• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.549-557
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• 2013

An flood inundation map is able to convey spatial distribution of inundation to a decision maker for flood risk management. A roughness coefficient with unclear values and a discharge obtained from the stage-discharge rating equation are key sources of uncertainty in flood inundation mapping by using a hydraulic model. Also, the uncertainty analysis needs an observation for the flood inundation, and satellite images is useful to obtain spatial distribution of flood. Accordingly, the objective of this study is to quantify uncertainty arising roughness and discharge in flood inundation mapping by using a hydraulic model and a satellite image. To perform this, flood inundations were simulated by HEC-RAS and terrain analysis, and ISODATA (Iterative Self-Organizing Data Analysis) was used to classify waterbody from Landsat 5TM imagery. The classified waterbody was used as an observation to calculate F-statistic (likelihood measure) in GLUE (Generalized Likelihood Uncertainty Estimation). The results from GLUE show that flood inundation areas are 74.59 $km^2$ for lower 5 % uncertainty bound and 151.95 $km^2$ for upper 95% uncertainty bound, respectively. The quantification of uncertainty in flood inundation mapping will play a significant role in realizing the efficient flood risk management.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.651-664
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• 2014

Recently, the demands of accurate forest carbon stock estimation and mapping are increasing in Korea. This study investigates the feasibility of two methods, k-Nearest Neighbor (kNN) and Regression Tree Analysis (RTA), for carbon stock estimation of pilot areas, Gongju and Sejong cities. The 3rd and 5th ~ 6th NFI data were collected together with Landsat TM acquired in 1992, 2010 and Aster in 2009. Additionally, various vegetation indices and tasseled cap transformation were created for better estimation. Comparison between two methods was conducted by evaluating carbon statistics and visualizing carbon distributions on the map. The comparisons indicated clear strengths and weaknesses of two methods: kNN method has produced more consistent estimates regardless of types of satellite images, but its carbon maps were somewhat smooth to represent the dense carbon areas, particularly for Aster 2009 case. Meanwhile, RTA method has produced better performance on mean bias results and representation of dense carbon areas, but they were more subject to types of satellite images, representing high variability in spatial patterns of carbon maps. Finally, in order to identify the increases in carbon stock of study area, we created the difference maps by subtracting the 1992 carbon map from the 2009 and 2010 carbon maps. Consequently, it was found that the total carbon stock in Gongju and Sejong cities was drastically increased during that period.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• The Journal of Engineering Geology
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• v.30 no.3
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• pp.347-378
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• 2020

Based on monthly average groundwater recharge over a nearly 10 year period, results of fully integrated hydrologic modeling of SWAT-MODFLOW, land cover, land use, soil type and hydrologic response unit (HRU) was used to assess the dominant influencing factors of groundwater recharge spatial patterns in Jangseong district. As dominant factors, land cover was FRSE (forest-evergreen) and soil type was Samgag. Landsat-8 OLI imaging spectrometer data were acquired in the period 2003 to 2004 and seasonal bare soil lines (BSL) were estimated through NIR-RED plot. Extent of slope of BSL was from 1.092 to 1.343 and the intercept was from -0.004 to -0.015. To know correlation between spatial groundwater recharge and soil-vegetation indices (PVI, NDVI, NDTI, NDRI), this study employed frequency and regression analysis. On May, RED band increased up 3 to 4 times compared to other seasons and only one turning point appeared as recharge-index with upward parabola bell shape as results of existing research. Considering precipitation, if the various studies for relationship between groundwater recharge and soil-vegetation index just like NDVI are performed, it is possible to estimate groundwater recharge through analyzing remote sensing data.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.17-28
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• 2003

Since 1970s, Seoul Metropolitan Area has been growing in physical and demographic aspect. A number of new urban fringes, New City, had been particularly developed from the early of 1990s. To examine the urban growth, the population density maps are generally used to the efficient urban management tool. The density maps from political boundaries, however, were traditionally used to estimate an urban concentration, there is problems to apply directly to urban management decision making due to (i) the abrupt changes between boundaries and (ii) the inclusion of green areas and forests in these areas. The mass-preserving interpolation method, the Pycnophylactic interpolation, could provide more realistic density maps. In addition, the classified urban areas from satellite images corresponding years would turn out to be more reliable results since populations were only applied to urbanized areas. Even though the Pyconophylactic method makes the density larger, it would be useful to produce a general urban growth trend at large scale. Consequently, four different density maps are compared and reviewed for this study, and the cross-sectional analysis provided to glimpse of population density around the city center.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.152-157
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• 2012

Sarawak is the largest state in Malaysia that covers 37.5% of the total land area. Multitemporal satellite images of Landsat and SPOT were used to examine deforestation and forest fragmentation in Sarawak between 1990 and 2009. Supervised classification with maximum likelihood classifier was used to classify the land cover types in Sarawak. The overall accuracies of all classifications were more than 80%. Our results showed that forests were reduced at 0.62% annually during the two decades. The peat swamp forest suffered a tremendous loss of almost 50% between 1990 and 2009 especially at coastal divisions due to intensified oil palm plantation development. Fragmentation analysis revealed the loss of about 65% of the core area of intact forest during the change period. The core area of peat swamp forest had almost completely disappeared during the two decades.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.361-364
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• 2005

The use of remotely sensed data and geographic information system (GIS) to develop conservation-oriented watershed management strategies on Imha Dam, Korea, is presented. The change of land use for study area was analyzed using multi-temporal Landsat imagery. A soil loss model was executed within a GIS environment to evaluate watershed management strategies in terms of soil loss. In general, remotely sensed data provide efficient means of generating the input data required for the soil loss model. Also, GIS allowed for easy assessment of the relative erosion hazard over the watershed under the different land use change options. The soil loss model predicted substantial declines in soil loss under conservation-oriented land management compared to current land management for Imha Dam. The results of this study indicate that soil loss potential (5,782,829 ton/yr) on Imha Dam in 2003 is approximately 1.27 times higher than that (4,557,151 ton/yr) in 1989. This study represents the first attempt in the application of GIS technology to watershed conservation planning for Imha Dam. The procedures developed will contribute to the evolution of a decision support system to guide the land planning and dam management in Imha Dam.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.394-397
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• 2005

This study aims to estimate a heat island potential distribution based on the land-use types using LANDSAT/TM(1100LST April 2000) and AWS data in Daegu. The heat island potential is defined as a difference between surface temperature and air-temperature at each place. The study area was selected as about $900k km^2$ square including Daegu metropolitan area. Land-use data obtained by dividing all of Daegu metropolitan area into l-km-square three types of maps were prepared, in the 1 960s, 1970s and 2000s respectively. The types of land-use were divided into 5. Forest and farm lands have been reduced at a wide range during 40 years, most of which changed to urban area. The heat island potential distribution presented a striking contrasts according to land-use types. For example, the heat island potential of urban area was higher than $14^{\circ}$ in comparison to those of water or paddy rice areas.

• 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.

• Journal of Environmental Science International
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• v.16 no.1
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• pp.65-71
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• 2007

This study aims to estimate a urban heat island potential distribution based on the land-use types using Landsat TM(1100 LST August 2004) and AWS data in Daegu. The heat island potential is defined as a difference between surface temperature and air-temperature at each place. The study area was selected as about $900km^2$ square including Daegu metropolitan area. Land-use data obtained by dividing all of Daegu metropolitan area in- to 1-km-square three types of maps were prepared in the 1960s, 1970s and 2000s respectively. Land-use types were classified into 5 categories. Forest and farm lands have been reduced at a wide range during 40 years. Most of those changed into urban area. The heat island potential distribution presented a striking contrasts according to land-use types. For example, the heat island potential of urban area was higher than $10^{\circ}C$ in comparison to those of water or paddy rice areas.