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ITS » Paper and Presentation » S2 - Teknik Geomatika
Posted by aprill@is.its.ac.id at 30/09/2015 18:17:35  •  1731 Views


ANALISA KESESUAIAN ALGORITMA INDEKS VEGETASI LAHAN PERTANIAN KERING MENGGUNAKAN CITRA ALOS AVNIR-2

ANALYSIS OF SUITABILITY OF DRY FARMLAND VEGETATION INDEX ALGORITHM USING ALOS AVNIR-2

Author :
AFRIARINI, SASTIKA ZAHRA ( 3512 201 009 )




ABSTRAK

Lahan Pertanian kering digunakan untuk tujuan budidaya pertanian yang bukan padi seperti jagung ketela dsb. Lahan tersebut berada di dataran rendah daerah pegunungan yang dilalui aliran sungai seperti Kabupaten Kediri yang terletak antara 11147 05-11218 20 BT 736 12-80 32 LS. Indeks vegetasi adalah suatu formulasi pengolahan data penginderaan jauh untuk mengkaji informasi tematik dari lahan bervegetasi. Dalam penelitian ini digunakan citra satelit penginderaan jauh ALOS AVNIR-2 untuk membandingkan nilai indeks vegetasi di lahan pertanian kering menggunakan algoritma Normalized Different Vegetation Index NDVI Enhanced Vegetation Index EVI Soil Adjusted Vegetation Index SAVI Modified Soil Adjusted Vegetation Index MSAVI. Dari penelitian ini diperoleh nilai korelasi yang tinggi terhadap kondisi lahan pertanian kering dengan memperhatikan nilai indeks vegetasi yang sesuai digunakan sebagai dasar untuk pemetaan lahan pertanian kering di Kecamatan Pagu Kabupaten Kediri. Hasil dari penelitian ini menunjukkan nilai korelasi tertinggi pada algoritma SAVI dengan hasil ground truth yang memiliki korelasi tertinggi yaitu dengan luas lahan jagung 2429693 ha 16402 dan luas lahan ketela rambat 483349 ha 3484. MSAVI juga memiliki korelasi tinggi yaitu sebesar dengan luas jagung 2715697 ha 19573 dan luas lahan ketela rambat 818321 ha 5.898. Sedangkan algoritma lain memiliki korelasi sedang yaitu algoritma EVI dengan luas lahan jagung 2275802 ha 18511 dan luas lahan ketela rambat 240182 1731. NDVI memiliki korelasi rendah yaitu dengan luas lahan jagung 2169456 ha 15636 dan luas lahan ketela rambat 34364 ha 2478.


ABSTRACT

Dry farmland is used for non-rice cultivation such as maize cassava etc. One example of the dry farmland is in the Kediri district precisely in lowland mountainous area which is traversed by watershed which is located between 11147 05-11218 20 BT 736 12-80 32 LS. The research in this thesis is related to the identification of dry farmland in the district of Kediri using vegetation index algorithm. Vegetation index is a formulation for processing of remote sensing data to assess the thematic information of vegetated land. In this research satellite remote sensing imagery ALOS AVNIR-2 is used to compare the vegetation index values in dry farmland using algorithm of Normalized Different Vegetation Index NDVI Enhanced Vegetation Index EVI Soil Adjusted Vegetation Index SAVI and Modified Soil Adjusted Vegetation Index MSAVI. From this research obtained a high correlation value of dry farmland condition with regard to the vegetation index value which can be used as a basis for making dry farmland map in Pagu sub-district Kediri district. The results of this research shows the highest correlation value is at the algorithm of SAVI with corn land area of 2429693 ha 16402 and sweet potato land area of 483349 ha 3484.While other algorithms have a lower correlation including MSAVI with corn land area of 2715697 ha 19573 and sweet potato land area of 818321 ha 5.898. EVI with corn land area of 2275.802 ha 18.511 and sweet potato land area of 240.182 ha 1.731 NDVI with corn land area of 2169.456 ha 15.636 and sweet potato land area of 343.64 ha 2.478.



KeywordsNormalized Different Vegetation Index (NDVI); Enhanced Vegetation Index (EVI); Soil Adjusted Vegetation Index (SAVI) Modified Soil Adjusted Vegetation Index (MSAVI); Lahan pertanian kering dan ALOS AVNIR-2
 
Subject:  penginderaan
Contributor
  1. Dr. Ir. Muhammad Taufik
Date Create: 30/09/2015
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-paper-35121150007974
Collection ID: 35121150007974
Call Number: RTG 621.367 8 Afr a


Source
Paper and Presentations, Geomatics Engineering, RTG 551.307 Roc s, 2015

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Copyright @2015 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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