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

AFRIARINI, SASTIKA ZAHRA (2014) ANALISA KESESUAIAN ALGORITMA INDEKS VEGETASI LAHAN PERTANIAN KERING MENGGUNAKAN CITRA ALOS AVNIR-2. Masters thesis, Institut Teknologi Sepuluh Nopember.

Text 3512201009-Master_theses.pdf - Published Version Restricted to Repository staff only Download (2MB) | Request a copy

Abstract

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 111°47'05"-112°18’20’’ BT 7°36’12”-8°0’32” 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 2429,693 ha (16,402%) dan luas lahan ketela rambat 483,349 ha
(3,484%). MSAVI juga memiliki korelasi tinggi yaitu sebesar dengan luas jagung
2715,697 ha (19,573%) dan luas lahan ketela rambat 818,321 ha (5.898%).
Sedangkan algoritma lain memiliki korelasi sedang yaitu algoritma EVI dengan
luas lahan jagung 2275,802 ha (18,511%) dan luas lahan ketela rambat 240,182
(1,731%). NDVI memiliki korelasi rendah yaitu dengan luas lahan jagung
2169,456 ha (15,636%) dan luas lahan ketela rambat 343,64 ha (2,478%).

===================================================================================================

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
111°47'05"-112°18’20’’ BT 7°36’12”-8°0’32” 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 2429,693 ha (16,402%) and sweet
potato land area of 483,349 ha (3,484%).While other algorithms have a lower
correlation including MSAVI with corn land area of 2715,697 ha (19,573%) and
sweet potato land area of 818,321 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%).

Item Type:	Thesis (Masters)
Additional Information:	RTG 621.367 8 Afr a
Uncontrolled Keywords:	Normalized 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, Dry Farmland dan ALOS AVNIR-2
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.546 Computer algorithms
Divisions:	Faculty of Civil Engineering and Planning > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Anis Wulandari
Date Deposited:	30 Jan 2017 03:01
Last Modified:	30 Jan 2017 03:01
URI:	http://repository.its.ac.id/id/eprint/3902

Actions (login required)

View Item