• Journal of Forest and Environmental Science
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• 제33권4호
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• pp.295-304
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• 2017

This study compared and analyzed the construction of a land use change matrix for the Intergovernmental Panel on Climate Change's (IPCC) land use, land use change, and forestry area (LULUCF). We used National Forest Inventory (NFI) permanent sample plots (with a sample intensity of 4 km) and permanent sample plots with 500 m sampling intensity. The land use change matrix was formed using the point sampling method, Level-2 Land Cover Maps, and forest aerial photographs (3rd and 4th series). The land use change matrix using the land cover map indicated that the annual change in area was the highest for forests and cropland; the cropland area decreased over time. We evaluated the uncertainty of the land use change matrix. Our results indicated that the forest land use, which had the most sampling, had the lowest uncertainty, while the grassland and wetlands had the highest uncertainty and the least sampling. The uncertainty was higher for the 4 km sampling intensity than for the 500 m sampling intensity, which indicates the importance of selecting the appropriate sample size when constructing a national land use change matrix.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.47-49
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• 2003

Automatic land use and land cover change (LUCC) detection via remotely sensed imagery has a wide application in the area of LUCC research, nature resource and environment monitoring and protection. Under the condition that one time (T1) data is existed land use and land cover maps, and another time (T2) data is remotely sensed imagery, how to detect change automatically is still an unresolved issue. This paper developed a land use and land cover class knowledge guided method for automatic change detection under this situation. Firstly, the land use and land cover map in T1 and remote sensing images in T2 were registered and superimposed precisely. Secondly, the remotely sensed knowledge database of all land use and land cover classes was constructed based on the unchanged parcels in T1 map. Thirdly, guided by T1 land use and land cover map, feature statistics for each parcel or pixel in RS images were extracted. Finally, land use and land cover changes were found and the change class was recognized through the automatic matching between the knowledge database of remote sensing information of land use & land cover classes and the extracted statistics in that parcel or pixel. Experimental results and some actual applications show the efficiency of this method.

• 농업과학연구
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• 제47권4호
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• pp.933-940
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• 2020

Land-use change matrix data is important for calculating the LULUCF (land use, land use change and forestry) sector of the national greenhouse gas inventory. In this study, land cover changes in 2004 and 2019 were compared using the Wall-to-Wall technique with a land cover map of Sejong City from the Ministry of Environment. Sejong City was classified into six land use classes according to the Intergovernmental Panel on Climate Change (IPCC) guidelines: Forest land, crop land, grassland, wetland, settlement and other land. The coordinate system of the land cover maps of 2004 and 2019 were harmonized and the land use was reclassified. The results indicate that during the 15 years from 2004 to 2019 forestlands and croplands decreased from 50.4% (234.2 ㎢) and 34.6% (161.0 ㎢) to 43.4% (201.7 ㎢) and 20.7% (96.2 ㎢), respectively, while Settlement and Other land area increased significantly from 8.9% (41.1 ㎢) and 1.4% (6.9 ㎢) to 35.6% (119.0 ㎢) and 6.5% (30.3 ㎢). 79.㎢ of cropland area (96.2 ㎢) in 2019 was maintained as cropland, and 8.8 ㎢, 1.7 ㎢, 0.5 ㎢, 5.4 ㎢, and 0.4 ㎢ were converted from forestland, grassland, wetland, and settlement, respectively. This research, however, is subject to several limitations. The uncertainty of the land use change matrix when using the wall-to-wall technique depends on the accuracy of the utilized land cover map. Also, the land cover maps have different resolutions and different classification criteria for each production period. Despite these limitations, creating a land use change matrix using the Wall-to-Wall technique with a Land cover map has great advantages of saving time and money.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1221-1223
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• 2003

With speediness of economy, the structure of land use has taken lots of change. How can we quickly and exactly obtain detailed land use/cover change information, and then we know land resource amount, quality, distributing and change direction. More and more high resolution satellite systems are under development. So we can make good use of RS data, existed GIS data and GPS data to extract change information and update map. In this paper a fully automated approach for detecting land use/cover change using remote sensing data with object-oriented classification based on GIS data, GPS data is presented (referring to Fig.1). At same time, I realize integrating raster with vector methods of updating the basic land use/land cover map based on 3S technology and this is becoming one of the most important developing direction in 3S application fields; land-use and cover change fields over the world. It has been successful applied in two tasks of The Ministry of Land and Resources P.R.C and taken some of benefit.

• 환경영향평가
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• 제22권1호
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• pp.109-116
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• 2013

By IPCC climate change scenario, the socioeconomic actions such as the land use change are closely associated with the climate change as an up zoning action of urban development to increase green gas emission to atmosphere. Prediction of the land use change with rational quality can provide better data for understanding of the climate change in future. This study aims to predict land use change of Cheongju in future and SLEUTH model is used to anticipate with the status quo condition, in which the pattern of land use change in future follows the chronical tendency of land use change during last 25 years. From 40 years prediction since 2000 year, the area urbanized compared with 2000 year increases up to 87.8% in 2040 year. The ratios of the area urbanized from agricultural area and natural area in 2040 are decreased to 53.1% and 15.3%, respectively.

• 대기
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• 제25권3호
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• pp.483-499
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• 2015

This study examined the impact of change of land-use and meteorological condition due to urbanization on heat environment in Seoul metropolitan area over a decade (2000 and 2009) using Weather Research and Forecasting (WRF)-Urban Canopy Model (UCM). The numerical simulations consist of three sets: meteorological conditions of (1) October 2000 with land-use data in 2000 (base simulation), (2) October 2009 with land-use data in 2000 (meteorological condition change effect) and (3) October 2009 with land-use data in 2009 (both the effects of land-use and meteorological condition change). According to the experiment results, the change of land-use and meteorological condition by urbanization over a decade showed different contribution to the change of heat environment in Seoul metropolitan area. There was about $1^{\circ}C$ increase in near-surface (2 m) temperature over all of the analyzed stations due to meteorological condition change. In stations where the land-use type changed into urban, large temperature increase at nighttime was observed by combined effects of meteorological condition and land-use changes (maximum $4.23^{\circ}C$). Urban heat island (UHI) over $3^{\circ}C$ (temperature difference between Seoul and Okcheon) increased 5.24% due to the meteorological condition change and 26.61% due to the land-use change. That is, land-use change turned out to be contributing to the strengthening of UHI more than the meteorological condition change. Moreover, the land-use change plays a major role in the increase of sensible heat flux and decrease of latent heat flux.

• 한국기후변화학회지
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• 제6권1호
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• pp.33-40
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• 2015

Forests are to be recognized as an important carbon sink under the UNFCCC that consist of above- and below-biomass, dead organic matter (DOM) such as dead wood and litter, and soil organic matter (SOM). In order to asses for DOM and SOM, however, it is relevant to land-use change matrices over last 20 years for each land-use category. In this study, a land-use change matrix was produced and its uncertainty was assessed using a point sampling technique with permanent sample plots in national forest inventory at Chungbuk province. With point sampling estimated areas at 2012 year for each land-use category were significantly similar to the true areas by given six land-use categories. Relative standard error in terms of uncertainty of land-use change among land-use categories ranged in 4.3~44.4%, excluding the other land. Forest and cropland covered relatively large areas showed lower uncertainty compared to the other land-use categories. This result showed that selected permanent samples in the NFI are able to support for producing land-use change matrix at a national or province level. If the $6^{th}$ NFI data are fully collected, the uncertainty of estimated area should be improved.

• 한국농공학회논문집
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• 제50권3호
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• pp.61-69
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• 2008

Land-use in northern Cheongju region is changing rapidly because of the increased interactions of human activities with the environment as population increases. Land-use change detection is considered essential for monitoring the growth of an urban complex. The analysis was undertaken mainly on the basis of the multi-temporal Landsat images (1991, 1992 and 2000) and DEM data in a post-classification analysis with GIS to map land-use distribution and to analyse factors influencing the land-use changes for Cheongju city. The area of each land-use category was also calculated for monitoring land-use changes. Land-use statistics revealed that substantial land-use changes have taken place and that the built-up areas have expanded by about $17.57km^2$ (11.47%) over the study period (1991 - 2000). This study illustrated an increasing trend of urban and barren lands areas with a decreasing trend of agricultural and forest areas. Land-use changes from one category to others have been clearly represented by the NDVI composite images, which were found suitable for delineating the development of urban areas and land use changes in northern Cheongju region. Rapid economic developments together with the increasing population were noted to be the major factors influencing rapid land use changes. Urban expansion has replaced urban and barren lands.

• 농촌계획
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• 제16권2호
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• pp.47-55
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• 2010

Land cover and land use change data are important in many studies including climate change and hydrological studies. Although the various theories and models have been developed, it is difficult to identify the driving factors of the land use change because land use change is related to policy options and natural and socio-economic conditions. This study is to attempt to simulate the land cover change using the CLUE model based on a statistical analysis of land-use change. CLUE model has dynamic modeling tools from the competition among land use change in between driving force and land use, so that this model depends on statistical relations between land use change and driving factors. In this study, Yongin, Icheon and Anseong were selected for the study areas, and binary logistic regression and factor analysis were performed verifying with ROC curve. Land cover probability map was also prepared to compare with the land cover data and higher probability areas are well matched with the present land cover demonstrating CLUE model applicability.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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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.