• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.439-442
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• 1999

It is important to analyze the seasonal change profiles of land cover type in large scale for establishing preservation strategy and environmental monitoring. Because the NOAA-AVHRR data sets provide global data with high temporal resolution, it is suitable for the land cover classification of the large area. The objectives of this study were to classify land cover of Korea, to investigate the phenological profiles of land cover. The NOAA-AVHRR data from Jan. 1998 to Dec. 1998 were received by Korea Ocean Research & Development Institute(KORDI) and were used for this study. The NDVI data were produced from this data. And monthly maximum value composite data were made for reducing cloud effect and temporal classification. And the data were classified using the method of supervised classification. To label the land cover classes, they were classified again using generalized vegetation map and Landsat-TM classified image. And the profiles of each class was analyzed according to each month. Results of this study can be summarized as follows. First, it was verified that the use of vegetation map and TM classified map was available to obtain the temporal class labeling with NOAA-AVHRR. Second, phenological characteristics of plant communities of Korea using NOAA-AVHRR was identified. Third, NDVI of North Korea is lower on Summer than that of South Korea. And finally, Forest cover is higher than another cover types. Broadleaf forest is highest on may. Outline of covertype profiles was investigated.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.153-162
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• 2011

This study analyzed the spatio-temporal change detection of land-use and urbanization in Yongin and Anseong regions, Kyunggi Province, using three Landsat-5 TM images for 1990, 1996, and 2000. Remote sensing (RS) and geographic information system (GIS) techniques were used for image classification and result analysis. Six land-use types were classified using supervised maximum likelihood classification. In the two study areas, the land-use changed significantly, especially the decrease of arable land and forest and increase of built-up area. Spatially, the urban expansion of Yongin region showed a spreading trend mainly along the national road and expressways. But in Anseong region the expansion showed 'urban sprawl phenomenon' with irregular shape like starfish. Temporally, the urban expansion showed disparity - the growth rates of urbanized area rose from the period 1990-1996 to 1996-2000 in both study areas. The increased built-up areas were converted mainly from paddy, dry vegetation, and forest.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.181-188
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• 1997

Vegetation is an important factor in EIA(Environmental Impact Assessment) and it is assessed according to DGN(Degree of Green Naturality) in EIS(Environmental Impact Statement) preparation. But DGN has room for improvement of assessing vegetation Status. This study introduced NDVI(Normalized Difference Vegetation Index) for improving status assessment method that subjects to DGN. For the application of NDVI, Landsat TM data of Chunchon on May 2, 1989 and June 1, 1994, and data of Ulsan on November 5, 1984, November 2, 1992 and May 9, 1994 were used. It compared NDVI with DGN according to season and location. The correlation coefficient value for the spring image (1994, 0.7, p=0.01) was proved to be higher than that of autumn (1984, 0.5, p=0.01).

• Journal of Korean Society of Rural Planning
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• v.12 no.1 s.30
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• pp.75-83
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• 2006

본 연구에서는 최대우도법과 인공신경망 모형에 의해 카테고리 분류를 수행하고 각각의 분류 성능을 비교 평가하였다. 인공신경망 모형은 오류역전파 알고리즘을 이용한 것으로서 학습을 통한 은닉층의 최적노드수를 결정하여 카테고리 분류를 수행하도록 하였다. 인공신경망 최적 모형은 입력층의 노드수가 7개, 은닉층의 최적노드수가 18개, 그리고 출력층의 노드수가 5개인 것으로 구성하였다. 위성영상은 1996년에 촬영된 Landsat TM-5 영상을 사용하였고, 최대우도법과 인공신경망 모형에 의한 카테고리 분류를 위하여 각각의 카테고리에 대한 분광특성을 대표하는 지역을 절취하였다. 분류 정확도는 인공신경망 모형에 의한 방법이 90%, 최대우도법이 83%로서, 인공신경망 모형의 분류 성능이 뛰어난 것으로 나타났다. 카테고리 분류 항목인 토지 피복 상태에 따른 분류는 두 가지 방법에서 밭과 주거지의 분류오차가 큰 것으로 나타났다. 특히, 최대우도법에 의한 밭에서의 태만오차는 62.6%로서 매우 큰 값을 보였다. 이는 밭이나 주거지의 특성이 위성영상 촬영시기에 따라 나지의 형태로 분류되거나 산림, 또는 논으로도 분류되는 경향이 있기 때문인 것으로 보인다. 차후에 카테고리 분류를 위한 각각의 클래스의 보조적인 정보를 추가한다면, 카테고리 분류 향상이 이루어질 것으로 기대된다.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.306-309
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• 2004

The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the Geographic Information System (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat TM (Thermatic Mapper) satellite images; and the vegetation index value from SPOT HRV (High Resolution Visible) satellite images. Landslide hazardous areas were analysed and mapped using the landslide-occurrence factors employing the probability-frequency ratio method. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, land 'cover had relatively positive effects, and lithology had relatively negative effects on the landslide susceptibility maps in the study area. In addition, the landslide susceptibility maps using the all factors showed the relatively good results.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.240-245
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• 2006

오늘날 도시인구집중화 현상에 따른 대규모 도시개발과 도시역의 확대로 지표면의 피복 변화가 극심하게 이루어지고 있는 한편 이러한 현상으로 인해 도시의 내 외적 경관변화 뿐만 아니라 지형 및 기온상승, 바람장의 변화 등 복합적인 국지기후 변화를 초래하게 되었다. 본 연구에서는 이러한 도시의 기후 변화에 따라 청계천 복원 전의 도시 지표 열 환경 특성을 분석을 수행하고자 한다 도시지역의 열환경 분석을 위하여 기존에는 주로 Landsat TM/ETM+ 위성영상 자료를 사용하였으나 2003년 5월 위성 센서의 고장으로 위성영상 자료의 사용이 불가피하게 되었다. 이에 대체 방안으로 ASTER 영상 열적외 센서에서 취득한 지표온도 값과 현장에서 취득한 AWS자료와의 상관성 분석을 실시하였으며, 이를 기반으로 청계천 주변의 근접성 분석 및 토지이용별 지표온도 분포 패턴 등 도시 열 환경 변화 탐지 및 분석을 위하여 GIS 및 RS 분석을 실시하였다.

• Proceedings of the KSRS Conference
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• v.1
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• pp.94-97
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• 2006

Timber stand age information of timber in industrialized plantation forest is generally collected by field surveying which is labor-intensive, time-consuming, and very costly. It is also inconsistent in analyses perspective. As an alternative, The objective of this research is to present a practical solution for estimating timber age of loblolly pine plantation using Landsat thematic mapper (TM) images, shuttle radar topography mission (SRTM), and national elevation dataset (NED). A multivariate regression model was developed based upon satellite image-based information (i.e.normalized difference vegetation index (NDVI), tasseled cap (TC) transformation, and derived tree heights). A residual studentized technique was applied to remove potential outliers. After that, a refined age estimation model with a correlation coefficient R-square of 84.6% was obtained. Finally, the feasibility test of estimated model was performed by comparing estimated and measured stand ages of timber plantations using test datasets of plantation stands (2,032 stands). The result shows that the proposed method of this study can estimate loblolly pine stand age within an error of $2{\sim}3$ years in an effective and consistent way in terms of time and cost.

• Economic and Environmental Geology
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• v.29 no.5
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• pp.615-622
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• 1996

Slope stability analysis was conducted using remote sensing and Geoscientific Information System (GIS) as a part of natural hazard assessment around Chungju area. Landsat TM band 5 and 7 which contain more information about geological structure and geography are chosen and processed to analyse regional geological structure. Through image processing technique such as PCA, HFF, edge detection and enhancement, regional lineament can be mapped and identified. The lineament density map is constructed based on summed length of lineaments per unit area and the study area can be divided into 7 structural domains. Various factors of slope stability analysis such as geology, slope aspect, degree of slope, landcover, water shed as well as characterized structural domain are constructed as a database of GIS. Rating and weighting of each factor for slope stability analysis is decided by considering environmental geological characteristics of study area. Spatial analysis of regional slope stability is examined through overlaying technique of the GIS. The result of areal distribution of slope stability shows that the most unstable area is all over Jaeogae-ni, Hyangsan-ni and Mt. Daedun.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1018-1020
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• 2003

The costal area where takes up over 32% in domestic teritory is considered as very importantly because it has not only economic facilities such as harbor and an industrial complex but also recreation facilities. Moreover, the tidal flat area has been used as culture ponds and salt farms because this area is occupied by various oceanic species. Also, the tidal flat area has played an important role to purify ocean pollution and maintain an ecosystem. However, the costal ecosystem has seriously threatened by domestic reclamation projects and a large-scale tide embankment during recent 10 years in Korea. This serious problem results in loosing 34%(810$km^2$) of the entire domestic costal area. In this paper, the micro-landform in the tidal flat area, which is called as Garolim bay in Korea, is classified by using Landsat TM images also verified through a filed report. Through the result of this, the tidal flat area is expected to manage efficiently especially through analyzing sediment environment and characteristic of grain size by using satellite images.