Landsdlide Identification and Landslide Vegetation Recovery Analysis Using GIS and Remote Sensing Techniques-A Study CAse in El Cajon Reservoir and Choluteca River Watersheds, Honduras, C.A.

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Title:	Landsdlide Identification and Landslide Vegetation Recovery Analysis Using GIS and Remote Sensing Techniques-A Study CAse in El Cajon Reservoir and Choluteca River Watersheds, Honduras, C.A.
Authors:	柯明格;Miguel Valdez
Contributors:	國際環境永續發展碩士在職專班國際專班
Keywords:	衛星影像;山崩地;植生復育;GIS.;NDVI;Remote Sensing;Landslides;Vegetation Recovery;Watershed
Date:	2008-06-26
Issue Date:	2009-09-21 09:58:27 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	宏都拉斯因一再遭受自然災害而受傷頗重，其中山崩可能是最普遍和最具破壞的自然災害。宏都拉斯史無前例的大規模自然災害是1998年的米奇颶風，估計全國70%的道路網遭山崩破壞，同時造成將近1,000個人命喪生。因大量植被及根深葉茂有助於穩定土壤及減緩山崩，所以本論文主要目是研究米奇颶風災後山崩的植生復育情況。基於地方政府在米奇颶風災後復原的優先考量下，本論文選擇El Cajon水庫集水區的5個郡及Choluteca流域集水區的14個郡為測試區。首先利用米奇颶風(1998)前的Landsat衛星影像 (1996)、及米奇颶風後的Landsat衛星影像(1999)以植生指標(NDVI)找出災後的山崩地位置。結果顯示El Cajon有162處山崩地佔面積547.99 Has，Choluteca有817處山崩地佔面積 959.45Has，兩個測試區總共找到979處山崩地佔面積1507.44547.99 Has。衛星影像所萃取出的山崩地，在本研究也利用地真資料及資料探勘方式驗證其精確度，結果顯示有70%的精確度。至於山崩地的復育則利用2003年及2007年的Landsat衛星影像，以植生指標(NDVI)方式找出1999-2003及2003-2007兩時期的植生復育情況。El Cajon分別在2003年有84.8%的植生復育及在2007年有 89.6%的植生復育，顯示相當高的植生復育率。Choluteca則分別在2003年有20.23%的植生復育及在2007年有 33.32%的植生復育。植生復育分析結果顯示Choluteca的山崩地非常需要人工植生復育，而El Cajon人工植生復育則較無急迫性。本研究所研發的方法可提供決策者分析災後山崩地的復育情況，作為未來民眾受災後遷移政策的規劃，及山崩地災害的管理。 In a recurrent way Honduras has been exposed to natural disasters as a result of its local vulnerability. Landslides are possibly the most common and destructive natural disasters in Honduras. The arrival of Hurricane Mitch in Honduras in 1998 produced effects that were unprecedented in their wide-spread nature throughout the country. Estimations indicate that landslides damaged 70% of the road network in Honduras and nearly 1,000 fatalities. Abundant vegetation and deep roots are helpful to have stable soils and to limit the amount potential of a landslide. For this, the aim and objectives of developing the landslide identification after Hurricane Mitch and its vegetation recovery using satellite images from 1996, 1999 for the landslide identification, and 2003 and 2007 landsat images for the vegetation recovery. The study area selected was in response to the priorization developed by local authorities. In El Cajon reservoir watershed 5 counties were selected and in Choluteca River watershed 14 counties. Landslides were identified using NDVI calculated from the Landsat scenes from 1996, previous Hurricane Mitch, and 1999 scene after the Hurricane. The results show an occurrence of 162 landslides in “El Cajon” Reservoir with a total landslide area of 547.99 Has. 817 landslide events in Choluteca River watershed with a total landslide area of 959.45 making a total of 979 landslides and a landslide area of 1507.44 Has. To assess the landslide identification, ground truth was intersected with them. Another technique to asses it was a Probability map generated using the Data mining analysis. The Vegetation recovery of these landslides identified was calculated for two periods, 1999-2003 and 2003-2007 using NDVI calculated from the Landsat images year 2003 and 2007. In “El Cajon” Reservoir watershed, in the year 2003 the vegetation recovery rate is 84.8% and the Vegetation recovery rate by the year 2007 is 89.6% showing a very high rate of recovery. For Choluteca river watershed area the situation is not so good. The recovery rates by the year 2003 are 20.23%, and by the year 2007 the recovery rate is: 33.32%. The data statistics generated reflect the need of artificial vegetation for the disturbed areas in Choluteca river watershed although for El Cajon reservoir watershed area, the artificial vegetation recovery is not required. This research can become a tool for decision makers in order to assess the recovery of landslides for future planning and reorganization of human settlements as well as techniques for natural disasters management planning in the field of landslides.
Appears in Collections:	[International Environment Sustainable Development Program] Electronic Thesis & Dissertation

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