• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.121-132
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• 2016

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.341-350
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• 2008

Change detection has been recognized as one of the most important steps to update city models. In this study, we thus propose a method to detect urban changes from two sets of LIDAR data acquired at different times. The main processes in the proposed method are (1) detecting change areas through subtraction between two DSMs generated from the LIDAR sets, (2) organizing the LIDAR points within the detected areas into surface patches, (3) classifying the class of each patch such as ground, vegetation, and building, and (4) determining the kinds of changes based on the properties and classes of the patches. The results which were obtained from the application of the proposed method to real data were verified as appropriate using the reference data manually acquired from the visual inspection of the orthoimages of the same area. The probability of success in change detection is assessed to 97% on an average. In conclusion, the proposed method is evaluated as a reliable, and efficient approach to change detection and thus the update of city model.

• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.25-37
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• 2013

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.495-502
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• 2016

Italian Ryegrass (IRG), which is known as high yielding and the highest quality winter annual forage crop, is grown in mid-south area in Korea. The objective of this study was to evaluate the use of unmanned aerial vehicle (UAV) for the monitoring IRG growth. Unmanned aerial vehicle imagery obtained from middle March to late May in Nonsan, Chungcheongnam-do. Unmanned aerial vehicle imagery corrected geometrically and atmospherically to calculate normalized difference vegetation index (NDVI). We analyzed the relationships between $NDVI_{UAV}$ of IRG and biophysical measurements such as plant height, fresh weight, and dry weight over an entire IRG growth period. The similar trend between $NDVI_{UAV}$ and growth parameters was shown. Correlation analysis between $NDVI_{UAV}$ and IRG growth parameters revealed that $NDVI_{UAV}$ was highly correlated with fresh weight (r=0.988), plant height (r=0.925), and dry weight (r=0.853). According to the relationship among growth parameters and $NDVI_{UAV}$, the temporal variation of $NDVI_{UAV}$ was significant to interpret IRG growth. Four different regression models, such as (1) Linear regression function, (2) Linear regression through the origin, (3) Power function, and (4) Logistic function were developed to evaluate the relationship between temporal $NDVI_{UAV}$ and measured IRG growth parameters. The power function provided higher accurate results to predict growth parameters than linear or logistic functions using coefficient of determination. The spatial distribution map of IRG growth was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to power function. From these results, $NDVI_{UAV}$ can be used as a new tool for monitoring IRG growth.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.420-428
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• 2016

For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.1
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• pp.27.2-27.2
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• 2011

The Kepler(NASA) and CoRoT(ESA) space telescopes are surveying thousands of exoplanet for finding Earth-like exoplanets with similar environments of the Earth. Then the TPF(NASA), DARWIN(ESA) and many large-aperture ground telescopes have plan for spectroscopic observations of these earth-like exoplanets in next decades. Now, it has been started to simulate the disk averaged spectra of the earthlike exoplanets for comparing the observed spectra and suggesting solutions of environment of these planets. Previous research, the simulations are based on radiative transfer method, but these are limited by optical models of Earth system and instruments. We introduce a new simulation method, IRT(Integrated Ray Tracing) to overcome limitations of previous method. The 3 components are defined in IRT; 1)Sun model, 2)Earth system model (Atmosphere, Land and Ocean), 3)Instrument model. The ray tracing in IRT is simulated in composed 3D real scale space from inside the sun model to the detector of instrument. The Sun model has hemisphere structure with Lambertian scattering optical model. Atmosphere is composed of 16 distributed structures and each optical model includes BSDF with using 6SV radiative transfer code. Coastline and 5 kinds of vegetation distribution data are used to land model structure, and its non-Lambertian scattering optical model is defined with the semi-empirical "parametric kernel method" used for MODIS(NASA) and POLDER(CNES) missions. The ocean model includes sea ice cap structure with the monthly sea ice area variation, and sea water optical model which is considering non-lambertian sun-glint scattering. Computation of spectral imaging and radiative transfer performance of Earth system model is tested with hypothetical space instrument in IRT model. Then we calculated the disk averaged spectra of the Earth system model in IRT computation model for 8 cases; 4 viewing orientation cases with full illuminated phase, and 4 illuminated phase cases in a viewing orientation. Finally the DAS results are compared with previous researching results of radiative transfer method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.5 no.5
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• pp.1-10
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• 2002

우리나라의 기후변화연구에서 삼림생태계의 영향과 적응은 가장 중요한 관심사중 하나이다. 지리적 위치와 통일문제 등을 고려할 때, 한반도는 역동적인 개발이 이루어질 지역이며 인구와 경제적 상황의 변화로 삼림 생태계에 급격한 변화가 예상된다. 기후변화의 영향은 이러한 상황을 더욱 복잡하게 만들게 될 것이다. 본 연구에서는 이런 영향을 평가하기 위해, IS92a 시나리오의 GCMs(General Circulation Models)결과들을 이용하여 가능한 기온 증가 범위내에서 삼림생태계의 변화를 예측하였다. 변화를 추정하기 위해 AIM/Impact[Korea](the Asian-Pacific Integrated Model) 모형을 이용하여 시기별 Holdridge 생물기후대를 예측하고 목본식물의 이동속도를 고려한 지역삼림의 영향 및 적응 패턴을 분석하여 생태계 변화로 인한 경제적 가치 손실액을 추정하였다. 분석 결과는 다음과 같이 요약된다. 1) 목본식물의 추정 평균이동속도 0.25km/년의 경우, 한반도에서 삼림소실지역은 발생하지 않는 것으로 예측되었다. 그러나 인위적 개입이 없는 경우 고사의 위험이 높은 지역은 남한의 경우 남한 총면적의 14%를 차지하였고, 북한은 18%정도의 면적이 고사 위험이 있는 것으로 나타났다. 남한 고사위험지역의 80%는 난온대림 지역으로 주로 남해일원과 전라도 서해안에서 발생하며, 북한은 고사위험지역의 대부분이 냉온대림지역으로 주로 평안도 내륙지역과 중국 접경지경, 함경남도의 영흥만 북부에서 나타났다. 2) 목본식물의 이동속도 변화에 따라 남한은 매년 0~976백만불, 북한은 0~2,492백만불 범위의 경제적 가치손실이 발생하는 것으로 예측되었다. 또한 목본식물의 추정 평균이동속도가 0.25km/년일 경우, 한반도 전체의 가치손실액은 매년 3,471백만불에 달했으며, 남한의 경우 목본식물의 이동속도가 0.5km/년 이상인 경우 삼림의 경제적 가치 손실은 발생하지 않았다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1397-1399
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• 2003

When and Where, What kind of agricultural products will be produced and provided for the market? It is a commercial requirement, and also an academic questions to remote sensing technology. Crop physiology analysis and growth monitoring are important elements for precision agriculture management. Remote sensing technology supplies us more selections and available spaces in this dynamic change study by producing images of different spatial, spectral and temporal resolutions. Especially, the hyperspectral remote sensing should do play a key role in crop growth investigation at national, regional and global scales. In the past five years, Chinese academy of sciences and Japan NTT-DATA have made great efforts to establish a prototype information service system to dynamically survey the vegetable planting situation in Nagano area of Japan mainly based on remote sensing data. For such concern, a flexible and light-duty flight system and some practical data processing system and some necessary background information should be rationally made together. In addition, some studies are also important, such as quick pre-processing for hyperspectral data, Multi-temporal vegetation index analysis, hyperspectral image classification in support of GIS data, etc. In this paper, several spectral data analysis models and a designed airborne platform are provided and discussed here.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.397-406
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• 2013

Wetland conservation plan has been established to protect ecologically important wetlands based on vegetation integrity, spatial distribution of endangered species, but recently more demands are concentrated on the landscape ecological approaches such as topological relationship, neighboring area, spatial arrangements between wetlands at the broad scale. Landscape ecological analysis and graph theory are conducted to identify spatial characteristics related to core nodes and weak links of wetland networks in Nakdong basin. Regular planar model, which is selected for wetland networks, is applied in the Nakdong basin. The analysis indicates that 5 regional groups and 4 core wetlands are extracted with 15km threshold distance. The IIC and PC values based on the binary and probability models suggest that the wetland group C composed of main stream of Nakdong river and Geumho river is the most important area for wetland network. Wetland conservation plan, restoration projected of damaged and weak links between wetlands should be proposed through evaluating the node, links, and networks from wetlands at the local to the regional scale in Nakdong basin.

• Korean Journal of Remote Sensing
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• v.11 no.2
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• pp.1-16
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• 1995

This study is conducted to eveluate the potential of a GIS to assist an application problem. GIS has been applied to rainfall-runoff modeling over Soyang area. Various rainfall-runoff models have been developed over the years. A distributed rainfall-runoff model is selected because it considers the topographic characteristics over the basin. GIS can handle the spatial data to enhance the modeling. GRASS-a public domain GIS S/W-is used for GIS tools. Digital database is generated, including soil map, vegetation map, digital elevation model, basin and subbasin map, and water stream. The inpu data for the model has been generated and manupulated using GIS. The database, model and GIS are integrated for on-line operation. The inflow hydrographs are tested for the flood of Sept., 1990. This shows the promising results even without the calibration.