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...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Theses and Dissertations NonPeerReviewed |
| منشور في: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| الموضوعات: | |
| الوصول للمادة أونلاين: | 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 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| الملخص: | 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 |
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