• 대한원격탐사학회지
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• 제20권5호
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• pp.315-327
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• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.

• 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.

• Spatial Information Research
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• 제15권1호
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• pp.67-80
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• 2007

토지피복도는 지표면의 상태를 나타내는 자료로 특히 환경 분야에서 지역의 현황을 파악하고 정책을 수립하기 위한 기초적인 자료이다. 토지피복도를 효과적으로 제작하기 위해서는 인공위성을 이용하여 한 지표면 현황에 대한 정보를 신속하게 수집하고, 이를 지리정보로 변환하여 구축하고 관리하여야한다. 본 연구에서는 우리나라 환경부에서 구축한 중분류 토지피복도의 제작과정을 검토하고, 이를 객관적이고 구체적으로 개선하고자 한다. 이를 위하여 국내외의 토지피복도 제작 현황과 문제점을 파악한 후, 중분류 토지피복도를 제작하기 위한 구체적이고 효과적인 개선방안을 제시하였다. 본 연구에서 제시한 경계선 설정기준과 속성정보 부여기준은 기존의 토지피복도 제작과정에서 나타난 문제점을 보완할 수 있었다.

• 대기
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• 제20권4호
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• pp.415-426
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• 2010

A Land cover map over East Asian region (Kongju national university Land Cover map: KLC) is classified by using support vector machine (SVM) and evaluated with ground truth data. The basic input data are the recent three years (2006-2008) of MODIS (MODerate Imaging Spectriradiometer) NDVI (normalized difference vegetation index) data. The spatial resolution and temporal frequency of MODIS NDVI are 1km and 16 days, respectively. To minimize the number of cloud contaminated pixels in the MODIS NDVI data, the maximum value composite is applied to the 16 days data. And correction of cloud contaminated pixels based on the spatiotemporal continuity assumption are applied to the monthly NDVI data. To reduce the dataset and improve the classification quality, 9 phenological data, such as, NDVI maximum, amplitude, average, and others, derived from the corrected monthly NDVI data. The 3 types of land cover maps (International Geosphere Biosphere Programme: IGBP, University of Maryland: UMd, and MODIS) were used to build up a "quasi" ground truth data set, which were composed of pixels where the three land cover maps classified as the same land cover type. The classification results show that the fractions of broadleaf trees and grasslands are greater, but those of the croplands and needleleaf trees are smaller compared to those of the IGBP or UMd. The validation results using in-situ observation database show that the percentages of pixels in agreement with the observations are 80%, 77%, 63%, 57% in MODIS, KLC, IGBP, UMd land cover data, respectively. The significant differences in land cover types among the MODIS, IGBP, UMd and KLC are mainly occurred at the southern China and Manchuria, where most of pixels are contaminated by cloud and snow during summer and winter, respectively. It shows that the quality of raw data is one of the most important factors in land cover classification.

• 대기
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• 제21권4호
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• pp.405-414
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• 2011

In this study, the influence of a change in land use on the local weather fields is investigated around the Lake Shihwa area using synthetic land cover data and a high-resolution mesoscale model - the Weather Research and Forecasting (WRF). The default land cover data generally used in the WRF is based on the land use category of the United States Geological Survey (USGS), which erroneously presents most land areas of the Korean Peninsula as savannas. To revise such a fault, a multi-temporal land cover data, provided by the Ministry of Environment of Korea, was employed to generate a land cover map of 2005 subject to the land use in Korea at that time. A new land cover map of 1989, before the construction of the Lake Shihwa, was made based on the 2005 map and the Landsat 4-5 TM satellite images of two years. Over the areas where the land use had been changed (e.g., from sea to wetlands, towns, etc.) due to the Lake Shihwa development project, the skin temperature decreased by up to $8^{\circ}C$ in the winter case while increased by as much as $14^{\circ}C$ in the summer case. Changes in the water vapor mixing ratio were mostly affected by advection and topography in both seasons, with considerable increase in the summer case due to continuous sea breeze. Local decrease in water vapor occurred over high land use change areas and/or over downstream of such areas where alteration in wind fields were induced by changes in skin temperature and surface roughness at the areas of land use changes. The albedo increased by about 0.1% in the regions where sea was converted into wetland. In the regions where urban areas were developed, such as Songdo New Town and Incheon International Airport, the albedo increased by up to 0.16%.

• 대한원격탐사학회지
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• 제30권4호
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• pp.511-524
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• 2014

본 연구에서는 12년(2001-2012)간의 MODerate Resolution Imaging Spectroradiometer (MODIS) 토지피복 자료를 이용하여 동북아시아 지역에 대한 토지피복 유형별 통계적 점유율과 연변동을 조사하였다. MODIS 토지피복 자료의 공간해상도는 500 m이며 토지피복 유형의 수는 17개이다. 12년 평균에서 농지(36.96%), 초지(23.14%) 그리고 혼합림(22.97%) 3가지 유형이 분석 영역의 80% 이상을 점유하고 있는 것으로 나타났고, 그 외 농지와 자연 식생의 혼합유형(6.09%), 낙엽활엽수림(4.26%), 도시(2.46%) 그리고 사바나(1.54%) 유형이 점유하고 있는 것으로 나타났다. 비록 자료의 사용 기간이 짧지만 단순회귀분석에서 상록침엽수림, 낙엽활엽수림, 혼합림은 유의수준 5%에서 점유율이 증가하는 경향을 보였으나 사바나 유형은 유의수준 5%에서 감소하는 경향을 보였다. 토지피복 유형이 매년 다르게 분류되는 화소의 비율이 10% 이상이며 토지피복 유형별 점유율의 연변동은 농지(1.41%), 혼합림(0.82%), 초지(0.73%)에서 가장 두드러지게 나타났다. 또한, 12년 동안 토지피복 유형이 1개로만 분류된 화소의 비율은 단지 57%이며, 나머지 화소들에서는 2개 이상으로 분류되었으며 최대 9개 유형으로 분류된 화소도 존재했다. 공간적으로 균질하게 1개 유형만 분포하고 있는 중국 동부와 북서부 지역을 제외한 전체 지역에서 토지피복 유형이 연도별도 다르게 분류되고 있다. 따라서 토지피복 변화에 소요되는 시간적 규모를 고려할 때 동북아시아 지역에서 MODIS 토지피복 자료를 이용할 시 주의가 필요하다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.539-542
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• 2006

To investigate the streamflow impact of land cover changes by a typhoon, WMS HEC-1 storm runoff model was applied by using land cover information before and after the typhoon. The model was calibrated with three storm events of 1985 to 1988 based on 1985 land cover condition for a 192.7 $km^2$ watershed in northeast coast of South Korea. After the model was tested, it was run to estimate impacts of land cover change by the typhoon RUSA occurred in 2002 (31 August - 1 September) with 897.5 mm rainfall. The land covers before and after the typhoon were prepared using Landsat 7 ETM+ of September 11 of 2000 and Landsat 5 TM of September 29 of 2002 respectively. For the 6.9 $km^2$ damaged area (3.6 % of the watershed), the peak runoff and total runoff by the changed land cover condition increased 12.5 % and 12.7 % for 50 years rainfall frequency and 1.4 % and 1.8 % for 500 years rainfall frequency respectively based on AMC (Antecedent Moisture Condition)-I condition.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• 대한원격탐사학회지
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• 제22권5호
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• pp.407-413
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• 2006

To investigate the streamflow impact of land cover changes by a typhoon, HEC-l storm runoff model was applied by using land cover information before and after the typhoon. The model was calibrated with three storm events of 1985 to 1988 based on 1985 land cover condition for a $192.7km^{2}$ watershed in northeast coast of South Korea. After the model was tested, it was run to estimate impacts of land cover change by the typhoon RUSA occurred in 2002 (31 August-1 September) with 897.5 mm rainfall. The land covers before and after the typhoon were prepared using Landsat 7 ETM+ of September 11 of 2000 and Landsat 5 TM of September 29 of 2002 respectively. For the $6.9km^{2}$ damaged area (3.6 % of the watershed), the peak runoff and total runoff by the changed land cover condition increased 12.5 % and 12.7 % for 50 years rainfall frequency and 1.4 % and 1.8 % for 500 years rainfall frequency respectively based on AMC (Antecedent Moisture Condition)-I condition.

• 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.