• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.44-51
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• 2021

Rapid urbanization and population growth have caused substantial land use land cover (LULC) change in the Kathmandu valley. The lack of temporal and geographical data regarding LULC in the middle mountain region like Kathmandu has been challenging to assess the changes that have occurred. The purpose of this study is to investigate the changes in LULC in Chandragiri Municipality between 1996 and 2017 using geographical information system (GIS) and remote sensing. Using Landsat imageries of 1996 and 2017, this study analyzed the LULC change over 21 years. The images were classified using the Maximum Likelihood classification method and post classified using the change detection technique in GIS. The result shows that severe land cover changes have occurred in the Forest (11.63%), Built-up areas (3.68%), Agriculture (-11.26%), Shrubland (-0.15%), and Bareland (-3.91%) in the region from 1996 to 2017. This paper highlights the use of GIS and remote sensing in understanding the changes in LULC in the south-west part of Kathmandu valley.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.575-579
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• 2006

The land use in suburban area has been changed rapidly due to the urban expansion in Korea during the last few decades. And such land use changes result in various environmental problems such as biodiversity decrease, habitat fragmentation, air pollution and urban heat island. Remote Sensing (RS) and Geographical Information Systems (GIS) can be used for land cover change detection to understand the impact and trend of the land use change. Change detection is the process of identifying differences in the state of an object or phenomenon by observing it at different times and it can provide quantitative and comparative information for the land use/cover change. RS is less expansive than field survey for producing land use maps, and can be accessed quickly and repetitively for large area. Also it can be used for change detection using multi-temporal land use/cover by accumulated data. Therefore, the purpose of this study is to detect and quantitatively evaluate urban land cover change in urban stream watershed area for the last few decades and ultimately to provide the basic data for urban land use planning and management.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.1-13
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• 2016

In an effort to establish adaptive measures for low carbon use and climate change, this study developed storylines for shared socio-economic reference pathways(SSP) and simulated change in land use for each storyline. First, cellular automata modeling was performed using past data, and a transition rule for the local characteristics of each planning area under study was derived by comparing with the results of the base year. Second, three storylines were formulated based on the hypothesized change in land use for the SSP. SSP1, the scenario for sustainability, assumed that the land was developed into a compact city, SSP2 assumed the development of a road through the middle of the land while maintaining the current situation, and SSP3 assumed unsustainable development into a fragmented world. Third, change in land use depending on planning area was predicted by integrating the SSP scenarios with cellular automata(CA) modeling. According to the results of analysis using the SSP scenarios, the urban area ratio increased slightly up to 2020 in SSP1 and up to 2030 in SSP2 and did not change any more subsequently, but it increased continuously until 2050 in SSP3 that assumed low level urban planning. These results on change in land use are expected to contribute towards making reasonable decisions and policies on climate change, and the outcomes of simulation derived from spatial downscaling, if applied to vulnerability assessment, will be useful to set the priority of policies on climate change adaptation.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.385-398
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• 2018

Although the importance of developing reliable and systematic GHG inventory has increased, the GIS/RS-based national scale LULUCF (Land Use, Land-Use Change and Forestry) sector analysis is insufficient in the context of the Paris Agreement. In this study, the change in $CO_2$ storage of forest land due to land use change is estimated using two GIS/RS methodologies, Sampling and Wall-to-Wall methods, from 2000 to 2010. Particularly, various imagery with sampling data and land cover maps are used for Sampling and Wall-to-Wall methods, respectively. This land use matrix of these methodologies and the national cadastral statistics are classified by six land-use categories (Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land). The difference of area between the result of Sampling methods and the cadastral statistics decreases as the sample plot distance decreases. However, the difference is not significant under a 2 km sample plot. In the 2000s, the Wall-to-Wall method showed similar results to sampling under a 2 km distance except for the Settlement category. With the Wall-to-Wall method, $CO_2$ storage is higher than that of the Sampling method. Accordingly, the Wall-to-Wall method would be more advantageous than the Sampling method in the presence of sufficient spatial data for GHG inventory assessment. These results can contribute to establish an annual report system of national greenhouse gas inventory in the LULUCF sector.

• Journal of KIISE
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• v.43 no.10
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• pp.1104-1114
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• 2016

Software is continuously changing during development and after development. When a change is required, it is difficult to precisely grasp the scope of impact intuitively. A systematic method is needed to accomplish the required change. The purpose of impact analysis on software change is to avoid missing any information by recognizing the ripple effect that the change might cause. This paper proposes a dynamic method that can easily identify the scope of change request by using the association between use-case scenarios and artifacts of UML modeling in object-oriented development environment. By using this approach, the scope of impact that the change might have on other components such as class diagram and sequence diagram in use-case scenarios can be identified by forward tracing. In addition, analysis of influence of possible further changes due to changes in other components can be identified iteratively through backward tracing. The results of this paper are not limited to impact analysis on artifacts and change type. They can also be used as basic guidelines during impact analysis for various change requests.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.383-387
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• 2007

The improved accuracy of the Land Cover/Land Use Map constructed using Hyperspectal Satellite Image and the possibility of real time classification of Land Use using optimal Band Selective Factor enable the change detection from automatic classification using the existed Land Cover/Land Use Map and the newly acquired Hyperspectral Satellite Image. In this study, the effective analysis techniques for automatic generation of training regions, automatic classification and automatic change detection are proposed to minimize the expert's interpretation for automatic update of the Land Cover/Land Use Map. The proposed algorithms performed successfully the automatic Land Cover/Land Use Map construction, automatic change detection and automatic update on the image which contained the changed region. It would increase applicability in actual services. Also, it would be expected to present the effective methods of constructing national land monitoring system.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.1
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• pp.1-10
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• 2002

The purpose of this article is to examine land use change in the fringe area of a metropolitan city through multi-temporal data analysis. Change detection has been regarded as one of the most important applications for utilization of remotely sensed imageries. Conventionally, two images were used for change detection, and Arithmetic calculators were generally used on the process. Meanwhile, multi-temporal change detection for a large number of images has been carried out. In this paper, a digital land-use map and three Landsat TM data were utilized for the multi-temporal change detection Each urban area map was extracted as a base map on the process of multi-temporal change detection. Each urban area map was converted to bit image by using boolean logic. Various urban change types could be obtained by stacking the urban area maps derived from the multi-temporal data using Geographic Information System(GIS). Urban change type map was created by using the process of piling up the bit images. Then the urban change type map was compared with each land cover map for the change detection. Dalseo-gu of Daegu city and Hwawon-eup of Dalsung-gun, the fringe area of Daegu Metropolitan city, were selected for the test area of this multi-temporal change detection method. The districts are adjacent to each other. Dalseo-gu has been developed for 30 yeais and so a large area of paddy land has been changed into a built-up area. Hwawon-eup, near by Dalseo-gu, has been influenced by the urbanization of Dalseo-gu. From 1972 to 1999, 3,507.9ha of agricultural area has been changed into other land uses, while 72.7ha of forest area has been altered. This agricultural area was designated as a 'Semi-agricultural area'by the National landuse Management Law. And it was easy for the preserved area to be changed into a built-up area once it would be included as urban area. Finally, the method of treatment and management of the preserved area needs to be changed to prevent the destruction of paddy land by urban sprawl on the urban fringe.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.397-408
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• 2003

The information about land use presents future development and vision being the basis of nation development; therefore, it is necessary to more active research that can detect wide land use and changes for the information and efficient management about land use. In this study, we wished to analyze effectively land use changes to Ansan city that is fast changing land use by the latest national land development and urbanization. this study executed land-cover classification using 4 year's Landsat TM images including Ansan city, and efficiently could manage the result of land-cover changes through Arc/Info GRID analysis. Especially, by using change detection system that is developed in this research, we could variously detect land-cover changes, and query and search easily past land-cover changes of pixels that correspond to specific region.

• Journal of Environmental Impact Assessment
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• v.4 no.2
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• pp.23-28
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• 1995

Remote sensing begins to be applied in Environmental Impact Assessment(EIA), and it can systematically assess land use which is an important factor in EIA. This study is to predict land use change of Ulsan region and to assess impact on land use using the past and the present data of remote sensing. Also we analyzed an impact area influenced by EIA projects through the integration of remote sensing and GIS. This technique will be applied to the screening stage in EIA.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.59-65
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• 2005

It is very important to detect land cover/land use change from the past and to use it for future urban plan. This paper investigated the application of Landsat satellite imagery for detecting urban growth and assessing its impact on surface temperature in the region. Land cover/land use change detection was carried out by using 30m resolution Landsat satellite images and hierarchial approach was introduced to detect more detail change on the changing area through high resolution aerial photos. Also, surface temperature according to land cover/land use was calculated from Landsat TM thermal infrared data and compared with real temperature to analyze the relationship between urban expansion and surface temperature. As a result, the urban expansion has raised surface radiant temperature in the urbanized area. The method using remote sensing data based on GIS was found to be effective in monitoring and analysing urban growth and in evaluating urbanization impact on surface temperature.