• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.116-121
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• 1998

Global land related datasets such as land use, land cover, vegetation cover percentage, forest cover percentage, are part of important global geospatial environmental datasets for global change studies. Since land cover varies place by place, continental production of dataset is a usual approach. Western academically developed countries have some projects to describe land cover related information in digital form using remote sensing technology in African, American continent and Oceania. In this paper, the author introduce his initiative to coordinate Asian scientists in order to develop land related dataset of Asia for our better understanding of the environment of Asia and for contribution to the development of global dataset. This paper explains activities by Land Cover Working Group (LCWG) of the Asian Association on Remote Sensing(AARS), Data and Information System(DIS) sub-committee of Japan national committee for the International Geosphere and Biosphere Program(IGBP), and the International Society for Photogrammetry and Remote Sensing(ISPRS) Working Group IV/6 on Global databases supporting environmental monitoring.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.567-569
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• 2003

Because of the limited land resources, an efficient land use management to reach the sustainable development policy has become an urgent call in Taiwan. A long-term project entitled 'National land use monitoring program-the establishment of a land use change detection system' has been jointly conducted by both National Central University and Ministry of Interior since year of 2001. The main aim of the project is to use the remote sensing images to detect the land use changes on a national scale. This plan has been put into practice and indeed provides an effective assistance for land management.

• Journal of Environmental Impact Assessment
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• v.22 no.2
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• pp.147-156
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• 2013

Myanmar(Burma) has been preserved valuable environmental resources because of its political isolation. But recently, Myanmar has moved a capital city(Naypyidaw) at central forest area and it has been urbanized radically since 2005. In this paper, we built multi-temporal land cover map from Landsat images of 1970s to 2012 with ENVI 4.5 software. For a broad approach, administrative district Yamethin which includes Naypyidaw is classified into 3 classes and with only Naypyidaw region is classified with 4-5 classes to analyse specific changes. And with forest cover extracted by Object Oriented Classification, we evaluated forest fragmentation before and after the development using Patch Analyst(FRAGSTATs 3.3) at Yamethin area. For Yamethin area, there were significant forest cover change, 51% in 1999 to 48% in 2012, and for Naypyidaw area, 67% in 1999 to 57% in 2012 respectively. Also landscape indices resulted from Patch Analyst concluded that the total edge, edge density and mean shaped index of forest patches increased and total core area is decreased. It is attributed from land cover change with urbanization and agricultural land expansion.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.113-122
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• 2021

Urban expansion, particularly converting sub-urban areas to residential and commercial land use in metropolitan areas, has been considered as a significant signal of regional economic development. However, this results in urban climate change. One of the key impacts of rapid urbanization on the environment is the effect of UHI (Urban Heat Island). Understanding the effects of urban land cover change on UHI is crucial for improving the ecology and sustainability of cities. This research reports an application of remote sensing data, GIS (Geographic Information Systems) for assessing effects of urban land cover change on the LST (Land Surface Temperature) and heat budget components in Ho Chi Minh City, where is one of the fastest urbanizing region of Vietnam. The change of urban land cover component and LST in the city was derived by using multi-temporal Landsat data for the period of 1998 - 2020. The analysis showed that, from 1998 to 2020 the city had been drastically urbanized into multiple directions, with the urban areas increasing from approximately 125.281 km² in 1998 to 162.6 km² in 2007, and 267.2 km² in 2020, respectively. The results of retrieved LST revealed the radiant temperature for 1998 ranging from 20.2℃ to 31.2℃, while that for 2020 remarkably higher ranging from 22.1℃ to 42.3℃. The results also revealed that given the same percentage of urban land cover components, vegetation area is more effective to reduce the value of LST, meanwhile the impervious surface is the most effective factor to increase the value of the LST.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.44-55
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• 2018

The importance of establishing a greenhouse gas inventory is emerging for policymaking and its implementation to cope with climate change. Thus, it is needed to establish Approach 3 level Land Use, Land-Use Change and Forestry (LULUCF) matrix that is spatially explicit regarding land use classifications and changes. In this study, four types of spatial information suitable for establishing the LULUCF matrix were analyzed - Cadastral Map, Land Cover Map, Forest Map, and Biotope Map. This research analyzed the classification properties of each type of spatial information and compared the quantitative and qualitative characteristics of the maps in Boryeong city. Drawn from the conclusions of the quantitative comparison, the forest area showed the maximum difference of 50.42% ($303.79km^2$) in the forest map and 46.09%($276.65km^2$) in the cadastral map. The qualitative comparison drew five qualitative characteristics: data construction scope difference, data construction purpose difference, classification standard difference, and classification item difference. As a result of the study, it was evident that the biotope map was the most appropriate spatial information for the establishment of the LULUCF matrix. In addition, if the LULUCF matrix is made by integrating the biotope, the forest map, and the land cover map, the limitations of each spatial information would be improved. The accuracy of the LULUCF matrix is expected to be improved when the map of the level-3 land cover map and the biotope map of 1:5,000 covering the whole country are completed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.249-260
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• 2017

UHI (Urban Heat Island) is an important environmental issue occurring in highly developed (or urbanized) area such as Seoul Metropolitan City of Korea due to modification of the land surface by man-made structures. With the advance of the remote sensing technique, land cover types and LST (Land Surface Temperature) influencing UHI were frequently investigated describing that they have a positive relationship. However, the concept of land cover considers material characteristics of the urban cover in a comprehensive way and does not provide information on how human activities influence on LST in detail. Instead, land use reflects ways of land use management and human life patterns and behaviors, and explains the relationship with human activities in more details. Using this concept, LST was segmented according to land use types from the Landsat imagery to identify the human-induced heat from the surface and interannual and seasonal variation of LST with GIS. The result showed that the LST intensity of Seoul was greatest in the industrial area and followed by the commercial and residential areas. In terms of size, the residential area could be defined as the major contributor among six urban land use types (i.e., residential, industrial, commercial, transportation, etc.) affecting UHI during daytime in Seoul. For temperature, the industrial area was highest and could be defined as a major contributor. It was found that land use type was more appropriate to understand the human-induced effect on LST rather than land cover. Also, there was no significant change in the interannual pattern of LST in Seoul but the seasonal difference provided a trigger that the human life pattern could be identified from the satellite-derived LST.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.3
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• pp.20-30
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• 2000

Average annual NDVI values from the NOAA/NASA Pathfinder AVHRR Land Data Sets from 1982 to 1994 showed comprehensive systematic displacement patterns in Asia. Inter-annual growing season data, however, did not show such systematic patterns. The most likely cause for the abrupt displacements, which appear especially in 1982, 1989 and 1990, may be changes in satellite sensors, although global warming, El Ni$\tilde{n}$o-Southern Oscillation events, changes in processing algorithms, and changes in land-use patterns in various parts of Asia may also play some role. The results suggest that researchers must be extremely careful in their inter-annual global change research, since direct use of the raw data could cause unexpected results. Growing-season NDVI shows decreases throughout most of Southeast Asia and modest gains in northern China and some parts in India, which could be related to land-use and land-cover changes.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• Spatial Information Research
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• v.2 no.1
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• pp.47-51
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• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.69-88
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• 2023

Efficient spatial planning is one of the necessary factors to successfully respond to climate change. And researchers often use LULC(Land-Use/Cover) data to conduct land use and spatial planning research. However, LULC data has a limited number of grades related to urban surface, so each different urban structure appearing in several cities is not easily analyzed with existing land cover products. This limitation of land cover data seems to be overcome through LCZ(Local Climate Zone) data used in the urban heat island field. Therefore, this study aims to first discuss whether LCZ data can be applied not only to urban heat island fields but also to other fields, and secondly, whether LCZ data still have problems with existing LULC data. Research methodology is largely divided into two categories. First, through literature review, studies in the fields of climate, land use, and urban spatial structure related to LCZ are synthesized to analyze what research LCZ data is currently being used, and how it can be applied and utilized in the fields of land use and urban spatial structure. Next, the GIS spatial analysis methodology is used to analyze whether LCZ still has several errors that are found in the LULC.