• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.969-979
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• 2018

This paper presents reflection symmetry of polarimetric SAR over the Amazon rainforest in terms of correlation coefficients between the pairs of HH- and HV-pol and VV- and VH-pol data by ALOS PALSAR. The reflection symmetry is defined as a non-zero correlation between HH- and HV-pol and VV- and VH-pol over natural distributed targets, and is a fundamental assumption for cross-talk calibration coefficient computation and for three-component decomposition for polarimetric SAR data. The Amazon rainforest is especially one of the common global reference sites for the reflection symmetry. The correlation coefficients for the pairs of reflection symmetry obtained in this study range from 0.018 to 0.097. The results imply that there exists a non-negligible dependency between co-pol and cross-pol in the distributed natural targets, and consequently the non-zero correlation must be considered as a potential contribution to errors of spaceborne SAR polarimetry to some extent.

• Advances in environmental research
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• v.4 no.4
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• pp.247-262
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• 2015

The few lignin biomarker studies conducted in tropical environments are hampered by having to use references signatures established for plants and soils characteristic of the temperate zone. This study presents a lignin biomarker analysis (vanillyls (V), p-hydroxyls (P), syringyls (S), cinnamyls (C)) of the dominant plant species and soil horizons as well as an analysis of the interrelated terrigenous organic matter (TOM) dynamics between vegetation and soil of the $Tapaj{\acute{o}}s$ river region, an active colonization front in the Brazilian Amazon. We collected and analyzed samples from 17 fresh dominant plant species and 48 soil cores at three depths (0-5 cm, 20-25 cm, 50-55 cm) from primary rainforest, fallow forest, subsistence agriculture fields and pastures. Lignin signatures in tropical plants clearly distinguish from temperate ones with high ratios of Acid/aldehyde of vanillyls ((Ad/Al)v) and P/V+S. Contrary to temperate environments, similarly high ratios in tropical soils are not related to TOM degradation along with pedogenesis but to direct influence of plants growing on them. Lignin signatures of both plants and soils of primary rainforest and fallow forest clearly distinguish from those of non-forested areas, i.e., agriculture fields and pastures. Attalea speciosa Palm trees, an invasive species in all perturbed landscapes of the Amazon, exhibit lignin signatures clearly distinct from other dominant plant species. The study of lignin signatures in tropical areas thus represents a powerful tool to evaluate the impact of primary rainforest clearing on TOM dynamics in tropical areas.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.733-741
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• 2020

A smart dust monitoring system is useful for obtaining information on rough terrain that is difficult for humans to access. One of ways to deploy sensors to gather information in smart dust environment is to use an aircraft in the Amazon rainforest to scatter an enormous amount of small and cheap sensors (or smart dust devices), or to use an unmanned spacecraft to throw the sensors on the moon's surface. However, scattering an enormous amount of smart dust devices creates the difficulty of managing such devices as they can be scattered into inaccessible areas, and also causes problems such as bottlenecks, device failure, and high/low density of devices. Of the various problems that may occur in the smart dust environment, this paper is focused on solving the bottleneck problem. To address this, we propose and construct a three-layered hierarchical smart dust monitoring system that includes relay dust devices (RDDs). An RDD is a smart dust device with relatively higher computing/communicating power than a normal smart dust device. RDDs play a crucial role in reducing traffic load for the system. To validate the proposed system, we use climate data obtained from authorized portals to compare the system with other systems (i.e., non-hierarchical system and simple hierarchical system). Through this comparison, we determined that the transmission processing time is reduced by 49%-50% compared to other systems, and the maximum number of connectable devices can be increased by 16-32 times without compromising the system's operations.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1457-1468
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• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.