• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• Carbon letters
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• 제13권4호
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• pp.254-259
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• 2012

Nanoporous non-woven carbon fibers for a gas sensor were prepared from a pitch/polyacrylonitrile (PAN) mixed solution through an electrospinning process and their gas-sensing properties were investigated. In order to create nanoscale pores, magnesium oxide (MgO) powders were added as a pore-forming agent during the mixing of these carbon precursors. The prepared nanoporous carbon fibers derived from the MgO pore-forming agent were characterized by scanning electron microscopy (SEM), $N_2$-adsorption isotherms, and a gas-sensing analysis. The SEM images showed that the MgO powders affected the viscosity of the pitch/PAN solution, which led to the production of beaded fibers. The specific surface area of carbon fibers increased from 2.0 to $763.2m^2/g$ when using this method. The template method therefore improved the porous structure, which allows for more efficient gas adsorption. The sensing ability and the response time for the NO gas adsorption were improved by the increased surface area and micropore fraction. In conclusion, the carbon fibers with high micropore fractions created through the use of MgO as a pore-forming agent exhibited improved NO gas sensitivity.

• 대한원격탐사학회지
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• 제28권6호
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• pp.661-670
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• 2012

Urban forests provide great ecosystem services to population in metropolitan areas even though they occupy little green space in a huge gray landscape. Unfortunately, urbanization inherently results in threatening the green infrastructure, and the recent urbanization trends drew great attention of scientists and policy makers on how to preserve or restore green infrastructure in metropolitan area. For this reason, mapping the spatial distribution of the green infrastructure is important in urban environments since the resulting map helps us identify hot green spots and set up long term plan on how to preserve or restore green infrastructure in urban environments. As a preliminary step for mapping green infrastructure utilizing multi-source remote sensing data in urban environments, the objective of this study is to map vegetation volume by fusing LiDAR and multispectral data in urban environments. Multispectral imageries are used to identify the two dimensional distribution of green infrastructure, while LiDAR data are utilized to characterize the vertical structure of the identified green structure. Vegetation volume was calculated over the metropolitan Chicago city area, and the vegetation volume was summarized over 16 NLCD classes. The experimental results indicated that vegetation volume varies greatly even in the same land cover class, and traditional land cover map based above ground biomass estimation approach may introduce bias in the estimation results.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.349-352
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• 2007

The Fourth Assessment Report of IPCC predicted that global warming is already happening and it should be caused from the increase of greenhouse gases by the extension of human activities. These global changes will give a serious influence for human society. Global environment can be monitored by the earth observation using satellite. For the observation of global climate change and resolving the global warming process, satellite should be useful equipment and its detecting data contribute to social benefits effectively. JAXA (former NASDA) has made a new plan of the Global Change Observation Mission (GCOM) for monitoring of global environmental change. SGLI (Second Generation GLI) onboard GCOM-C (Climate) satellite, which is one of this mission, provides an optical sensor from Near-DV to TIR. Characteristic specifications of SGLI are as follows; 1) 250 m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500 m resolutions temperature over land and area along shore. These characteristics are useful in many fields of social benefits. For example, multi-angular observation and 250 m high frequency observation give new knowledge in monitoring of land vegetation. It is expected that land products with land aerosol information by polarization observation are improved remarkably. We are studying these possibilities by ground data and satellite data.

• 센서학회지
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• 제27권1호
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• pp.13-20
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• 2018

Gas sensors based on metal oxide semiconductors are used in numerous applications including monitoring indoor air quality and detecting harmful substances like volatile organic compounds. Nanostructures, for example, nanoparticles, nanotubes, nanodomes, and nanofibers have been widely utilized to improve gas sensing properties of metal oxide semiconductors, and this increases the effective surface area, resulting in participation of more target gas molecules in the surface reaction. In the recent times, 1-dimensional (1D) metal oxide nanostructures fabricated using anodic oxidation have attracted great attention due to their high surface-to-volume ratio with large-area uniformity, reproducibility, and capability of synthesis under ambient air and pressure, leading to cost-effectiveness. Here, we provide a brief overview of 1D metal oxide nanostructures fabricated by anodic oxidation and their gas sensing properties. In addition, recent progress on thin film-based anodic oxidation for application in gas sensors is introduced.

• 대한원격탐사학회지
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• 제34권1호
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• 대한원격탐사학회지
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• 제34권1호
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• pp.141-150
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• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• 센서학회지
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• 제19권5호
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• pp.385-390
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• 2010

CO sensing thick film gas sensors using $Co_3O_4$ powders prepared by hydrothermal reaction method, were fabricated, and their structural, electrical and CO gas sensing properties were investigated. The specific surface area of the $Co_3O_4$ powders obtained from BET analysis was about 79.0 $m^2/g$. XRD and SEM results show that the thick films heat-treated at $500^{\circ}C$ for 30 min after screen printing had the preferred orientation of (311) direction and the crystalline size was calculated to 221 $\AA$. The maximum activation energy obtained from the temperature-resistance characteristics was 3.11 eV in the temperature range of $290^{\circ}C$ to $310^{\circ}C$. The sensitivity to 1,000 ppm CO was about 150 %. The specific surface area, crystalline size, and maximum activation energy were increased significantly and the sensitivity for CO gas was improved largely.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1255-1257
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• 2003

This study proposes a single-channel satellite remote sensing algorithm for retrieving aerosol optical thickness over global ocean using FY-1C/1D data. An efficient lookup table (LUT)method is adopted in this algorithm to generate apparent reflectance in channel 1 and channel 2 of FY-1C/1D over ocean. The algorithm scale the apparent reflectance in cloud-free conditions to aerosol optical thickness using a state-of-art radiative transfer model 6S with input of the relative spectral response of channel 1 and 2 of FY-1C/1D. Monthly mean composite maps of the aerosol optical thickness have been obtained from FY-1C/1D global area coverage data between 2001 and 2003. Aerosol optical thickness maps can show the major aerosol source which are located off the west coast of northern and southern Africa, Arabian Sea and India Ocean. These result is very similar to other satellite sensors such as AVHRR and MODIS in the location area of heavy aerosol optical thickness over global ocean. The algorithm have been used to FY-1D operational performance and it is the first operational aerosol remote sensing product in China.

• 대한원격탐사학회지
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• 제19권1호
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• pp.21-30
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• 2003

It was studied the relationship between the red tide occurrence and the meteorological and oceanographic factors, the choice of potential area for red tide occurrence, and the satellite monitoring for red tide. From 1990 through 2001, the red tide continuously appeared and the number of red tide occurrence increased every year. Then, the red tide bloomed during the periods of July and August. An important meteorological factor governing the mechanisms of the increasing in number of red tide occurrence was heavy precipitation. Oceanographic factors of favorable marine environmental conditions for the red tide formation included warm water temperature, low salinity, high suspended solid, low phosphorus, low nitrogen. A common condition for the red tide occurrence was heavy precipitation 2∼4 days earlier, and the favorable conditions for the red tide formation were high air temperature, proper sunshine and light winds for the day in red tide occurrence. From satellite images, it was possible to monitor the spatial distributions and concentrations of red tide. It was founded the potential areas for red tide occurrence in August 2000 by CIS conception: Yeosu∼Dolsan coast, Gamak bay, Namhae coast, Marado coast, Goheung coast, Deukryang bay, respectively.