• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.397-408
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• 2013

The purpose of this study is to analyze water cycle area ratio and spatial evaluation of water cycle in urban area of Changwon-si, Gyeongsangnam-do. Water cycle area ratio are analyzed by using spatial data of land-cover and land-use, and Hot spot analysis of GIS program was used for spatial evaluation of water cycle. The results are as below. Firstly, the high water cycle area ratio areas were forests, parks, and rivers, but urban areas covered asphalt and concrete were low under 40%. Public institutions and co-residential of urban areas were higher than others because of high area ratio of pervious land-cover. Spatial evaluation of water cycle was analyzed to vulnerable areas there are dense residential and commercial area. These areas are really occurring frequently flooding and immersion, therefore, is required water management facilities and improvement of land-cover from impervious to pervious. In the future, it will require additionally analysis of water cycle area ratio supplemented data of water management facility and ground water.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.3
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• pp.13-26
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• 2018

This study estimated the carbon sequestration from urban green spaces in Ansan City using environmental spatial information. We examined study results of carbon sequestration from existing urban green spaces, using a land cover map (level 3). In particular, the carbon sequestration of trees by land use and the IPCC Global default value were linked with the land cover map level 3. Domestic research showed that carbon storage in urban green spaces in Ansan City was 17,927.2 tC, and the annual carbon sequestration was calculated as 2,680.5 tC/yr. On the other hand, applying the IPCC Global Default value resulted in annual carbon sequestration of 5,287.8 tC/yr, which was 2,607.3 tC/yr more that the domestic research value. This resulted from difference in detailed methodologies such as background data, sample size for on-site investigation, and measurement of tree species. The study presented a consistent assessment method to assess the sequestration of carbon from municipal urban green spaces. Furthermore, we provided basic data that could be useful in urban green space policies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of KIBIM
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• v.7 no.2
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• pp.36-43
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• 2017

Population growth and rapid urbanization has been converting large amounts of rural vegetation into urbanized areas. This human induced change has increased temperature in urban areas in comparison to adjacent rural regions. Various studies regarding to urban heat island have been conducted in different disciplines in order to analyze the environmental issue. Especially, different types of thermal infrared remote sensing data are applied to urban heat island research. This article reviews research focusing on thermal infrared remote sensing for urban heat island and urban planning studies. Seven studies of analyses for the relationships between urban heat island and other dependent indicators in urban planning discipline are reviewed. Despite of different types of thermal infrared remote sensing data, units of analysis, land use and land cover, and other dependent variable, each study results in meaningful outputs which can be implemented in urban planning strategies. As the application of thermal infrared remote sensing data is critical to measure urban heat island, it is important to understand its advantages and disadvantages for better analyses of urban heat island based on this review. Despite of its limitations - spatial resolution, overpass time, and revisiting cycle, it is meaningful to conduct future research on urban heat island with thermal infrared remote sensing data as well as its application to urban planning disciplines. Based on the results from this review, future research with remotely sensed data of urban heat island and urban planning could be modified and better results and mitigation strategies could be developed.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.5
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• pp.39-48
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• 2006

The objective of this research was to find an indirect method to estimate land surface temperature (LST) efficiently, using Landsat images. Agricultural fields including paddy fields have long been known to have multi-functions beneficial to the environment and ecology of the urban surrounding areas. Among these functions, the ambient temperature cooling (ATC) effect is widely acknowledged. However, quantitative and regional assessment of such effect has not been performed. Thermal remote sensing has been used over urban areas to assess the ATC effect, Thermal Island Effect(TIE), and as input for models of urban surface atmosphere exchange. Here, we review the use of thermal remote sensing in the study of paddy fields and urban climates, focusing primarily on the ATC effect. Landsat satellite images were used to determine the surface temperatures of different land cover types of a $44km^{2}$ study area in Cheongiu, Korea. The results show that the ATC is a function of paddy area percentage in Landsat pixels. Landsat pixels with higher paddy area percentage have much more cooling effect. The use of satellite data may contribute to a globally consistent method for analysis of ATC effect.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.763-776
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• 2021

This paper introduces a method of selecting priority update areas for subdivided land cover maps by training orthoimages and serial cadastral maps in a deep learning model. For the experiment, orthoimages and serial cadastral maps were obtained from the National Spatial Data Infrastructure Portal. Based on the VGG-16 model, 51,470 images were trained on 33 subdivided classifications within the experimental area and an accuracy evaluation was conducted. The overall accuracy was 61.42%. In addition, using the differences in the classification prediction probability of the misclassified polygon and the cosine similarity that numerically expresses the similarity of the land category features with the original subdivided land cover class, the cases were classified and the areas in which the boundary setting was incorrect and in which the image itself was determined to have a problem were identified as the priority update polygons that should be checked by operators.

• Aerospace Engineering and Technology
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• v.8 no.1
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• pp.132-137
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• 2009

This study has regard to classification by using multi-temporal SAR data. Multi-temporal JERS-1 SAR images are used for extract the land cover information and possibility. So far, land cover information extracted by high resolution aerial photo, satellite images, and field survey. This study developed on multi-temporal land cover status monitoring and coherence information mapping can be processing by L band SAR image. From July, 1997 to October, 1998 JERS SAR images (9 scenes) coherence values are analyzed and then extracted land cover information factors, so on. This technique which forms the basis of what is called SAR Interferometry or InSAR for short has also been employed in spaceborne systems. In such systems the separation of the antennas, called the baseline is obtained by utilizing a single antenna in a repeat pass.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.171-178
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• 2004

The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study was presented more better land cover classification method through an algorithm development. We accomplished FCM(Fuzzy C-Mean) classification technique with MLC (Maximum Likelihood classification) technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method. This study is used to the high-resolution(6.6m) Electro-Optical Camera(EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1(KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer(MODIS) image data(36 bands).

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.117-128
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• 2003

The purpose of this study is to analyze the characteristics of the landscape type on Chunchon by CG(computer graphics) pictures and visibility analysis. The land use CG picture and the land cover CG picture are created by using Zoning area data and DEM(digital elevation model), and by using data of land cover classification and DEM. According to the analysis result of the land cover from 1989 to 2000, the city area has increased to $7.7km^2$, the green area has diminished to $12.7km^2$. The tendency of the city area increases and the green area decreases which appear in the city area, developmental restriction zone and green area on land use. The landscape is classified into three types by cluster analysis using the area rate of the element which constitutes the land use CG picture. Type 1 is a landscape characteristics of developmental restriction zone. Type 2 is a landscape characteristics of green land and type 3 is a landscape characteristics based on city area and water area. The increase of city area and decrease of green area are shown in all landscape types of land cover CG pictures. The same tendency is seen in the place where the scenery is of high importance as a result of visible analysis. The preservation and management of the scenery to the green area are requird in developmental restriction zone are required.