IDENTIFIKASI HUTAN MANGROVE MENGGUNAKAN TEKNOLOGI PENGINDERAAN JAUH DI BALI BARAT

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ITS » Undergraduate Theses » Teknik Geodesi / Teknik Geomatika
Posted by dewi007 at 17/12/2009 16:33:11 • 3411 Views

IDENTIFIKASI HUTAN MANGROVE MENGGUNAKAN TEKNOLOGI PENGINDERAAN JAUH DI BALI BARAT

IDENTIFICATION MANGROVE FOREST BY USING REMOTE SENSING TECHNOLOGI IN WEST BALI

Created by :
Kurniawan, Achmad ( 3502100033 )

Subject:	Kontrol jarak jauh
Alt. Subject :	Remote Sensing Mangrove abration
Keyword:	identifikasi hutan mangrove penginderaan jauh

Description:

Hutan mangrove merupakan daerah yang dapat mencegah adanya abrasi pantai dan merupakan ekosistem air payau yang didalamnya terdapat berbagai jenis ikan dan udang. Oleh karena itu perlu dijaga agar tidak terjadi kerusakan dan mengetahui sebaran dari hutan mangrove. Salah satu metode untuk mengetahui sebaran hutan mangrove adalah dengan menggunakan teknologi penginderaan jauh. Penelitian ini menggunakan citra satelit Landsat dan citra satelit Spot untuk mengidentifikasi hutan mangrove, luas dan kerapatannya. Untuk citra satelit Landsat menggunakan klasifikasi terawasi dan algoritma Cresshours untuk identifikasi hutan mangrove dan mengetahui luasnya, sedangkan kerapatannya menggunakan NDVI dan algoritma Cresshours. Pada citra Spot menggunakan klasifikasi terawasi dalam megnidentifikasi dan mengetahui luasnya, dan kerapatannya menggunakan NDVI. Dari penelitian ini didapatkan luas hutan mangrove dari data citra Landsat dengan klasifikasi terawasi seluas 373,923 Ha dan dengan algoritma Cresshours seluas 371,519 Ha. Luas dari data citra Spot seluas 151,893 Ha. Untuk kerapatannya dapat dibagi menjadi 4 kelas yaitu kelas tak bervegetasi, kelas vegetasi kerapatan jarang, kelas vegetasi kerapatan sedang, dan kelas vegetasi kerapatan rapat.

Alt. Description

Mangrove is a region which can prevent shore abration and is a brackish ecosystem where there is varying fishes and prawns inside. Because of that, mangrove needs to be protected from damage and knowing the distribution of mangrove. One of the methods for knowing the distribution of mangrove by using remote sensing technology This research is using Landsat and SPOT satellite imagery for identifying mangrove, mangrove area, and mangrove density. Landsat satellite imagery is using controlled classification and Cresshour algorithm to identify mangrove and knowing mangrove area. For knowing mangrove density it using NDVI and Cresshours algorithm. SPOT satellite imagery is using controlled classification to identify mangrove and knowing mangrove area. For knowing Mangrove density it using NDVI. From this research, is obtained area of mangrove from Landsat satellite imagery data with controlled classification is about 373, 923 Ha and with Cresshours algorithm is about 371,519 Ha. Area of mangrove from SPOT satellite imagery is about 151,893 Ha. For density, it divided into 4 classes: non vegetative class, rare density vegetative class, middle density vegetative class, and dense density vegetative class

Contributor	:	Prof. DR. Ir. Bangun M.S., DEA, DESS Ariani Andayani SSi
Date Create	:	17/12/2009
Type	:	Text
Format	:	pdf.
Language	:	Indonesian
Identifier	:	ITS-Undergraduate-3100007028520
Collection ID	:	3100007028520
Call Number	:	RSG 621.367 8 Kur i

Source :
Undergraduate Theses of Geomatic Engineering, RSG 621.367 8 Kur i, 2006

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Copyright @2006 by ITS Library. This publication is protected by copyright and permission should be obtained from the ITS Library prior to any prohibited reproduction, storage in a retrievel system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permission(s), write to ITS Library

Publication URL :
http://digilib.its.ac.id/identifikasi-hutan-mangrove-menggunakan-teknologi-penginderaan-jauh-di-bali-barat-6256.html

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  3. ITS-Undergraduate-6256-3502100033-bab2.pdf - 169 KB
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  5. ITS-Undergraduate-6256-3502100033-bab4.pdf - 177 KB
  6. ITS-Undergraduate-6256-3502100033-kesimpulan.pdf - 22 KB
  7. ITS-Undergraduate-6256-3502100033-lampiran.pdf - 77 KB

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