• Proceedings of the KSRS Conference
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• v.2
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• pp.639-642
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• 2006

The intensity-hue-saturation (IHS) technique has become a standard procedure in image analysis. It enhances the colour of highly correlated data. Unfortunately, IHS technique is sensitive to the properties of the analyzed area and usually faces colour distortion problems in the fused process. This paper explores the relationship of colour between before and after the fused process and the change in colour space of images. Subsequently, the fused colours are transformed back into the 'simulative' true colours by the following steps: (1) For each pixel of fused image that match with original pixel (of the coarse spectral resolution image) is transformed back to the true colour of original pixel. (2) The value for interpolating pixels is compensated to preserve the DN ratio between the original pixel and it's vicinity. The 'compensative matrix' is constructed by the DN of fused images and simulation of scaling process. An illustrative example of a Landsat and SPOT fused image also demonstrates the simulative true colour fusion methods.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.367-373
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• 2000

Natural and artificial land features are very dynamic, changing somewhat repidly in our lifetime. It is important that such changes are inventoried accurately so that the physical and human processes at work can be more fully understood. Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. The purpose of this research is to detect environmental changes surrounding an area of Mountain Moscow, Idaho using Landsat Thematic Maper (TM) images of (July 8, 1990 and July 20, 1991). For accurate classification, the Image enhancement process was performed for improving the image quality of each image. A SPOT image (Aug. 14, 1992) was used for image merging in this research. Supervised classification was performed using the maximum likelihood method. Accuracy assessments were done for each classification. Two images were compared on a pixel-by-pixel basis using the post-classification comparison method that is used for detecting the changes of the study area in this research. The 'from-to' change class information can be detected by post classification comparison using this method and we could find which class change to another.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.100-119
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• 2020

During recent years, the heat environment and particulate matter (PM₁₀) have become serious environmental problems, as increases in heat waves due to rising global temperature interact with weakening atmospheric wind speeds. There exist urban heat islands and urban pollution islands with higher temperatures and air pollution concentrations than other areas. However, few studies have examined these issues together because of a lack of micro-scale data, which can be constructed from spatial data. Today, with the help of satellite images and big data collected by private telecommunication companies, detailed spatial distribution analyses are possible. Therefore, this study aimed to examine the spatial distribution patterns of urban heat islands and urban pollution islands within Busan Metropolitan City and to compare the distributions of the two phenomena. In this study, the land surface temperature of Landsat 8 satellite images, air temperature and particulate matter concentration data derived from a private automated meteorological observation system were gridded in 30m × 30m units, and spatial analysis was performed. Analysis showed that simultaneous zones of urban heat islands and urban pollution islands included some vulnerable residential areas and industrial areas. The political migration areas such as Seo-dong and Bansong-dong, representative vulnerable residential areas in Busan, were included in the co-occurring areas. The areas have a high density of buildings and poor ventilation, most of whose residents are vulnerable to heat waves and air pollution; thus, these areas must be considered first when establishing related policies. In the industrial areas included in the co-occurring areas, concrete or asphalt concrete-based impervious surfaces accounted for an absolute majority, and not only was the proportion of vegetation insufficient, there was also considerable vehicular traffic. A hot-spot analysis examining the reliability of the analysis confirmed that more than 99.96% of the regions corresponded to hot-spot areas at a 99% confidence level.

• Proceedings of the KSRS Conference
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• v.1
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• pp.52-55
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• 2006

It's used to be said that tsunami is a rare event. The recurrence time of tsunami in Sumatra area is approximately 230 years as CalTech Research Group‘s study from paleocoral. However, the tsunami occurred in Indian Ocean on 26 December 2004, 28 March 2005 and 17 July 2006, because the earthquakes still release the energy. To cope with the tsunami disaster, we have to put the much effort on better disaster preparedness. The Tsunami Reduction Of Impacts through three Key Actions (TROIKA) was suggested by Eddie N. Bernard, the director of NOAA/PMEL (Pacific Marine Environmental Laboratory). They are Hazard Assessment, Mitigation and Warning Guidance. The satellite remote sensing has potential on these actions. The medium and high resolution satellite data were used to assess the degree of damage at the six-damaged provinces on the Andaman seacoast of Thailand. Fast and reliable interpretation of the damage by remote sensing method can be used for inundation mapping, rehabilitation and housing plans for the victims. For tsunami mitigation, the satellite data can be used with GIS to construct the evacuation map (evacuation route and refuge site) and coastal zone management. It is also helpful for educational program for local residents and school systems. Tsunami is a kind of ocean wave, therefore any satellite sensors such as SAR, Altimeter, MODIS, Landsat, SPOT, IKONOS can detect the tsunami wave in 2004. The satellite images have shown the characteristics of tsunami wave approaching the coast. For warning, satellite data has potential for early warning to detect the tsunami wave in deep ocean, if there are enough satellite constellation to monitor and detect the first tsunami wave like the pressure gauge, seismograph and tide gauge with the DART buoy can do. Moreover, the new methods should be developed to analyse the satellite data more faster for early warning procedure.