PEMANFAATAN CITRA ALOS AVNR-2 UNTUK ESTIMASI PRODUKSI TANAMAN JATI DENGAN MENGGUNAKAN METODE TRANSFORMASI SPEKTRAL INDEKS VEGETASI (DAERAH KAJIAN : SEBAGIAN KABUPATEN GUNUNG KIDUL)

This study aimed to: (a) Assess the ability of ALOS AVNIR-2 imagery to identify teak plants, (b) Determine the best transformation of the vegetation index to estimate the production of teak plants and (c) Determine the details of spectral transformation methods of vegetation index. Area of this stud...

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Bibliographic Details
Main Authors: , MEYSITA NOORMASARI, , Dr. Sigit Heru Murti B S, S.Si. M.Si.
Format: Theses and Dissertations NonPeerReviewed
Published: [Yogyakarta] : Universitas Gadjah Mada 2014
Subjects:
ETD
Online Access:https://repository.ugm.ac.id/132341/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72870
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Institution: Universitas Gadjah Mada
Description
Summary:This study aimed to: (a) Assess the ability of ALOS AVNIR-2 imagery to identify teak plants, (b) Determine the best transformation of the vegetation index to estimate the production of teak plants and (c) Determine the details of spectral transformation methods of vegetation index. Area of this study is hardwood plants production BDH (Bagian Daerah Hutan) in a part of Gunungkidul regency. The methods that used in this study are transformation SAVI, RVI, ARVI, NDVI, and statistical data analysis regression. The primary data that used is recording of ALOS AVNIR-2 imagery in 2009. Regression worked in two step, first regression of index value in each transformation with canopy density in field. There is an R value that is a correlation coefficient showing the strengh and direction of correlation from variables that included. Second regression, used the log volume with the canopy density, in which used to make estimation model. Estimation model of hardwood production is log volume and the important thing of hardwood production comes from its log. The results of regression between transformation index with canopy density shows significancy. R values from NDVI is 0,766, ARVI is 0,576, RVI is 0,788, and SAVI is 0,745. Besides of R value there is SE (Standar Error) that used to determine model with the best transformation, SEE resulted from model accuration test between volume in the field and in the model. SEE values from NDVI is ±1,28 m�/piksel, ARVI is ±1,6 m�/piksel, RVI is ±1 m�/piksel, and SAVI is ±1,18 m�/piksel. From the result the best transformation model to estimate hardwood production RVI. Keywords : ALOS AVNIR-2 Imagery, Transformation Vegetation Index, Estimated Production, Teak Plants