• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.3
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• pp.79-85
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• 2003

Human beings have pursued development and economic betterment; thus, enhancing convenience and prosperity. A flourish of human civilization upon the industrialization results a massive urbanization. However, human beings have connived the environmental importance in the course of rapid urbanization. The environmental quality now becomes one of the most important factors that determine the quality of life in a city. Many studies were proceeded about the heat island effect in large cities. In general, most studies have been done to investigate urban microclimate phenomena using meteorological network or AWS (automatic weather station) data. Those preceding studies do not seem to sufficiently reflect the and thus, failed to show regional representative. In this study, temporal Landsat TM satellite imageries of May 20, 1987 and May 21, 1999 were 뻐d in order to detect the surface temperature of the study area using the band 6 ($10.4{\mu}m{\sim}12.5{\mu}m$). The surface temperature distribution detected by the band 6 of Landsat TM was over layed with the land cover classification data in order to investigate the temperature difference of the paved road and the riparian areas of the stream. As a result, a surface temperature difference as much as $3^{\circ}C$ between the paved road and the riparian areas with vegetation was observed. This study concludes that the land cover change is one of the main causes of urban heat island effect which may be closely affected by the paved areas and roads. Besides, the change of the atmospheric temperature followed by the urban secular change could have been confirmed. In the case of Yangjaecheon stream which underwent a heavy environmental restoration in 1995, the temperature was decreased as much as $0.6^{\circ}C$ after the restoration. The results of this study is expected to contribute to develop an urban space in harmony with the healthy human life and the environment respecting the crucial role of vegetation to stabilize the urban environmental dynamics.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.201-211
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• 2017

The estuary in Nakdong River has changes by the construction of harbors, land reclamation and artificial waterway changes. These resultslead to changes of extinction and creation of deltaic barrier island. The deltaic barrier island changes in the Nakdong River estuary affect the function of the barrier islands and cause environmental changes. Therefore, it is important to monitor the changes in the area of the Nakdong estuary. In this study, long-term changes of the area and suspended sediment of deltaic barrier island in the Nakdong River estuary were analyzed using Landsat TM/ETM+ images. As a result, end point rate (EPR) values of shoreline in Jinwoodo and Sinjado are about 5m/yr and about 50 m/yr, respectively. The EPR values of north-south and east-west direction in Doyodeung are 20 m/yr and -20 ~ 10 m/yr. The suspended sediment concentration (SSC) has a maximum value of $25g/m^3$ in the vicinity of Jinwoodo and Sinjado, while it has a maximum concentration of $40g/m^3$ in the vicinity of Shinjido and Doyodeung. In other words, the area and the SSC change are small in Jinwoodo, and the area change and the SSC variation are large in Sinjado and Doyodeung. As a result of analysis of correlation between area change and SSC variation using all data, the Pearson coefficient value (r) is 0.36 and it is 0.32 in winter data. In other words, it is considered that the SSC variation affectsthe deltatic barrier island area change. However, verification using advanced altimetry data is necessary in the future. These studies can be used for coastal monitoring and environmental monitoring.

• Korean Journal of Soil Science and Fertilizer
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• v.35 no.3
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• pp.185-195
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• 2002

The purpose of this study is to evaluate and seek the best suitable band and threshold boundary level on the change detection of image differencing method using Landsat TM data(20 May 1987 and 20 May 1993) in Pyeongtaeg City. The change detection images differencing method were evaluated by using normal reference data with an optimal threshold level{$mean{\pm}(SD{\times}T$ value). The normal reference data consisted of positive change{change dark into light in image pattern, that is, it changed arable land(paddy, upland, forest and so on) to artificial area(buildings, vinyl-house and roads, etc)} and negative change(change light into dark in image pattern, that is, it changed artificial area into arable land). As the result, the kappa coefficients of visible bands(D1, D2 and D3) were higher than those of infrared bands(D4, D5 and D7), and than D1 image with 1.0 thresholding and normal reference data was a improved result in the land-surface change detection such as kappa coefficient : 68.4%, overall accuracy : 89.2%, negative change : 6.6%, positive change : 10.6%.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.3
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• pp.1-15
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• 1999

This study was carried out to find out the way to build a comprehensive wetland ecosystem database using the technique of remote sensing and geographic information system. A Landsat TM image taken in May 17, 1997 was used for the primary source for the image analysis. Field surveys were conducted March to September of 1998 to help image analysis and examine the results. An actual wetland vegetation map was created based on the field survey. A Landsat TM image was analyzed by unsupervised and supervised classification methods and finally categorized into such 5 classes as Phragmites australis community, mixed community, sand beach, Scirpus trigueter community and non-vegetation intertidal area. Wetland basemap was developed for the overall accuracy assesment in wetland mapping. Vegetation index map of wetland vegetation was developed using NDVI(normalized difference vegetation index). The map of wetland productivity was developed based on the productivity of Phragmites australis and the relationship to the proximity of adjacent water bodies. The map of potential vegetation succession map was also developed based on the experience and knowledge of the field biologists. Considering these results, it is possible to use the remote sensing and GIS techniques for producing wetland ecosystem database. This study indicated that these techniques are very effective for the development of the national wetland inventory in Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.80-91
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• 2003

In this research, re-using band ratio data was proposed and examined as a method of raising the accuracy in landcover classification which is using satellite data.In order to determine the band which is used to calculation in the classified item, the six bands except the band 6 were combined with the band in which combination is possible and the landcover classification by MLC of supervised classification was carried out. In the result of landcover classification which is combined with forty nine combination, Two bands which were mostly used by band combination in the accuracy belonged inside the 10th place of a higher rank were selected and also calculated. landcover classification were performed again after the calculation result had been recombinated from the research. In addition, the new landcover classification result was compared and examined with the landcover classification using the old data. From the result of which was compared and examined the new landcover classification data recombinated calculation result with landcover classification using the original data, The classification accuracy of the new landcover classification data recombinated calculation result became low in ground but became improved in the all class. Specially The accuracy to urban area is very improved. therefore, it determined that reusing band ratio data is very useful when we need to analyze landcover classification and land information to urban area after that.

• Korean Journal of Environment and Ecology
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• v.32 no.1
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• pp.97-104
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• 2018

This study investigated the effect of forest type changes in Daegu, the hottest city in Korea, on the land surface temperature (LST). The LST change by forest type was analyzed by 2scene of Landsat TM image from 1990 to 2007. The land cover types were classified into 4 types; forest areas, urban areas, cultivated areas and other areas, and water areas. The forest areas were further classified into the coniferous tree areas and the broadleaf tree areas. The result of the statistical analysis of the LST change according to the forest type showed that the LST increased when the forest was changed to the urban area. The LST increased by about $0.6^{\circ}C$ when a broadleaf tree area was changed to an urban area and about $0.2^{\circ}C$ when a coniferous tree area was changed to an urban area. This was the temperature change as the result of the simple type change for 17 years. The temperature change was larger when considering both cases of the forest type being retained and changed. The LST increased by $2.3^{\circ}C$ more when the broadleaf tree areas were changed to the urban areas than when broadleaf trees were maintained. The LST increased by $1.9^{\circ}C$ more when the coniferous tree areas were changed to the urban areas than when the coniferous tree areas were maintained. The LST increased by $0.4^{\circ}C$ more when the broadleaf tree areas were destroyed than when the coniferous tree areas were destroyed. The results confirmed that the protection of broadleaf trees in urban forests was more effective for mitigating climate change.

• 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.