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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/44805


    Title: 應用衛星資料及地理資訊系統在印尼BALURAN國家公園野生牛棲息地之測繪;MAPPING HABITAT SUITABILITY OF BANTENG (BOS JAVANICUS) USING SATELLITE IMAGERY AND GEOGRAPHIC INFORMATION SYSTEMS AT BALURAN NATIONAL PARK, INDONESIA
    Authors: 魏凱芳;Khanty Widayanti
    Contributors: 遙測科技碩士學位學程
    Keywords: 棲息地;地理資訊系統;衛星影像;野生牛(Banteng);Bos javanicus;Satellite Imagery;Banteng;Geographic Information Systems;Habitat Suitability
    Date: 2010-07-21
    Issue Date: 2010-12-09 14:02:12 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 對於保護瀕臨絕種的動植物而言,瞭解其生態環境所需之各項條件是非常重要的,但通常這類物種的棲息地區是很難以地面調查的方式進行探勘。目前較可行的方式為利用衛星觀測資料,結合地理資訊系統的分析,完成物種棲息地生態環境之測繪和監測。 因此,本研究的主要目標即為利用衛星觀測資料(Landsat ETM+ 7及ASTER)所提供之地形及環境等參數,建立適合棲息的指標,探討印尼Baluran國家公園適合瀕臨絕種的野生牛(Banteng)棲息地區之生態環境參數,期能提供其保護區相關規劃之參考。本文所探討的生態參數包括地表覆蓋種類、植生指數 (Normalized Difference Vegetation Index; NDVI)及土壤水氣含量 (Soil Moisture Index; SMI),而地形參數則為坡度及坡向。在各參數的分析,則將配合現場調查野生牛棲息的分布地區,透過地理資訊系統之分析,進行各項參數之評分與加權,最後將整合各參數並建立一適合野生牛(Banteng)棲息地區的評估指標- HSI (Habitat Suitability Index)。 研究結果顯示,最適合評估Baluran國家公園野生牛棲息地區的權重組合為生態參數權重0.75及地形參數權重0.25。此外,Baluran國家公園極適合野生牛的棲息地區約佔18.5 %,合適的地區約佔23.8 %,主要分佈於Baluran國家公園的東南方和西南方地區,極適合規劃為野生牛(Banteng)的保護地區,而低適合度和完全不適合的區域分別約為20.1 %及19.11 %,大都分佈於Baluran國家公園的北方。The knowledge of ecological requirements and distributions of endangered species is a primary prerequisite to identify potential habitat for the species. But the potential habitat sites are usually difficult to access thus hard to investigate by traditional ground survey. With the capability of remotely sensed observations for wide area, satellite imagery combined with Geographic Information Systems (GIS) seems to be the best means for mapping and monitoring biodiversity at present. The main aim of this study is to develop habitat suitability index (HSI) of banteng at Baluran National Park (BNP) based on biologic and topographic variable that were derived from remote sensing imagery data. The biologic variables consist of three sub variables; land cover map, Normalized Difference Vegetation Index (NDVI) map and Soil Moisture Index (SMI) map, which are derived from Landsat ETM+ 7. The topographic variables consist of elevation and slope map of the study area which are derived from ASTER GDEM. Analysis of banteng habitat suitability was conducted spatially using scoring, weighting and overlaying methods. Each layer of habitat variable/sub-variable was grouped into five classes and scored based on the habitat selection of banteng, with the highest score represent the area with very high suitability and lowest score represent unsuitable area for banteng. The calculation of weight value is done using the extension tool of Analytical Hierarchy Process (AHP) in ArcGIS 9.2 software. The Saaty’s pair-wise comparisons were applied for each habitat variable/sub-variable compared with the others to calculate the weight value of each habitat variable/sub- variable. The layer of biologic variable was produced with combination of weight value of 0.32 for land cover type, 0.12 for NDVI map and 0.56 for SMI map. The topographic variable was produced using elevation and slope map with 0.5 of weight value for each layer respectively. The final result of this study is HSI of banteng, which is calculated using weight value of 0.75 for biology variable and 0.25 for topographic variable. These biologic and topographic variables were superimposed to get a layer of banteng habitat suitability index. The result shows that only 18.5% of BNP area which is very high suitable for banteng and 23.8% of BNP area is high suitable. 19.1% and 20. 1% of BNP areas were classified as unsuitable and low suitable area for banteng habitat. Based on the HSI map of banteng at BNP, most suitable area for banteng are located at southeast and southwest part of BNP, especially at Bitakol, Bama and Perengan Resorts and most of unsuitable area for banteng is located on north part of BNP.
    Appears in Collections:[遙測科技碩士學位學程] 博碩士論文

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