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Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest) Jaya, Laode M Golok; Wikantika, Ketut; Sambodo, Katmoko Ari; Susandi, Armi
Forum Geografi Vol 31, No 1 (2017): July 2017
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v31i1.2518

Abstract

This paper was aimed to analyse the effect of temporal decorrelation in carbon stocks estimation. Estimation of carbon stocks plays important roles particularly to understand the global carbon cycle in the atmosphere regarding with climate change mitigation effort. PolInSAR technique combines the advantages of Polarimetric Synthetic Aperture Radar (PolSAR) and Interferometry Synthetic Aperture Radar (InSAR) technique, which is evidenced to have significant contribution in radar mapping technology in the last few years. In carbon stocks estimation, PolInSAR provides information about vertical vegetation structure to estimate carbon stocks in the forest layers. Two coherence Synthetic Aperture Radar (SAR) images of ALOS PALSAR full-polarimetric with 46 days temporal baseline were used in this research. The study was carried out in Southeast Sulawesi tropical forest. The research method was by comparing three interferometric phase coherence images affected by temporal decorrelation and their impacts on Random Volume over Ground (RvoG) model. This research showed that 46 days temporal baseline has a significant impact to estimate tree heights of the forest cover where the accuracy decrease from R2=0.7525 (standard deviation of tree heights is 2.75 meters) to R2=0.4435 (standard deviation 4.68 meters) and R2=0.3772 (standard deviation 3.15 meters) respectively. However, coherence optimisation can provide the best coherence image to produce a good accuracy of carbon stocks.  
PENGKAJIAN PEMANFAATAN DATA TERRA-MODIS UNTUK EKSTRAKSI DATA SUHU PERMUKAAN LAHAN (SPL) BERDASARKAN BEBERAPA ALGORITMA Prasasti , Indah; Sambodo, Katmoko Ari; Carolita , Ita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 4 No. 1 (2007)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v4i1.3190

Abstract

Land surface temperature (LST) is one primary parameters energy balance on the surface and also as primary climatology variable that controlling long-wave energy flux through atmosphere. The LST data is needed for drought estimating models which based on calculating of soil moisture lavel and/or evapotranspiration. TERRA satellite that brings sensor MODIS (Moderate Resolution Imaging Spectroradiometer) is an evironmental. Observation satellite that can be used for extracting LST data regionally. The MODIS relatively has width coverage; 2330 Km, and spatial resolution 250 m (1 and 2 channel) with high spectral resolution (36 channels), and temporal resolution that almost similar to the previous generation satellite called NOAA.
PEMANFAATAN CITA Pi-SAR2 UNTUK IDENTIFIKASI SEBARAN ENDAPAN PIROKLASTIK HASIL ERUPSI GUNUNGAPI GAMALAMA KOTA TERNATE Suwarsono, Suwarsono; Yudhatama, Dipo; Trisakti, Bambang; Sambodo, Katmoko Ari
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 10 No. 1 (2013)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v10i1.3268

Abstract

This research aims to identify the distribution of pyroclastic deposits from the eruption volcano by using Pi-SAR2 imagery. The object of research is Gamalama Volcano, located in the city of Ternate in North Maluku Province. Research methods include radiometric calibration Pi-SAR2 to get the value of backscatter intensity sigma naught, calculation of statistical values (mean, standard of deviation and coefficient of correlation between bands) backscatter intensity of sigma naught among pyroclastic deposits and other surface objects, as well as the separation distribution of pyroclastic deposits using thresholding methods. This research concludes that the Pi-SAR2 imagery can be used to identify the distribution of volcanic pyroclastic deposits from the eruption. Concurrent use of polarization HH, VV and HV will give better results than using a single polarization HH and VV. This research suggests further research to be done by applying the method of verification is supported by the use of field data (ground check).