• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.94-106
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• 2011

The muddy water occurrence possibility of reservoir were analyzed by considering GIS based soil erosion model, sediment delivery ratio and effective reservoir capacity. For the purpose, the weakness factors for the establishment of countermeasures of basin were analyzed by evaluating input factors of RUSLE model based on spatial data such as DEM, soil map, landcover map and so on. The potential of soil erosion was estimated considering highland upland. The sediment yields of Chungju-Dam and Soyanggang-Dam showed the highest result in sediment yield using sediment delivery ratio with considering basin area. The sediment concentration of Imha-Dam and Chungju-Dam showed the highest value as 0.791 $kg/m^3/yr$ and 0.526 $kg/m^3/yr$ respectively in sediment concentration with considering effective reservoir capacity. Especially, sediment yield of Imha-Dam was about 2.36 times lower than Soyanggang-Dam, but the sediment concentration was 1.90 times higher preferably, because the effective reservoir capacity of Imha-Dam was about 4.48 times lower. This study calculated sediment concentration using the 10 years mean rainfall event and could consider the aspects of soil, terrain, landcover, cultivation condition and effective reservoir capacity of each basin effectively through the results. Therefore, these quantitative sediment concentration data could be used to estimate the potential of high density turbid water for reservoir and applied with effective tools for the management of reservoir.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.122-131
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• 2007

This study estimates how soil loss in a basin has been occurred according to the change of land cover, and analyzes which type of land cover has the largest soil loss by classifying the land-cover type into each area and a whole basin. Musimcheon, the second branch stream of GeumGang, is chosen as a research area. The result of analysis shows that the average soil loss occurs most largely in a crop land and a paddy field. The yearly soil loss of watershed estimates approximately 14,000 ton/yr in case of using 100-year-frequency rainfall data. A forest area, which takes the largest area in watershed, shows the soil loss occurs approximately 1,000ton/yr. A crop field shows that soil loss increased most largely 4,900 ton/yr (34.6%) in 1985 to 8,100 ton/yr (56.1%) in 2000. The change of land cover in a crop land increased 8% to 14%, and this change influences on the increase of soil loss. As a result of analyzing the area over $200ton/km^2/yr$, the soil loss in a crop field accounts for 74% to 96%.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.357-364
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• 2017

The purpose of the study is to develop and validate landslide susceptibility map of Bhotang village development committee, Nepal using FR (Frequency Ration) and SI (Statistical Index) methods. For the purpose, firstly, a landslide inventory map was constructed based on mainly high resolution satellite images available in Google Earth Pro, and rest fieldwork as verification. Secondly, ten conditioning factors of landslide occurrence, namely: altitude, slope, aspect, mean topographic wetness index, landcover, normalized difference vegetation index, dominant soil, distance to river, distance to lineaments and rainfall, were derived and used for the development of landslide susceptibility map in GIS (Geographic Information System) environment. The landslide inventory of total 116 landslides was divided randomly such that 70% were used for training and remaining 30% for validating result by receiver operating characteristics curve analysis. The area under the curve were found to be greater than 0.7 indicating an acceptable susceptibility maps obtained using FR and SI methods in GIS for hilly region of Nepal.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.1-4
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• 2001

The classification performance of Artificial Neural Network (ANN) and RBF-NN was compared for Landsat TM image. The RBF-NN was validated for three unique landuse types (e.g. Mixed landuse area, Cultivated area, Urban area), different input band combinations and classification class. The bootstrap resampling technique was employed to estimate the confidence intervals and distribution for unit load, The pollutant generation was varied significantly according to the classification accuracy and percentile unit load applied. Especially in urban area, where mixed landuse is dominant, the difference of estimated pollutant load is largely varied.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.170-170
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• 2011

토지피복은 지표면의 물리적 상태 및 사용 용도에 따른 특성을 나타내는 기본적인 정보로 농업, 환경, 재해, 수자원 등 다양한 분야에서 이용되고 있다. 식생활동으로 인해 생기는 증산과 토양에서 일어나는 증발을 증발산이라 통칭하며, 이의 정확한 산정은 수리, 수문학적 유역 분석에 중요하다. 정확한 증발산의 산정을 위해서는 기압, 온도 등 기상 인자의 역할이 중요하지만 토지피복 특성 역시 증발산에 큰 영향을 주므로 중요한 요소 중 하나이다. 이는 인간의 활동에 의해 점차적으로 빠르게 변화하는 추세이므로 인공위성 영상을 이용하여 효율적인 정보의 취합 및 관리가 필수적이다. 따라서 본 연구에서는 Landsat 5 TM(Thematic Mapper) 영상을 기반으로 무감독 분류법을 이용하여 ISODATA Training과 Masking기법을 사용하여 한강 유역의 토지피복도를 산정하였다. 본 연구에서는 연구 대상 지역의 영상을 사용하였고, 토지의 분류는 수역, 시가, 나지, 습지, 초지, 산림, 농지의 7가지로 분류하였다. 그 결과 우리나라의 대다수를 이루는 수역, 시가, 산림, 농지에 대한 높은 정확도를 갖는 토지피복도를 얻을 수 있었으며, 이는 군사경계 외부의 지역도 포함된 결과이다. 단, 나지와 습지, 초지 부분의 정확도는 비교적 떨어지나, 우리나라의 토지특성상 많은 비율을 차지하고 있지 않으므로 신뢰할 만한 결과라 할 수 있겠다. 이 결과와 외부 자료를 이용하여 보다 향상된 토지피복도를 만들 수 있을 것이다. 이를 토대로 군사지역 등 접근이 어려운 지역의 토지피복 현황을 파악하여 정확한 증발산 산정에 도움이 되고자 한다.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.131-137
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• 2004

This study presents the application of multi-temporal aerial photographs in detecting change in a small urban area. For the panchromatic aerial images of the scale of 1/20000 and 1/37500 photographed in 1987, 1996 and 2000, image geometric correction and registration were carried out before performing change detection in a common reference system and then image mosaicking. The image differencing technigue was employed to detect urban features and landcover change and then the results were compared to those of image ratioing techniques. Also threshold values were suggested in applying image differencing for change detection.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.132-137
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• 2009

This study has regard to classification by using multi-temporal SAR data. Multi-temporal JERS-1 SAR images are used for extract the land cover information and possibility. So far, land cover information extracted by high resolution aerial photo, satellite images, and field survey. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then extracted land cover information factors, so on. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass.

• Economic and Environmental Geology
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• v.29 no.5
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• pp.615-622
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• 1996

Slope stability analysis was conducted using remote sensing and Geoscientific Information System (GIS) as a part of natural hazard assessment around Chungju area. Landsat TM band 5 and 7 which contain more information about geological structure and geography are chosen and processed to analyse regional geological structure. Through image processing technique such as PCA, HFF, edge detection and enhancement, regional lineament can be mapped and identified. The lineament density map is constructed based on summed length of lineaments per unit area and the study area can be divided into 7 structural domains. Various factors of slope stability analysis such as geology, slope aspect, degree of slope, landcover, water shed as well as characterized structural domain are constructed as a database of GIS. Rating and weighting of each factor for slope stability analysis is decided by considering environmental geological characteristics of study area. Spatial analysis of regional slope stability is examined through overlaying technique of the GIS. The result of areal distribution of slope stability shows that the most unstable area is all over Jaeogae-ni, Hyangsan-ni and Mt. Daedun.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.68-71
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• 2008

Our goal is to obtain a better scientific understanding how to define the nature and role of remotely sensed land surface parameters and energy fluxes in the heat island phenomena, and local and regional weather and climate. By using the MODIS visible and thermal imagery data and analyzing the surface energy flux images associated with the change of the landcover and landuse in study area, we will estimate and present how significant is the magnitude of the heat island heat effect and its relation with the surface parameters and the energy fluxes in Taiwan. To achieve our objective, we used the energy budget components such as net radiation, soil heat flux, sensible heat flux, and latent heat flux in the study area of interest derived form remotely sensed data to understand the island heat effect. The result shows that the water is the most important component to decrease the temperature, and the more the consumed net radiation to latent heat, the lower urban surface temperature.