• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.239-246
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• 2010

Satellite image has capability of getting a broad data rapidly. It is possible that acquisition of change information about topography, land, ecosystem and urbanization etc. from multi-temporal satellite Images. In this study, the time-series change of vegetation has detected using four period Landsat Imageries. Also, NDVI was used to recognize the vitality of vegetation. Time series change of vegetation about study area was able to detect effectively by the results of classification and NDVI. It is expected that this study should be utilized as the decision making related to the effective management and plan establishment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.343-348
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• 1998

In this study, we extracted several terrain information using satellite and aerial images. We detected change of terrain using Landsat Thematic Mapper(TM) and aerial images which are multitemporal data. In change detection processing, we first classified satellite images by ISODATA algorithm which is an unsupervised learning algorithm, then performed change detection. By this method, we could obtain good result. Also we introduce sub-pixel concept to classify road and agriculture area in inaccessible area. In summary, in chang detection processing, we can find that the used method is efficient.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.419-422
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• 2004

This paper was carried out desertification area change detection from 1980s to 2000s per unit decade using by multitemporal satellite images (Landsat MSS, TM, ETM+). This study aims to use Spectral Mixture Analysis (SMA) to identify and classify study area. Endmembers is selected bare soil, green vegetation (GV), water body using by Minimum Noise Fraction (MNF). Endmembers used to generate increase and decrease images respective from 1980s to 1990s and from 1990s to 2000s. From the analysis of multitemporal change detection for three periods, it was apparent that the area of bare soil increased significantly, with simultaneous decrease of GV and water body. The multitemporal fraction images can be effectively used for change detection. Though there is no field survey dataset, SMA is reliable result of change detection in desertification in China.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.549-551
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• 2003

Satellite images are utilized for various purposes and many people are concerned about them. But it is necessary to process geometric correction for using of satellite images. However, common user regards geometric correction, which is basic preprocessing for satellite image, as laborious job. Therefore we should provide an automatic geometric correction method for Landsat image using GCP chip database. The GCP chip database is the collection of pieces of images with geoinformation and is provided by XML web service. More specifically, XML web service enables common users to easily use our GCP chip database for their own geometric correcting applications.

• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.341-350
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• 2014

Landsat images can monitor the snow-covered Earth surface variations with the ground resolution of 30m and the multi-spectral bands in the visible, NIR, SWIR and TIR spectral regions for the last 30 years. The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, and all of the volcanoes are covered with snow at the top of mountain. Snow cover area in southern province of the SVZ of Chile (37 to $46^{\circ}S$) have been influenced by significant frontal retreats as well as eruptive activities. In this study, we have investigated the changes of the snow-cover area and snow-line elevation at Mt. Villarrica and Mt. Llaima, Chile from three Landsat images acquired on Feb. 1990, 2005 and 2011. The snow-cover areas are 13.42, 26.75 and $21.60km^2$ at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 3.82, 25.12 and $8.89km^2$ at Mt. Llaima in 1990, 2005 and 2011, respectively. The snow-line elevations are 1871, 1738 and 1826m at Mt. Villarrica in 1990, 2005 and 2011, respectively, and 2007, 1822 and 1818m at Mt. Llaima in 1990, 2005 and 2011, respectively. The results indicate that both of the snow-cover and snow-line changes are strongly related with the volcanic activity change. The results demonstrate that the snow-cover area and snow-line elevation changes can be used as an indicator of the volcanic activity at Mt. Villarrica and Mt. Llaima, Chile.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.39-48
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• 2011

Global warming causes the climate change and makes severe damage to ecosystem and civilization Carbon dioxide greatly contributes to global warming, thus many studies have been conducted to estimate the forest biomass carbon stock as an important carbon storage. However, more studies are required for the selection and use of technique and remotely sensed data suitable for the carbon stock estimation in Korea In this study, the aboveground forest biomass carbon stocks of Danyang-Gun in South Korea was estimated using $k$NN($k$-Nearest Neighbor) algorithm and regression model, then the results were compared. The Landsat TM and 5th NFI(National Forest Inventory) data were prepared, and ratio images, which are effective in topographic effect correction and distinction of forest biomass, were also used. Consequently, it was found that $k$NN algorithm was better than regression model to estimate the forest carbon stocks in Danyang-Gun, and there was no significant improvement in terms of accuracy for the use of ratio images.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.73-86
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• 2000

This study focused on extracting an efficient method in the fruit cropping distribution mapping with various classification methods using multi-temporal satellite images and Geographic Information Systems(GIS). For this study, multi-temporal Landsat TM images, in observation data and existing fruit cropping area statistics were used to compare and analyze the properties of fruit cropping and seasonal distribution per classification method. As a result, this study concludes that Maximum Likelihood Method with earlier autumn satellite image was most efficient for the fruit cropping mapping using Landsat TM image. In addition, it was clarified that cropping area per administrative boundary was prepared and distribution pattern was identified efficiently using GIS spatial analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.15-23
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• 2004

In order to utilize remote sensed images effectively, it is necessary to correct geometric distortion. Geometric correction is a critical step to remove geometric distortions in satellite images. For geometric correction, Ground Control Points (GCPs) have to be chosen carefully to guarantee the quality of geocoded satellite images, digital maps, GPS surveying or other data. Traditional approach to geometric correction used GCPs requires substantial human operations. Also that is necessary much time and manpower. In this paper, we presented an on-line automatic geometric correction by constructing GCP Chip database. The Proposed on-line automatic geometric correction system is consists of four part. Input image, control the GCP Chip, revision of selected GCP, and output setting part. In conclusion, developed system reduced the processing time and energy for tedious manual geometric correction and promoted usage of Landsat imagery.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.383-392
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• 1993

Identification of rice paddy fields and estimation of their areas from the images taken by LANDSAT-5/TM were attempted. The results were verified by aerial photographs and also by ground observations. Changes of the spectral characteristics of rice plants were measured with a portable spectroradiometer during the growth period. Analyzing these characteristics, an index was developed for evaluating the growth and the yield of rice . Applying the index to the data observed by LANDSAT-5.TM on Sep. 26, 1986, Oct .20, 1989 and Sep, 21, 1990, it was confirmed that the estimated derived from the index agreed with actual values. The results well demonstrated its feasibility for evaluating the yield of rice by a satellite like LANDSAT-5/TM.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.765-770
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• 1999

The purpose of this study is to obtain land classification map by using remotely sensed data; Landsat TM and SPOT panchromatic, and to compare their results with statistical data and digitized coverage from topographic paper map. The classification was conducted by maximum likelihood method with training sets. The best result was obtained from the Landsat TM merged by SPOT Panchromatic, that is, similar with statistical data. This is caused by setting more precise training sets with the enhanced spatial resolution by using SPOT Panchromatic. The classified map may be useful as a fundamental data to estimate pollutant load in regional scale of agricultural watershed.