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토지피복지도 갱신을 위한 S2CVA 기반 무감독 변화탐지
박녕희,김동학,안재윤,최재완,박완용,박현춘 대한원격탐사학회 2017 大韓遠隔探査學會誌 Vol.33 No.6
In this study, we tried to utilize results of the change detection analysis for satellite images as the basis for updating the land cover map. The Sequential Spectral Change Vector Analysis (S2CVA) was applied to multi-temporal multispectral satellite imagery in order to extract changed areas, efficiently. Especially, we minimized the false alarm rate of unsupervised change detection due to the seasonal variation using the direction information in S2CVA. The binary image, which is the result of unsupervised change detection, was integrated with the existing land cover map using the zonal statistics. And then, object-based analysis was performed to determine the changed area. In the experiment using PlanetScope data and the land cover map of the Ministry of Environment, the change areas within the existing land cover map could be detected efficiently. 본 연구에서는 위성영상에 대한 변화탐지 기법의 결과를 토지피복지도 갱신의 기초자료로 활용하고자 하였다. S2CVA(Sequential Spectral Change Vector Analysis) 기법을 다시기 다중분광 위성영상에적용하여 해당 지역 내의 변화지역을 추출하였다. 특히, 분광변화벡터의 방향정보를 이용하여 계절적 변화에 의한 변화지역의 오탐지를 최소화하고자 하였다. 변화탐지 결과인 이진영상은 구역통계를 활용하여 토지피복도와 함께 통합하였으며, 토지피복지도 갱신을 위하여 객체 기반의 분석을 수행하였다. PlanetScope 자료와 환경부의 토지피복지도를 이용한 실험결과, 토지피복지도 내에 변화된 지역을 효과적으로 탐지할 수있음을 확인하였다.
Performance Evaluation of Pansharpening Algorithms for WorldView-3 Satellite Imagery
김구혁,박녕희,최석근,최재완 한국측량학회 2016 한국측량학회지 Vol.34 No.4
Worldview-3 satellite sensor provides panchromatic image with high-spatial resolution and 8-band multispectral images. Therefore, an image-sharpening technique, which sharpens the spatial resolution of multispectral images by using high-spatial resolution panchromatic images, is essential for various applications of Worldview-3 images based on image interpretation and processing. The existing pansharpening algorithms tend to tradeoff between spectral distortion and spatial enhancement. In this study, we applied six pansharpening algorithms to Worldview-3 satellite imagery and assessed the quality of pansharpened images qualitatively and quantitatively. We also analyzed the effects of time lag for each multispectral band during the pansharpening process. Quantitative assessment of pansharpened images was performed by comparing ERGAS (Erreur Relative Globale Adimensionnelle de Synthèse), SAM (Spectral Angle Mapper), Q-index and sCC (spatial Correlation Coefficient) based on real data set. In experiment, quantitative results obtained by MRA (Multi-Resolution Analysis)-based algorithm were better than those by the CS (Component Substitution)- based algorithm. Nevertheless, qualitative quality of spectral information was similar to each other. In addition, images obtained by the CS-based algorithm and by division of two multispectral sensors were shaper in terms of spatial quality than those obtained by the other pansharpening algorithm. Therefore, there is a need to determine a pansharpening method for Worldview-3 images for application to remote sensing data, such as spectral and spatial information-based applications.
ITPCA 기반의 무감독 변화탐지 기법을 이용한 산림황폐화 분석
최재완,박홍련,박녕희,한수희,송정헌 대한원격탐사학회 2017 大韓遠隔探査學會誌 Vol.33 No.6
In this study, we tried to analyze deforestation due to forest fire by using KOMPSAT satellite imagery. For deforestation analysis, unsupervised change detection algorithm is applied to multitemporal images. Through ITPCA (ITerative Principal Component Analysis) of NDVI (Normalized Difference Vegetation Index) generated from multitemporal satellite images before and after forest fire, changed areas due to deforestation are extracted. In addition, a post-processing method using SRTM (Shuttle Radar Topographic Mission) data is involved in order to minimize the error of change detection. As a result of the experiment using KOMPSAT-2 and 3 images, it was confirmed that changed areas due to deforestation can be efficiently extracted. 본 연구에서는 KOMPSAT 위성영상을 활용하여 산불에 의한 산림황폐화 발생 지역을 탐지하고자하였다. 산림황폐화 분석을 위하여 다시기 위성영상에 무감독 변화탐지 기법을 적용하고자 하였다. 산불 전후에 대한 다시기 영상으로부터 생성한 NDVI(Normalized Difference Vegetation Index)에 ITPCA(ITerative Principal Component Analysis)를 적용하여 산림황폐화에 의하여 발생한 변화지역을 추출하였다. 또한, SRTM(Shuttle Radar Topographic Mission)자료를 이용한 후처리 기법을 통하여 오탐지를 최소화하고자하였다. KOMPSAT-2, 3 영상을 이용한 실험결과, 해당 지역 내에 존재하는 산림황폐화 지역을 효과적으로 추출할 수 있음을 확인하였다.
박홍련(Honglyun Park),박녕희(Nyunghee Park),최재완(Jaewan Choi) 대한공간정보학회 2017 한국지형공간정보학회 학술대회 Vol.2017 No.10
본 연구에서는 교차융합영상을 이용한 무감독 변화탐지 기법을 제안하고자 한다. 이를 위하여 S²CVA(Sequential Spectral Change Vector Analysis)를 이용하여 산출한 변화크기(magnitude) 및 방향 값(direction)을 통해 최적의 변화지역을 탐지하고자 하였다. 특히, 방향 값의 특성을 분석하여 오탐지를 감소시키고자 하였다. 본 연구에서 제안한 방법을 고해상도 위성영상인 Kompsat-2에 적용한 결과 기존 방법에 비해 성능이 향상된 것을 확인하였다.
Land Cover Classification of RapidEye Satellite Images Using Tesseled Cap Transformation (TCT)
문호경,최태영,김구혁,박녕희,박홍련,최재완 대한원격탐사학회 2017 大韓遠隔探査學會誌 Vol.33 No.1
The RapidEye satellite sensor has various spectral wavelength bands, and it can capture large areas with high temporal resolution. Therefore, it affords advantages in generating various types of thematic maps, including land cover maps. In this study, we applied a supervised classification scheme to generate high-resolution land cover maps using RapidEye images. To improve the classification accuracy, object-based classification was performed by adding brightness, yellowness, and greenness bands by Tasseled Cap Transformation (TCT) and Normalized Difference Water Index (NDWI) bands. It was experimentally confirmed that the classification results obtained by adding TCT and NDWI bands as input data showed high classification accuracy compared with the land cover map generated using the original RapidEye images.