• Title/Summary/Keyword: satellite imagery

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Linear Feature Extraction from Satellite Imagery using Discontinuity-Based Segmentation Algorithm

  • Niaraki, Abolghasem Sadeghi;Kim, Kye-Hyun;Shojaei, Asghar
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.643-646
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    • 2006
  • This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

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Land Cover Classification Based on High Resolution KOMPSAT-3 Satellite Imagery Using Deep Neural Network Model (심층신경망 모델을 이용한 고해상도 KOMPSAT-3 위성영상 기반 토지피복분류)

  • MOON, Gab-Su;KIM, Kyoung-Seop;CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.3
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    • pp.252-262
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    • 2020
  • In Remote Sensing, a machine learning based SVM model is typically utilized for land cover classification. And study using neural network models is also being carried out continuously. But study using high-resolution imagery of KOMPSAT is insufficient. Therefore, the purpose of this study is to assess the accuracy of land cover classification by neural network models using high-resolution KOMPSAT-3 satellite imagery. After acquiring satellite imagery of coastal areas near Gyeongju City, training data were produced. And land cover was classified with the SVM, ANN and DNN models for the three items of water, vegetation and land. Then, the accuracy of the classification results was quantitatively assessed through error matrix: the result using DNN model showed the best with 92.0% accuracy. It is necessary to supplement the training data through future multi-temporal satellite imagery, and to carry out classifications for various items.

A Study on Three Dimensional Positioning of SPOT Satellite Imagery by Image Matching (영상정합에 의한 STOP 위성영상의 3차원 위치결정에 관한 연구)

  • 유복모;조기성;이현직;노도영
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.9 no.2
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    • pp.49-56
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    • 1991
  • In this study, 3D positioning of CCT digital imagery was done by using a personal computer image processing method to increase the economic and time efficiency of SPOT satellite imagery. Image matching technique which applies statistical theories, was applied to acqusition of satellite imagery. The reliability of these coordinates was anlysed to presente a new algorithm for three dimensional positioning necessary in digital elevation modelling and orthophoto production. In acquiring image coordinates from CCT digital satellite imagery, accuracy of planimetric and height coordinates was improved by applying the image matching technique and it was found through analysis of correlation factors between sizes of target window that 19$\times$19 pixels was the most suitable size for image coordinate acquisition. From these results, it was able to present an algorithm about utility of digital imagery in the analysis of SPOT satellite data.

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Comparative Analysis of LPF and HPF for Roads Edge Detection from High Resolution Satellite Imagery (고해상도위성영상에서 도로 경계 검출을 위한 고주파와 저주파 필터링 비교분석에 관한 연구)

  • Choi, Hyun;Kang, In-Joon
    • Journal of Korean Society for Geospatial Information Science
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    • v.14 no.3 s.37
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    • pp.3-11
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    • 2006
  • The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.

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Extraction of Urban Boundary Using Grey Level Co-Occurrence Matrix Method in Pancromatic Satellite Imagery (GLCM기법을 이용한 전정색 위성영상에서의 도시경계 추출)

  • Kim, Gi Hong;Choi, Seung Pil;Yook, Woon Soo;Sohn, Hong Gyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1D
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    • pp.211-217
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    • 2006
  • Growing urban areas modify patterns of local land use and land cover. Land use changes associated with urban expansion. One way to understand and document land use change and urbanization is to establish benchmark maps compiled from satellite imagery. Old satellite Imagery is useful data to extract urban information. CORONA is a photo satellite reconnaissance program used from 1960 to 1972 and its imagery was declassified and has been available to the public since 1995. Since CORONA images are collected with panoramic cameras, several types of geometric distortions are involved. In this study we proposed mathematical modeling method which use modified collinearity equations. After the geometric modeling, we mosaicked images. We can successfully extract urban boundaries using GLCM method and visual interpretation in CORONA (1972) and SPOT (1995) imagery and detect urban changes in Seoul quantitatively.

Geometric Corrections of Inaccessible Area Imagery by Employing a Correlative Method

  • Lee, Hong-Shik;Park, Jun-Ku;Lim, Sam-Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.10 no.5 s.23
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    • pp.67-74
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    • 2002
  • The geometriccorrection of a satellite imagery is performed by making a systematic correction with satellite ephemerides and attitude angles followed by employing the Ground Control Points (GCSs) or Digital Elevation Models (DEMs). In a remote area or an inaccessible area, however, GCPs are unavailable to be surveyed and thus they can be obtained only by reading maps, which are not accurate in reality. In this study, we performed the systematic correction process to the inaccessible area and the precise geometric correction process to the adjacent accessible area by using GCPs. Then we analyzed the correlation between the two geo-referenced Korea Multiurpose Satellite (KOMPSAT-1 EOC) images. A new geometrical correction for the inaccessible area imagery is achieved by applying the correlation to the inaccessibleimagery. By employing this new method, the accuracy of the inaccessible area imagery is significantly improved absolutely and relatively.

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A Study on Estimation of Water Depth Using Hyperspectral Satellite Imagery (초분광 위성영상을 이용한 수심산정에 관한 연구)

  • Yu, Yeong-Hwa;Kim, Youn-Soo;Lee, Sun-Gu
    • Aerospace Engineering and Technology
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    • v.7 no.1
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    • pp.216-222
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    • 2008
  • Purpose of this research is estimation of water depth by hyperspectral remote sensing in area that access of ship is difficult. This research used EO-l Hyperion satellite imagery. Atmospheric and geometric correction is executed. Compress of band used MNF transforms. Diffuse Attenuation Coefficient of target area is decided in imagery for water depth estimation. Determination of Emdmember in pixel is using Linear Spectral Unmixing techniques. Water depth estimated using this result.

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Evaluating Modified IKONOS RPC Using Pseudo GCP Data Set and Sequential Solution

  • Bang, Ki-In;Jeong, Soo;Kim, Kyung-Ok
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.82-87
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    • 2002
  • RFM is the sensor model of IKONOS imagery for end-users. IKONOS imagery vendors provide RPC (Rational Polynomial Coefficients), Ration Function Model coefficients for IKONOS, for end-users with imagery. So it is possible that end-users obtain geospatial information in their IKONOS imagery without additional any effort. But there are requirements still fur rigorous 3D positions on RPC user. Provided RPC can not satisfy user and company to generate precision 3D terrain model. In IKONOS imagery, physical sensor modeling is difficult because IKONOS vendors do not provide satellite ephemeris data and abstract sensor modeling requires many GCP well distributed in the whole image as well as other satellite imagery. Therefore RPC modification is better choice. If a few GCP are available, RPC can be modified by method which is introduced in this paper. Study on evaluation modified RPC in IKONOS reports reasonable result. Pseudo GCP generated with vendor's RPC and additional GCP make it possible through sequential solution.

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Heavy Snowfall Disaster Response using Multiple Satellite Imagery Information (다중 위성정보를 활용한 폭설재난 대응)

  • Kim, Seong Sam;Choi, Jae Won;Goo, Sin Hoi;Park, Young Jin
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.4
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    • pp.135-143
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    • 2012
  • Remote sensing which observes repeatedly the whole Earth and GIS-based decision-making technology have been utilized widely in disaster management such as early warning monitoring, damage investigation, emergent rescue and response, rapid recovery etc. In addition, various countermeasures of national level to collect timely satellite imagery in emergency have been considered through the operation of a satellite with onboard multiple sensors as well as the practical joint use of satellite imagery by collaboration with space agencies of the world. In order to respond heavy snowfall disaster occurred on the east coast of the Korean Peninsula in February 2011, snow-covered regions were analyzed and detected in this study through NDSI(Normalized Difference Snow Index) considering reflectance of wavelength for MODIS sensor and change detection algorithm using satellite imagery collected from International Charter. We present the application case of National Disaster Management Institute(NDMI) which supported timely decision-making through GIS spatial analysis with various spatial data and snow cover map.

The Change Detection from High-resolution Satellite Imagery Using Floating Window Method (이동창 방식에 의한 고해상도 위성영상에서의 변화탐지)

  • Im, Yeong-Jae;Ye, Cheol-Su;Kim, Gyeong-Ok
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.117-122
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    • 2002
  • Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

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