• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.297-305
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• 2012

This study was performed to estimate forest canopy density (FCD) using airborne hyperspectral data acquired in the Independence Hall of Korea in central Korea. The airborne hyperspectral data were obtained with 36 narrow spectrum ranges of visible (Red, Green, and Blue) and near infrared spectrum (NIR) scope. The FCD mapping model developed by the International Tropical Timber Organization (ITTO) uses vegetation index (VI), bare soil index (BI), shadow index (SI), and temperature index (TI) for estimating FCD. Vegetation density (VD) was calculated through the integration of VI and BI, and scaled shadow index (SSI) was extracted from SI after the detection of black soil by TI. Finally, the FCD was estimated with VD and SSI. For the estimation of FCD in this study, VI and SI were extracted from hyperspectral data. But BI and TI were not available from hyperspectral data. Hyperspectral data makes the numerous combination of each band for calculating VI and SI. Therefore, the principal component analysis (PCA) was performed to find which band combinations are explanatory. This study showed that forest canopy density can be efficiently estimated with the help of airborne hyperspectral data. Our result showed that most forest area had 60 ~ 80% canopy density. On the other hand, there was little area of 10 ~ 20% canopy density forest.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.403-406
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• 2005

In order to evaluate the Capability of ETM+ remotely- sensed data to provide 'Forest-shrub land-Rangeland' cover type map in areas near the timberline of northern forests of Iran, the data were analyzed in a portion of nearly 790 ha located in Neka-Zalemroud region. First, ortho-rectification process was used to correct the geometric errors of the image, yielding 0/68 and 0/69 pixels of RMS. error in X and Y axis, respectively. The original and panchromatic bands were fused using PANSHARP Statistical module. The ground truth map was made using 1 ha field plots in a systematic-random sampling grid, and vegetative form of trees, shrubs and rangelands was recorded as a criteria to name the plots. A set of channels including original bands, NDVI and IR/R indices and first components of PCI from visible and infrared bands, was used for classification procedure. Pair-wise divergence through CHNSEL command was used, In order to evaluate the separability of classes and selection of optimal channels. Classification was performed using ML classifier, on both original and fused data sets. Showing the best results of $67\%$ of overall accuracy, and 0/43 of Kappa coefficient in original data set. Due to the results represented above, it's concluded that ETM+ data has an intermediate capability to fulfill the spectral variations of three form- based classes over the study area.

• Journal of the Korean Institute of Landscape Architecture
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• v.35 no.1 s.120
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• pp.79-87
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• 2007

The objective of this study was to delineate forest patches in the cities around the Geum-buk mountains at the north of the Geum River using multiplesatellite remote sensing data. Landsat visible and near-infrared satellite images obtained at multiple dates in the growing season were used to create a forest distribution map. Fragstats 3.3 was used to get the landscape indices delineating the distribution of forest patches. Additional ground truth data was used to assess the accuracy of the classification. Factor analysis was used to get the 26 landscape indices clustered into 4 factors. Factor I was labeled as' size of forest patches', factor II as 'fragmentation of forest patches', factor III as 'shape of forest patches', and factor IV as 'complexity of forest patches'. Factor I described large patches and their core area, while others did small patches and their shape and complexity. Cities including Cheonan, Gongju, Cheongyang, and Boryeong near the main ridge of the Geumbuk Mtns. had a small number of large-sized forest patches. However, cities including Taean, Seosan, Dangjin, Hongseong near the ridge of the western Geumbuk Mtns. had a large number of small-sized forest patches. Finally, this study showed that the region near the coast line in Chung-nam province has various types of forest patches having an irregular forest edge due to the elevation and slope lower than the one of the region far from the coast line which is near the ridge of the Geum-buk Mountains. Remote sensing data were useful to understand the distribution of forest patches, and landscape indices could be keys to delineate the relationship between forest patches. And the factor analysis, which simplified 26 landscape indices into 4 landscape patterns allowed us to understand the distribution and relationship of forest patches in an easy way.

• Proceedings of the KSRS Conference
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• v.1
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• pp.86-89
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• 2006

Ocean color remote sensing community currently uses the different solar irradiance spectra covering the visible and near-infrared in the calibration/validation and deriving products of ocean color instruments. These spectra derived from single and / or multiple measurements sets or models have significant discrepancies, primarily due to variation of the solar activity and uncertainties in the measurements from various instruments and their different calibration standards. Thus, it is prudent to examine model-to-model differences and select a standard reference spectrum that can be adopted in the future calibration and validation processes, particularly of the first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meterological Satellite (COMS) planned to be launched in 2008. From an exhaustive survey that reveals a variety of solar spectra in the literature, only eight spectra are considered here seeing as reference in many remote sensing applications. Several criteria are designed to define the reference spectrum: i.e., minimum spectral range of 350-1200nm, based completely or mostly on direct measurements, possible update of data and less errors. A careful analysis of these spectra reveals that the Thuillier 2004 spectrum seems to be very identical compared to other spectra, primarily because it represents very high spectral resolution and the current state of the art in solar irradiance spectra of exceptionally low uncertainty ${\sim}0.1%.$ This study also suggests use of the Gueymard 2004 spectrum as an alternative for applications of multispectral/multipurpose satellite sensors covering the terrestrial regions of interest, where it provides spectral converge beyond 2400nm of the Thuillier 2004 spectrum. Since the solar-activity induced spectral variation is about less than 0.1% and a large portion of this variability occurs particularly in the ultraviolet portion of the electromagnetic spectrum that is the region of less interest for the ocean color community, we disregard considering this variability in the analysis of solar irradiance spectra, although determine the solar constant 1366.1 $Wm^{-2}$ to be proposed for an improved approximation of the extraterrestrial solar spectrum in the visible and NIR region.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.81-86
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• 2010

The urban thermal environment can be an important index to detect heat island phenomena and manage it to improve urban life quality. Cheongju is a typical plain-city that main part has been formed and developed in lowland. The Mushim stream crosses the city from south to north. We reviewed the use of thermal remote sensing in stream around areas and the thermal environments, focusing primarily on the Urban Heat Island(UHI) effect. The purpose of this study is to determine the relationship between the stream nearby urban area and the stream cooling effect of UHI. The objectives are to determine the usefulness of KOMPSAT-2 bands MS3 and MS4 for vegetation cover mapping, and the usefulness of LANDSAT TM band 6 in identifying thermal environmental characteristics and UHI. Land Surface Temperatures (LST) are retrieved by single-channel algorithm to study the UHI from the 6th band (thermal infrared band) of LANDSAT TM images and thermal radiance thermometer based on remote sensing method and the LST distribution maps are accomplished according to the retrieval results. There is also comparison of satellite-derived and in situ measured temperature. The results indicated that the LST of urban center is higher than that of suburban area, the temperature of mountain and water are the lowest area, so it is clearly proved that there are obvious UHI effects by stream. The surface temperature distribution of Mushim stream is detected $2^{\circ}C$ lower than urban area.

• Applied Chemistry for Engineering
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• v.31 no.4
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• pp.411-415
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• 2020

In this article, the preparation of hydrogels containing conducting polymer@lignin hybrids and their application to sensing materials were demonstrated using diverse techniques. A conducting polymer, polypyrrole (PPy) was polymerized on the surface of lignin and successful formation was analyzed with Fourier-transform infrared spectroscopy and scanning electron microscopy. Subsequently, PPy@lignin hybrids were mixed with a hydrogel matrix to obtain a conductive hydrogel. The feasibility of using the hydrogel as a sensing material was shown by obtaining reasonable sensing signals using various electrical measurements when adding solvents and solutions to the sensor system. The significance of sensor signals was confirmed with complementary experiments. This study shows that the hydrogel containing the PPy@lignin could be used for sensor applications.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.28-34
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• 2018

This paper is composed of a passenger management system using a temperature sensing module, a PIR sensor module for detecting movement inside a room, and a smart breath sensing module for determining a sleeping state. An embedded sensor module and a communication system integrated the sensing part and the algorithm driving part. As the aging society is accelerating and becoming more upgraded, the social cost of Silver Care increases, and in order to protect privacy, it is necessary to reduce costs by developing efficient smart silver care devices. The proposed non - image human body detection IOT sensor system is implemented by hardware and software and has superior performance compared with conventional image monitoring method.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.721-727
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• 2002

Precipitation evapotranspiration and runoff are three key parameters of regional water balance. Problems exist in the traditional methods for calculating such factors , such as explaining of the geographic rationality of spatial interpolating methods and lacking of enough observation stations in many important area for bad natural conditions. With the development of modern spatial info-techniques, new efficient shifts arose for traditional studies. Guided by theories on energy flow and materials exchange within Soil-Atmosphere-Plant Continuant (SPAC), retrieval models of key hydrological parameters were established in the Yellow River basin using CMS-5 and FengYun-2 meteorological satellite data. Precipitation and evapotranspiration were then estimated: (1) Estimating tile amount of solar energy that is absorbed by the ground with surface reflectivity, which is measured in the visible wavelength band (VIS): (2) Assessing the partitioning of the absorbed energy between sensible and latent heat with the surface temperature, which was measured in the thermal infrared band (TIR), the latent heat representing the evapotranspiration of water; (3) Clouds are identified and cloud top levels are classified using both VIS and TIR data. Hereafter precipitation will be calculated pixel by pixel with retrieval model. Daily results are first obtained, which are then processed to decade, monthly and yearly products. Precipitation model has been has been and tested with ground truth data; meanwhile, the evapotranspiration result has been verified with Large Aperture Scintillometry (LAS) presented by Wageningen University of the Netherlands. Further studies may concentrate on the application of models, i.e., establish a hydrological model of the Yellow river basin to make the accurate estimation of river volume and even monitor the whole hydrological progress.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.