• Spatial Information Research
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• v.2 no.2
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• pp.135-145
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• 1994

The primary purpose of this study is, using Landsat remote sensing data and a image processing software, ERDAS, to generate real data and image photographs on physical land use of the Seoul metropolitan region. The remote sensing data used in this study are Landsat MSS data (August 28, 1979) and TM data (May 31, 1991) which cover the Seoul metropolitan region of Korea. The spatial resolutions of MSS data and TM data are 57m X 79m and 30m X 30m respectively. In addition, this study aims at contrasting urbanization phases of the Seoul metropolitan region in 1979 with those in 1991, by making image photographs and statistics on physical land use. Summing up the major results, built-up area ratio within the Seoul city had been expanded from 41.9% in 1979 to 64.5% in 1991 and that within the radius of 40km of Seoul city hall had been expanded from 10.5% In 1979 to 19.8% in 1991. The data and technique developed in this study could serve as a useful tool in making various kinds of spatial plannings, that is, urban and regional planning, selection of optimal new town location, evaluation of public facilities location alternatives, etc..

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.471-476
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• 2010

This study aimed at monitoring, mapping, and assessing the land degradation in the desert area. In this research, the Landsat TM and ETM+ imageries to assess the extent of land degradation for study area during the period from 1991 to 2007. Were used to study supervized, unsupervized classfication and NDVI land cover changes in the desert area in Mongolia. The classified map consists of five classes of water, vegetation, slight desertification, middle desertification and sever desertification. It shows that for determination classfication methods and NDVI, desertification map of the study area are prepared. The result showed accounting for a clear deterioration in vegetative cover, an increase of sever desertification and a decrease in middle desertification and slight desertification respectively of the total study area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.39-47
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• 1996

This paper is to provide land cover classification techniques for large area ranged in different pathos by classifying Landsat TM data of Jeonnam province. The analyses proceeded by individual scene because acquired dates are not same in different pathes. In this processing, troubles had happened something like variation of classes can be classified in two scenes and choice problem about overlapped area. Since spatial effects in large area affect data values, it was difficult to make a selection of classes and training fields. we could present a solution about these problems by trial and error method, and found that Bayesian maximum likelihood classification and majority filtering were effective to improve classification accuracy.

• Korean Journal of Remote Sensing
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• v.8 no.2
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• pp.131-145
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• 1992

A low cost personal computer and image processing S/W were empolyed to derive Digtal Elevation Model(DEM) of tidal flat from multitemporal LANDSAT TM images, and to create three-dimensional(3D) perspective views of the tidel flat on Komso bay in west coasts of Korea. The method for generation of Digital Elevation Model(DEM) in tidal flat was considered by overlapping techniques of multitemporal LANDSAT TM images and interpolations. The boundary maps of tidal flat extracted from multitemporal images with different water high were digitally combined in x, y, z space with tide in formation and used as an inputcontour data to obtain an elevation model by interpolation using spline function. Elevation errors of less than $\pm$0.1m were achived using overlapping techniques and a spline interpolation approach, respectively. The derived DEM allows for the generation of a perspective grid and drape on the satellite image values to create a realistic terrain visualization model so that the tidal flat may be viewed from and desired direction. As the result of this study, we obtained elevation model of tidal flats which contribute to characterize of topography and monitoring of morphological evolution of tidal flats. Moreover, the modal generated here can be used for simulation of innudation according to tide and support other studies as a supplementary data set.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.79-86
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• 1999

This study was carried out to estimate the area of damaged forest and the volume of stand tree in burned area, Mt. Weol-A in eastern Chinju, Korea using digital maps derived from supervised classification of Landsat thematic mapper(TM) imagery as reference data. Criterion laser estimator and WinDENDRO$^{tm}$(v. 6.3b) system as a computer-aided tree ring measuring system were used to measure a volume and age of sampled tree. The sample site had been chosen in unburned areas having the same terrain condition and forest type of burned areas. The tree age, diameter at breast height, tree height and volume of the sample tree selected from sample site in unburned area were 27years, 20.9cm, 9.7m and $0.1396m^3$ respectively. Total stand volume of sample site was estimated $2.9316m^3$/0.04ha, Damaged stand volume evaluated to about $16,007m^3$ in the burned area of 218.4ha.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.135-148
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• 2015

This research is carried out for the land cover change detection in the Nakdong River basin before and after the 4 major rivers restoration project using the LiDAR DEM(Digital Elevation Model) and the multi-temporal Landsat imagery. Firstly the river basin polygon is generated by using the levee boundaries extracted from the LiDAR DEM, and the four river basin imagery are generated from the multi-temporal Landsat-5 TM(Thematic Mapper) and Landsat-8 OLI(Operational Land Imager) imagery by using the generated river basin polygon. Then the main land covers such as river, grass and bare soil are separately generated from the generated river basin imagery by using the image classification method, and the ratio of each land cover in the entire area is calculated. The calculated land cover changes show that the areas of grass and bare soil in the entire area have been significantly changed because of the seasonal change, while the area of the river has been significantly increased because of the increase of the water storage. This paper contributes to proposing an efficient methodology for the land cover change detection in the Nakdong River basin using the LiDAR DEM and the multi-temporal satellite imagery taken before and after the 4 major rivers restoration project.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.340-343
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• 2004

Since the tide embankment construction started in 1991, the coastal environment in and around the Saemangeum area has undergone changes rapidly, there is a need for monitoring the environmental change in this region. Owing to high temporal and spatial heterogeneity of the coastal ecosystem and processes as well as the expense with traditional filed sampling at discrete locations, satellite remote sensing measurements offer a unique perspective on mapping a large region simultaneously because of the synoptic and repeat coverage and that quantitative algorithms used for estimating constituents' concentration in the coastal environments. Thus, the main objectives of the present study are to analyze the retrieved Suspended Sediment (SS) pattern to predict changes after the commencement of the tide embankment construction work in 1991. This is accomplished with a series of the Landsat TM/ETM+ imagery acquired from 1985-2002 (a total of 18 imageries). Instead of a simple empirical algorithm, we implement an analytical SS algorithm, developed by Ahn et al. (2003), which is especially developed for estimating SS concentration (SSC) in Case-2 waters. The results show that there is a significant change in SS pattern, which is mainly influenced by the tide and tidal height after the construction of the embankment work. As the construction progressed, the distribution pattern of SS has greatly changed, and the rate of SS concentration in the gap area of the dyke of post-construction has significantly increased.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.479-482
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• 2003

Landsat-TM images were applied for evaluating the spatial variations of flow and water quality at the Saemankeum areas. For supervised classifications, the results from hydrodynamic modeling and water quality data were compared to the reflectance characteristics of the satellite images. Multiple regression analyses indicated that suspended sediment, transparency, salinity, total nitrogen, and total phosphorus showed a good relationship to the signature. Supervised classifications showed spatial variations of the water environments at the areas under construction. The results showed the satellite imagery may be applied for the project areas with a reasonable degree of accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.161-170
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• 1994

Traditional methods for the extraction of the environmental factors of waters in which environmental change is severer than in the land can not examine closely the changed phenomena because of the lack of equipments, manpower, time and cost, etc. Therefore, new practical and efficient methods are required. The research for the method to manage environment of the waters with remote sensing technology was needed. This study examined the interrelations between the data by an on-the-spot survey and Landsat TM data and presented the model for extracting factors of water quality with regression analysis and experimental formula.