INDREX II - indonesian airborne radar experiment campaign over tropical forest in L- and P-band: first results

Hajnsek, Irena; Kugler, Florian; Papathanassiou, K.; Horn, Ralf; Scheiber, Rolf; Moreira, Alberto; Hoekman, D.H.; Davidson, Malcolm

doi:10.1109/igarss.2005.1525878

Cited by 19 publications

(16 citation statements)

References 6 publications

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“…In Indonesia, the usage of PolInSAR through INDREX-II airborne campaign was initiated in 2004 (Hajnsek et al, 2005). The campaign was conducted to develop database of aboveground biomass in Kalimantan forests by using L-and P-bands in polarimetric and interferometric components using Experimental Synthetic Aperture Radar (E-SAR) of the German Aerospace Center (DLR).…”

Section: Resultsmentioning

confidence: 99%

Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest)

et al. 2017

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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 R 2 =0.7525 (standard deviation of tree heights is 2.75 meters) to R 2 =0.4435 (standard deviation 4.68 meters) and R 2 =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.Keywords: Temporal Decorrelation, Carbon Stocks, PolInSAR, ALOS PALSAR. Abstrak. Penelitian ini bertujuan untuk meneliti pengaruh dekorelasi temporal dalam pendugaan cadangan karbon. Pendugaan cadangan karbon sangat penting untuk memahami daur karbon secara global in atmosfer terkait upaya mitigasi perubahan iklim. Teknik PolInSAR menggabungkan dua buah teknik pemetaan dengan citra Synthetic

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Section: Resultsmentioning

confidence: 99%

Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest)

et al. 2017

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“…Finally, the RVoG/non-RVoG map for this test site is also generated and displayed in Figure 19, where the same conclusions on the range-dependent validity of the model can be drawn. In addition, the river pixels do not fulfill the RVoG assumption since noise is dominant and the low vegetation areas (peat swamp, see also RGB images in [50]) surrounding the river appear also as non-RVoG zones, since the low volume is almost transparent to P-band signals and the response is mostly made up by ground returns. It is noted that on such areas the topography estimation by the line fitting approach yields correct values due to the high coherence present on them.…”

Section: ) Forestmentioning

confidence: 99%

“…As seen, the topographic height by the line fitting exhibits a small bias around 1 m whereas the phase from element (1,2) reveals a wider height distribution. According to [50], this is a peat swamp area; therefore, it is plausible that low and nonuniform vegetation could induce phase variations on (1,2) element. Nevertheless, this issue must be further investigated IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING and confirmed.…”

Section: ) Forestmentioning

confidence: 99%

A Simple RVoG Test for PolInSAR Data

Ballester-Berman

Vicente-Guijalba

López-Sánchez

2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Abstract-In this paper, we present a simple algorithm for assessing the validity of the RVoG model for PolInSAR-based inversion techniques. This approach makes use of two important features characterizing a homogeneous random volume over a ground surface, i.e., the independence on polarization states of wave propagation through the volume and the structure of the polarimetric interferometric coherency matrix. These two features have led to two different methods proposed in the literature for retrieving the topographic phase within natural covers, i.e., the well-known line fitting procedure and the observation of the (1, 2) element of the polarimetric interferometric coherency matrix. We show that differences between outputs from both approaches can be interpreted in terms of the PolInSAR modeling based on the Freeman-Durden concept, and this leads to the definition of a RVoG/non-RVoG test. The algorithm is tested with both indoor and airborne data over agricultural and tropical forest areas.

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“…Instruments placed along this bridge automatically measure rainfall and water level every hour. In December 2004, an airborne radar survey (the ESA INDREX-2 campaign) was carried out along this bridge to test a variety of advanced imaging radar techniques (Hajnsek et al, 2005;Hajnsek and Hoekman, 2006). The intention is to collect data over an extended period (i.e.…”

Section: Field Station and Hydrological Characterisationmentioning

confidence: 99%

Monitoring Tropical Peat Swamp Deforestation and Hydrological Dynamics by ASAR and PALSAR

Hoekman¹

2009

Geoscience and Remote Sensing

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INDREX II - indonesian airborne radar experiment campaign over tropical forest in L- and P-band: first results

Cited by 19 publications

References 6 publications

Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest)

Temporal Decorrelation Effect in Carbon Stocks Estimation Using Polarimetric Interferometry Synthetic Aperture Radar (PolInSAR) (Case Study: Southeast Sulawesi Tropical Forest)

A Simple RVoG Test for PolInSAR Data

Monitoring Tropical Peat Swamp Deforestation and Hydrological Dynamics by ASAR and PALSAR

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