• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
• /
• pp.165-170
• /
• 1999

Previous technology of remote sensing was focused on analyzing raster image and gaining information through image processing. But now it has extended to diverse fields like automatic map generation, material exploitation or monitoring environmental changes with effort to utilizing practical usage. And with rapid expansion of information exchange on Internet and high-speed network, the demand of public which want to utilize remotely sensed image has been increased. This makes growth of service on acquisition and processing remotely sensed image. GeoNet is a Java-based remotely sensed image processing system. It is based on Java object-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing software made by Java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increase of remotely sensed data. In this paper, we introduce GeoNet and explain its architecture.

• 대한공간정보학회지
• /
• 제8권2호
• /
• pp.109-116
• /
• 2000

자바 언어를 이용하여 구축한 위성 영상 처리 소프트웨어인 GeoNet은 자바 언어의 장점을 그대로 수용하는 cross-platform 대용량 위성 영상처리 API로써의 인터페이스를 제공하며 개발 기간을 단축하는 자바 객체지향 패러다임의 기반에서 구축되었다. 네트워크 환경에서의 자바 확장성을 이용한 클라이언트/서버 이미지 처리의 적합성과 융통성 있는 시스템 구조로의 기반을 가지며 웹브라우저를 통한 실행도 GeoNet의 특징이다. 본 연구에서는 자바 언어를 통한 위성 영상 처리 소프트웨어 GeoNet의 개발을 통해 앞으로 확대될 위성 영상의 보급과 분산 환경에서의 영상 처리 요구에 신속히 대처할 수 있는 대안을 제시한다.

• 한국측량학회지
• /
• 제30권6_2호
• /
• pp.653-663
• /
• 2012

Using soft classification, it is possible to obtain the land cover proportions from the remotely sensed image. These land cover proportions are then used as input data for a procedure called "super-resolution mapping" to produce the predicted hard land cover layers at higher resolution than the original remotely sensed image. Superresolution mapping can be implemented using a number of algorithms in which the Hopfield Neural Network (HNN) has showed some advantages. The HNN has improved the land cover classification through superresolution mapping greatly with the high resolution data. However, the super-resolution mapping is based on the spatial dependence assumption, therefore it is predicted that the accuracy of resulted land cover classes depends on the relative size of spatial features and the spatial resolution of the remotely sensed image. This research is to evaluate the capability of HNN to implement the super-resolution mapping for SPOT image to create higher resolution land cover classes with different zoom factor.

• 한국측량학회지
• /
• 제31권6_2호
• /
• pp.559-565
• /
• 2013

Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

• 대한원격탐사학회지
• /
• 제13권1호
• /
• pp.31-46
• /
• 1997

최근 원격탐사영상을 이용한 서비스들(환경감시, GIS, 기상정보, 자원탐사 등)에 대한 연 구가 활발해짐에 따라, 원격탐사영상을 지정된 수신국에 등록하고, 처리하는 것이 아니라, 네트웍 을 이용해서 실시간정보를 서비스하거나, 다양한 전문지식을 가진 원격탐사영상 사용자 스스로 개별적인 원격탐사영상처리를 수행하는 것이 필요하게 되었다. 본 논문에서는 실시간에 원격탐사 영상처리를 할 수 있는시스템 구조를 제안하고, 기존의 시스템에서 처리하지 못했던 여러가지 문 제점들, 즉, 사용자가 직접 원격탐사영상을 처리할 수 없다는 점과 방대한 크기의 원격탐사영상으 로 인한 네트웍 트래픽의 낭비라는 측면을 고려하여, 현재 보편화된 인터넷을 이용하여 사용자와 수신국간의 대화식 통로를 만들고, Java 언어를 이용하여, 수신국의 영상을 효율적으로 처리할 수 있도록 사용자들이 빈번하게 사용하는 영상처리기법들을 구현하였으며, 수신국의 방대한 원격탐 사 영상을 효율적으로 관리하기 위해 객체관계형 데이타베이스 관리시스템을 이용해서 서비스를 구현하였다. 구현된 시스템은 LAN 환경에서 Netscape 웹브라우저와 IllustraDBMS를 이용하였으 며, 서비스 응답시간 측면에서 만족할 만한 성능을 보였다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.107-109
• /
• 2004

High-resolution remotely sensed data such as SPOT-5 imagery are employed to study the effectiveness of the watershed segmentation algorithm. Existing problems in this approach are identified and appropriate solutions are proposed. As a case study, the panchromatic SPOT-5 image of part of Beijing urban areas has been segmented by using the MATLAB software. In segmentation, the structuring element has been firstly created, then the gaps between objects have been exaggerated and the objects of interest are converted. After that, the intensity valleys have been detected and the watershed segmentation have been conducted. Through this process, the objects in an image are divided into separate objects. Finally, the effectiveness of the watershed segmentation approach for high-resolution imagery has been summarized. The approach to solve the problems such as over-segmentation has been proposed.

• 환경영향평가
• /
• 제10권3호
• /
• pp.167-174
• /
• 2001

National Parks in Korea occupy about four percents of South Korean land. This paper aims to prove the potentiality of the application of remotely sensed data for the effective management of National Parks. Different satellite images such as Landsat TM, IRS-1C, Alternative image, and IKONOS image are analyzed for the detection of changes, the extraction of degraded areas, and the comparison of Normalized Difference Vegetation Index (NDVI) in Bukhansan National Park. The artificial structures such as buildings and paved areas are overvalued in relatively higher resolution data. The result showed that the choice of images should be determined according to specific purposes and the combination of different resolution data may be the solution for the effective management of National Park.

• 한국농공학회:학술대회논문집
• /
• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
• /
• pp.544-549
• /
• 1999

The objective of this study is to identify the applicability of land cover image classified by remotely sensed data ; Landsat TM merged by SPOT for hydrological applications such as SCS runoff estimation . By comparing the calssified land cover image with the statistical data, it was proved that hey are agreed well with little errors. As a simple application , SCS runoff estimation was tested by varying rainfall intensity and AMC with Soilmap classfied by hydrologica soil map.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.237-240
• /
• 2004

In this study, the digital image processing with image enhancement based on homomorphic filtering was performed using geophysical imaging data such as gravity, magnetic data and sub-scenes of satellite images such as LANDSAT, IKONOS, and KOMPSAT. Windows application program for executing homomorphic filtering was designed and newly implemented. In general, homomorphic filtering is technique that is based on Fourier transform, which enhances the contrast of image by removing the low frequencies and amplifying the high frequencies in frequency domain. We can enhance the image selectively using homomorphic filtering as compared with the existing method, which enhance the image totally. Through several experiment using remotely sensed imagery and geophysical image with this program, it is concluded that homomorphic filtering is more effective to reveal distinct characteristics for some complicated and multi-associated features on image data.

• 한국농공학회:학술대회논문집
• /
• 한국농공학회 2000년도 학술발표회 발표논문집
• /
• pp.419-424
• /
• 2000

The land cover classification by using remotely sensed image becomes necessary and useful for hydrologic and water quality related applications. The purpose of this study is to obtain land classification map by using remotely sensed data : Landsat TM and KOMPSAT-1 EOC. The classification was conducted by maximum likelihood method with training set and Tasseled Cap Transform. The best result was obtain from the Landsat TM merged by KOMPSAT EOC, that is, similar with statistical data. This is caused by setting more precise training set with the enhanced spatial resolution by using KOMPSAT EOC(6.6m${\times}$6.6m).