵Դ¹ŧ鹷ҪŹ ҪҴ ǪҴ 駡͹ѧʺ¤ֹ йҨѴἹ ҵǹ 1: 25,000
šôԹҹ 鹷ҪŹͧѧѴѧŴŧҡش Դͷҳ 1,239 ҡdzӺ ͷͧ ͧŧ ѧѴʵ Դͷҳ 839 dzͷ ǹ˭Դҡúءء鹷͡ ɵ ҡ ǹ鹷ҪҴ Ѻҡѡ ͧҡѡɳзҧҾͧҪҴʹ 觨ѧѴվ鹷ҪҴŴŧҡش ѧѴйͧ Դ ͷҳ 22 ҡdzآҭ ͧŧ ѧѴѧ Դͷҳ 16 ҡdz͵Сǻ ǪҴѺҡش dzѧѴѧ Դͷҳ 2,264 ҡdzͤк ͧŧҤ ѧѴйͧ Դͷҳ 2,077 dz͡
ҡ ӢŢҧҨѴἹҪŹ ҪҴ ǪҴ 駡͹ѧʺ¤ ֹ ӹǹ 214 ҧ ˹§ҹǢͧ ö繢ŻСͺ㹡õѴԹ㨵ʹú Ѵ ҧἹп鹿پ鹷



кʹ͡˹ࢵѺ¢ͧçҹӵҤѹͧ͡
(Geo-Informatics for Sugar Cane Industry Zoning in Eastern Thailand)

ѹ ÷ջԵҹѹ
Ѳõ
ѳ بԵ
ǴзѾҡʵ ԷԴ
ʧ ʧǹ ǹʵ Էɵʵ

Ѵ
֡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·



 
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