• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.25-33
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• 2002

We were trying to understand indirectly the range of the discharge from the Nakdong with the dispersion of suspended solid(SS) related to the amount of discharge from river in this study. The range of dispersion of SS from the Nakdong was estimated using satellite remote sensing and numerical modeling. The stream field with two dimensional and numerical model using the condition of integrated depth was calculated. According to the results, the streamline flowed from Busan to the Jinhae Bay and Geojae Island. at the flood. The situation at the ebb was totally changed. The streamline flowed out Busan from the Bay. The velocity in offshore was faster than one at coastal water of the Nackdong. Residual current which was averaged during 12hours dominantly appeared the dominant direction from the southwestern part of the Nackdong to the northeastern part of it. The eastward current appeared at the eastern coast of Gaduck Is. Base on the results of the velocity field, the quantifying of the dispersion of SS was estimated by the method of numerical tracer related to the Lagrangian method. The significant range of the dispersion of the SS from the Nackdong was from the eastern coast of Gaduck Is, to the coastal areas of Busan, Korea. The estimated range of the dispersion of the SS using the SeaWiFS and Landsat satellite data was similar to the estimated results using the numerical model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.1
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• pp.17-24
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• 2008

This study was performed to estimate non-$CO_2$ greenhouse gases (i.e., GHGs) emission from biomass burning at a local scale. Estimation of non-$CO_2$ GHGs emission was conducted using Landsat TM satellite imagery in order to assess the damage degree in burnt area and its effect on non-$CO_2$ GHGs emission. This approach of estimation was based on the protocol of the 2003 IPCC Guidelines. In this study, we used one of the most severe fire cases occurred Samcheock in April, 2004. Landsat TM satellite imageries of pre- and post-fire were used 1) to calculate delta normalized burn ratio (dNBR) for analyzing burnt area and burn severity of the Samcheok large-fire and 2) to quantify non-$CO_2$ GHGs emission from different size of the burnt area and the damage degree. The analysis of dNBR of the Samcheok large-fire indicated that the total burnt area was 16,200ha and the size of the burnt area differed with the burn severity: out of the total burnt area, the burn severities of Low (dNBR < 152), Moderate (dNBR = 153-190), and High (dNBR = 191-255) were 35%, 33%, and 32%, respectively. It was estimated that the burnt areas of coniferous forest, deciduous forest, and mixed forest were about 11,506ha (77%), 453ha (3%), and 2,978ha (20%), respectively. The magnitude of non-$CO_2$ GHGs emissions from the Samcheok large-fire differed significantly, showing 93% of CO (44.100Gg), 6.4% of CH4 (3.053Gg), 0.5% of $NO_x$ (0.238Gg), and 0.1% of $N_2O$ (0.038Gg). Although there were little changes in the total burnt area by the burn severity, there were differences in the emission of non-$CO_2$ GHGs with the degree of the burn severity. The maximum emission of non-$CO_2$ GHGs occurred in moderate burn severity, indicating 47% of the total emission.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.493-500
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• 2007

In general, it accomplished a spectral reflectance analysis to be, the measurement results appear differently by targets, methods and condition. This paper presents a standard methodology for preprocessing mineral/rock samples and setting the distance from a target to the sensor, and then examines closely the spectral features for pyrophyllite. The size of mineral/rock samples is various according to the condition and scale of outcrop, so it is important to maintain the distance between the sensor and the sample. Before standardization for preprocessing samples and the sensor and sample distance, we prepare various rock samples (Quartz Porphyry) such as natural rock, pebble, powder and cutting rock. For a qualitative analysis to minimize the effect of surface condition of the sample and shadow, we maintains the distance from the sample to the sensor at 30cm and measures three times repeatedly for cutting the sample at $1{\sim}2cm$ thickness. To illustrate the proposed methodology, a case study for pyrophyllite was carried out. In this study, pyrophyllite showed an absorption pattern at wave length of 1.406nm, 1,868nm, 2.180nm and 2.309nm, and a higher grade represented strong absorption at 1.406nm and 2.180 nm. These absorption feature corresponds the band 7 of LANDSAT TM and band 8 of ASTER imageries. So, using these results, pyrophyllite deposits were extracted from other features (such as barren area, concrete area, bed of river, stone pit area etc.).

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.1
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• pp.1-10
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• 2002

The purpose of this article is to examine land use change in the fringe area of a metropolitan city through multi-temporal data analysis. Change detection has been regarded as one of the most important applications for utilization of remotely sensed imageries. Conventionally, two images were used for change detection, and Arithmetic calculators were generally used on the process. Meanwhile, multi-temporal change detection for a large number of images has been carried out. In this paper, a digital land-use map and three Landsat TM data were utilized for the multi-temporal change detection Each urban area map was extracted as a base map on the process of multi-temporal change detection. Each urban area map was converted to bit image by using boolean logic. Various urban change types could be obtained by stacking the urban area maps derived from the multi-temporal data using Geographic Information System(GIS). Urban change type map was created by using the process of piling up the bit images. Then the urban change type map was compared with each land cover map for the change detection. Dalseo-gu of Daegu city and Hwawon-eup of Dalsung-gun, the fringe area of Daegu Metropolitan city, were selected for the test area of this multi-temporal change detection method. The districts are adjacent to each other. Dalseo-gu has been developed for 30 yeais and so a large area of paddy land has been changed into a built-up area. Hwawon-eup, near by Dalseo-gu, has been influenced by the urbanization of Dalseo-gu. From 1972 to 1999, 3,507.9ha of agricultural area has been changed into other land uses, while 72.7ha of forest area has been altered. This agricultural area was designated as a 'Semi-agricultural area'by the National landuse Management Law. And it was easy for the preserved area to be changed into a built-up area once it would be included as urban area. Finally, the method of treatment and management of the preserved area needs to be changed to prevent the destruction of paddy land by urban sprawl on the urban fringe.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.36-46
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• 2007

The primary purpose of this study is to identify the characteristics of land use change at the urban fringe. For this purpose, the Daegu Metropolitan City is selected as a study area. Land use changes between 1990 and 2000 in fringe areas are identified by processing Landsat TM5 imageries. The main findings are follows: First, land development has been driven by residential development, especially large-scale residential development encouraged by the two-million housing construction plan. Second, the type and size of the land use conversion are not identical across the study area. For example, the main land use type of the newly developed area of Buk-gu is residential use while that of Suseong-gu is public use. Third, most of residential development type is a high-density development which is quite different from American type of low-density development.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.962-964
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• 2003

In 2002 Thailand was faced with severe flooding in the North, Northeast and Central parts of the country caused by heavy rainfall of the monsoonal depression which brought about significant damages. According to the report by the Ministry of Interior and the Ministry of Agricultural and Co-operatives, the total damages were estimated to be about 6 billion bath. More than 850,000 farmers and 10 million livestock were effected. An area of 1,450,000 ha of farmland in 59 Provinces were put under water for a prolonged period. Satellite imageries were employed for mapping and monitoring the flood-inundated areas, flood damage assessment, flood hazard zoning and post-flood survey of river configuration and protection works. By integrating satellite data with other updated spatial and non-spatial data, likely flood zones can be predicted beforehand. Some examples of satellite data application to flood dis aster mitigation in Thailand during 2002 using mostly Radarsat-1 data and Landsat-7 data were illustrated and discussed in the paper. The results showed that satellite data can clearly identify and give information on the status, flooding period, boundary and damage of flooding. For comprehensive flood mitigation planning, other geo-informatic data, such as the elevation of topography, hydrological data need to be integrated. Ground truth data of the watershed area, including the water level, velocity, drainage pattern and direction were also useful for flood forecasting in the future.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.329-337
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• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.