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Journal : Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital

PENGEMBANGAN METODE PENENTUAN INDEKS LUAS DAUN PADA PENUTUP LAHAN HUTAN DARI DATA SATELIT PENGINDERAAN JAUH SPOT-2 Suwarsono, Suwarsono; Arief, Muchlisin; Hidayat, Hidayat; Sulma, Sayidah; Suryo H, Nanik; Sulyantoro, Heri; Setiawan, Kuncoro Teguh
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 8 No. 1 (2011)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v8i1.3250

Abstract

It is necessary to develop the methods of Leaf Area Index (LAI) estimation based on satellite remote sensing data as first step to study the carbon storage and carbon emission which affect to global climate change. Direct measurements of Leaf Area Index in the field are expensive, take a long time, and so inefficient. The application of remote sensing data may gives an appropriate solution for Leaf Area Index estimation by more efficient and effective. Objective of the research is to develop the method of Leaf Area Index estimation by using remote sensing data. The method of Leaf Area Index estimation will be developed by using the reference method taken from back up algorithm of the Algorithm Theoretical Basis Document (ATBD) MOD15. The research will try to develop the model and applicate it for another remote sensing data, especially those of acquired or distributed by Indonesian National Institute of Aeronautics and Space (LAPAN) such as SPOT-2. Results of the research show that the LAI based on MOD 15 has low correlation with the measured LAI, but the measured LAI has good correlation with NDVI from SPOT-2 for forest area.
ESTIMASI BATIMETRI DARI DATA SPOT 7 STUDI KASUS PERAIRAN GILI MATRA NUSA TENGGARA BARAT Setiawan, Kuncoro Teguh; Manessa, Masita Dwi Mandini; Winarso, Gathot; Anggraini, Nanin; Giarrastowo, Gigih; Asriningrum, Wikanti; Herianto, Herianto; Rosid, Syamsu; Supardjo, A. Harsono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v15i2.3342

Abstract

Indonesia is an archipelagic state consists of five large islands and thousands of small islands surrounded by shallow marine waters. For this reason, complete and accurate bathymetric information is needed. Large scale bathymetry data in Indonesian waters is still limited, including in the shallow sea waters of Gili Matra, NTB Province. To overcome these problems, remote sensing technology is used. The aim of the study was to analyze the effect of shallow marine habitat base objects on estimating bathymetry from SPOT 7 satellite images. Many methods can be used to produce estimated bathymetry with this technology. The analysis used in this study is multiple linear regression (MLR). The data used is SPOT 7 satellite imagery in the shallow sea waters of Gili Matra, West Nusa Tenggara Province. The estimation of bathymetry was carried out using insitu depth data with two modifications. The first modification did not pay attention to the basic habitat object types and the second modification paid attention to the coral habitat, seagrass, macroalgae and substrate objects. The results of this study provide the value of determination R2 which increased from 72.1% to 78.6% and decreased the RMSE value from 3.3 meters to 2.9 meters.