Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Lingkungan Majalah Geografi Indonesia Jurnal Nasional Teknologi Terapan
Projo Danoedoro
Fakultas Geografi, Universitas Gadjah Mada
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Nasional Teknologi Terapan

 1 
Kajian Transformasi Indeks Vegetasi Citra Satelit Sentinel-2A untuk Estimasi Produksi Daun Kayu Putih Menggunakan Linear Spectral Mixture Analysis Lilik Norvi Purhartanto; Projo Danoedoro; Pramaditya Wicaksono
Jurnal Nasional Teknologi Terapan (JNTT) Vol 3, No 1 (2019): JULI
Publisher : Penelitian dan Pengabdian Kepada Masyarakat Sekolah Vokasi Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1066.098 KB) | DOI: 10.22146/jntt.56618

Abstract

A forest plantation area of Melaleuca cajuputi at BDH Karangmojo, BKPH Yogyakarta are 2,325.20 ha. One of the efforts to keep its sustainability is to plan the target and realization of cajuputi leaf production considerwith forest condition. Advances in remote sensing technology can be an alternative in estimating the cajuputi leaf production on large areas with an efficient time and high accuracy and able to analyze the quality of cajuputi. This study aims to examine Sentinel-2A capabilities through a relationship model of some vegetation indices integrated with vegetative factors on the production to obtain estimates of leaf production, map and test the estimation model accuracy. The method used is to classify objects in pixels with Linear Spectral Mixture Analysis and build relationship between age, number of plants and vegetation index with cajuputi leaf production. The results showed that the unmixing method has 99,66% accuracy in classifying pixels into the fraction of cajuputi. MERIS Terrestrial Chlorophyll Index of unmixing cajuputi fraction simultaneously with age and number of plants has the highest correlation with value of r = 0,668 to the production and modeled in mapping the estimated cajuputi leaf production at the research location with Standard Error of Estimate is 0,183.
Co-Authors Aria Jaka Dwiputra Hartono Hartono Lilik Norvi Purhartanto Nursida Arif Pramaditya Wicaksono R. Suharyadi