• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.275-288
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• 2004

This paper presents a fuzzy relaxation labeling approach incorporated to the fuzzy logic fusion scheme for the classification of multi-sensor remote sensing images. The fuzzy logic fusion and iterative relaxation labeling techniques are adopted to effectively integrate multi-sensor remote sensing images and to incorporate spatial neighboring information into spectral information for contextual classification, respectively. Especially, the iterative relaxation labeling approach can provide additional information that depicts spatial distributions of pixels updated by spatial information. Experimental results for supervised land-cover classification using optical and multi-frequency/polarization images indicate that the use of multi-sensor images and spatial information can improve the classification accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.544-544
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• 2016

최근 지구온난화 등 기후변화에 따른 돌발 홍수가 계절과 관계없이 빈번하게 발생하고 있으며, 국지성 호우 및 태풍의 영향으로 인한 홍수피해가 매년 발생하고 있다. 이와 같은 피해를 저감하기 위해서는 정확한 강우 관측 및 홍수량 산정이 매우 중요하기 때문에 많은 수문학적 연구와 기술 발달이 이루어지고 있다. 그 중 강우의 변화를 실시간으로 관측 가능한 레이더영상 자료의 활용성이 증대되어 활발한 연구가 진행되고 있으나, 제주도의 경우 다른 지역에 비해 연구가 미흡한 실정이다. 이에 따라, 제주도 유역을 대상으로 유역의 공간적 특성을 격자기반으로 분석하고 매개변수 산정 시 경험적 요인을 제거할 수 있는 분포형 모형인 Vflo와 기상청에서 제공하는 레이더 영상자료 및 강우자료를 활용하여 연구를 수행하였다. 본 연구에서는 Arc-GIS를 이용하여 제주도 도심하천인 외도천 유역의 지형적 지리적 특성(DEM, 토양도, 토지피복도 등)을 $30m{\times}30m$ 격자크기로 분석하고, 레이더영상 자료로부터 강우 자료를 추출하였으며, 분포형 모형(Vflo)을 활용하여 유출량을 모의하였다. FSIV기법을 통해 현장 관측한 유출량과 비교 분석하였으며, 레이더 영상자료로부터 추출한 강우자료는 AWS자료를 활용하여 제주도에 적합한 강우보정계수를 산정하였다. 이와 같은 연구를 통해 향후 제주도 미계측 유역의 홍수량 산정이 가능할 것으로 판단되며, 하천기본계획 및 유역종합치수계획 등 치수계획 수립 시 많은 활용이 될 것으로 기대한다.

• Journal of Environmental Science International
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• v.33 no.3
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• pp.227-234
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• 2024

We investigated the change in land-use alteration in a 45 km × 45 km area around the Upo wetlands in 1920s(before the Japanese occupation period), 1950s(immediately Korean independence) and the period 1970s to 2000s. These data can guide in understanding surface environmental changes in the lower Nakdong River from the early 20^th century to the present. The influence of the long-term decreasing trend of the wetland area at the Upo Swamp was evaluated using a high-resolution local circulation model. The cooling effect of the wetlands on surface air during the daytime in summer(e.g, early August) was approximately 2℃ greater in the 1920s than in the 2000s, which is attributed to wider water areas in the 1920s. Additionally, long-term changes in land use have caused changes in the convergence zone of local circulation wind.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1231-1244
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• 2020

Landsat satellites are representative optical satellites that have observed the Earth's surface for a long-term, and are suitable for long-term changes such as disaster preparedness/recovery monitoring, land use change, change detection, and time series monitoring. In this paper, clouds and cloud shadows were detected using QA bands to detect and remove clouds simply and efficiently. Then, the missing area of the experimantal image is restorated through the SSG algorithm, which does not directly refer to the pixel value of the reference image, but performs restoration to the pixel value in the Experimental image. Through this study, we presented the possibility of utilizing the modified SSG algorithm by quantitatively and qualitatively evaluating information on variousl and cover conditions in the thermal wavelength band as well as the visible wavelength band observing the surface.

• Journal of the Korean Geographical Society
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• v.40 no.2 s.107
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• pp.221-241
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• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.17-24
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• 2011

Global warming and climatic changes due to human activities impact on marine and terrestrial ecosystems, which feedbacks to climate system. These negative feedbacks amplify or accelerate again global climate change. In particular, it is important to analyze vegetation change. This study attempts to analyze quantitatively vegetation change in Korea peninsula by using harmonic analysis. Harmonic-Analysis based on Fourier Transform is the method to effectively demonstrate for time series data. Especially, Harmonic-Analysis is very suitable method to analyze vegetation change because the vegetation repeats the cycle growth and extinction every year. The result of harmonic-analysis shows vegetation change as time passes. In this study, SPOTNEGETATION S10 MVC NDVI data was used during last 10 years (1999-2008) in Korea Peninsula. Also, land type classification used MODIS Land Cover Map data. The study estimated that phase values moved up approximately 0.5 day per year in cropland and 0.8 day per year in forest.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.383-396
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• 2004

The application of spatial statistics to obtain the spatial uncertainty distributions in classification of remote sensing images is investigated in this paper. Two quantitative methods are presented for describing two kinds of uncertainty; one related to class assignment and the other related to the connection of reference samples. Three quantitative indices are addressed for the first category of uncertainty. Geostatistical simulation is applied both to integrate the exhaustive classification results with the sparse reference samples and to obtain the spatial uncertainty or accuracy distributions connected to those reference samples. To illustrate the proposed methods and to discuss the operational issues, the experiment was done on a multi-sensor remote sensing data set for supervised land-cover classification. As an experimental result, the two quantitative methods presented in this paper could provide additional information for interpreting and evaluating the classification results and more experiments should be carried out for verifying the presented methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.34-40
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• 2017

In recent years, global warming has caused abnormal weather phenomena. Unusually cold climates have occurred all around the world, including cold waves in the Northeastern United States, Beijing, China, Southern India, and Pakistan, as well as floods in Chile, Kazakhstan, and Vietnam. China has been experiencing a nationwide heat wave annually since the year 2013, especially in the southern region. In this study, we used Landsat 8 OLI TIRS sensor images from four periods to analyze the characteristics of abnormal high temperature phenomena in Cixi-si, China. Land cover classification was performed using 10 bands of satellite imagery, and the surface temperature was extracted using the 10th thermal band. The results of the land cover classification of the fourth period show the changes of the time series quantitatively. The results of the surface temperature calculation provided both the average overall temperature and the average temperature of individual items. The temperature was found to be highest for buildings, followed by grassland, forest, agricultural land, water systems, and tidal flats in the same period.

• Journal of the Korean association of regional geographers
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• v.23 no.1
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• pp.136-150
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• 2017

This study analyzed the spatial change of urban green spaces in Daegu from 1989 to 2009 using cell based spatial metrics. To do so, the conversion process of land covers during the past 20 years was explored using a land cover change detection matrix. The synoptic analysis with a moving window sampling strategy was conducted to quantify cell based spatial metrics related to size, shape, cohesion, and diversity and to explain the spatial change at the local level. Difference maps were then generated by subtracting the 1989 maps of spatial metrics from the 1998 maps and the 1998 maps from the 2009 maps. The gradient analysis was performed to identify the directional change of spatial metrics along an urban development axis in Daegu. The results from this study show that urban green spaces in Daegu during the past 20 years have been gradually fragmented around the new town housing development districts such as Dalseong-gun, Seongseo, and Ansim. Forests were most prominently fragmented in the Hwawon area while most rapidly in the Chilgok area. Grasslands were largely fragmented in many areas due to the decrease in size and cohesion indices and most fragmented in the Ansim area. The spatial pattern of the decreased and fragmented urban green spaces identified by this study can be used as a base data for establishing the environment-friendly urban development strategy in Daegu.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.275-291
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• 2023

Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.