• Journal of the Korean Association of Geographic Information Studies
• /
• v.10 no.3
• /
• pp.31-39
• /
• 2007

In this study, the hydrosphere change of the Daecheong dam basin was detected qualitatively and quantitatively using Landsat satellite images until recentness since the construction of Daecheong dam. The hydrosphere change of the basin was analyzed by applying supervised classification about Landsat satellite images which were classified according to the hydrosphere, vegetation, road and etc. for four distinct years which are 1981, 1987, 1993, and 2002 year. Landsat satellite images of each year were achieved overlay analysis with extracting only the hydrosphere, and though these results, the hydrosphere change of the Daecheong dam basin was monitored efficiently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.2
• /
• pp.189-197
• /
• 2012

This research attempted to find possibilities of the practical use utilizing geospatial methods for the balanced promotion of sustainable coastal development and preservation through a case study of Jekyll Island, one of Georgia's barrier islands. In response, this research provided ways for practical use in sustainable development and preservation plans. First this research thoroughly investigated the 1996 master plan of Jekyll Island and tried to recalculate developed and undeveloped areas. Second, new estimations for developed areas were investigated through field survey. Third, this research proposed the use of the satellite images with different levels of spatial resolutions and tested different classification schemes to find possibilities for practical use. For these purposes, first, we classified developed and undeveloped features by manual digitization using an aerial photo image with 0.5m spatial resolution. Second, a Landsat 7 ETM+ and a QuickBird satellite images with mid- and high-levels of spatial resolutions were applied to identify developed and undeveloped areas using both the National Land Cover Data (NLCD) and the Coastal Change Analysis Program (CCAP) classification schemes. Also, GEOBIA (Geographic Object-Based Image Analysis) was conducted to accurately identify developed and undeveloped areas.

• Journal of Korea Society of Industrial Information Systems
• /
• v.7 no.1
• /
• pp.27-33
• /
• 2002

The objective of this research is to develop a new module which can reuse XML data by modifying the property of satellite images through the client's GUI at remote site. In order to implement this functionality, we used DOM interface which increases the efficiency of accessing the document structure, and loaded the developed GUI that could resort, retrieve and manage the satellite image list as converted XML data. The system was applied to the management system of satellite images in the Research Institute of SFC at Keio University which results in the confirmation of the technical functionalities.

• Korean Journal of Remote Sensing
• /
• v.20 no.4
• /
• pp.253-259
• /
• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat + ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by National Geographic Information based on aerial photograph and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The classification result by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2003.10a
• /
• pp.379-384
• /
• 2003

In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixel-based methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from high-resolution satellite images. This system enables fast process of the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.

• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.294-296
• /
• 2006

Recently the development of GIS and spatial information technology is used to construct very detail forest information. In addition, in order to classify forest characteristic, the geographical characteristic information of forest could be very useful for the forest classification, In this study sampling points were arranged to clarify the difference between the orm area and the land forest area. Also, forest feature pattern could be discriminated by using satellite images and SML. This study result should be constructed to efficiency forest management in especially forest area in Jeju Island

• Journal of the Korean GEO-environmental Society
• /
• v.6 no.4
• /
• pp.73-80
• /
• 2005

The domestic Remote Sensing field uses mainly Landsat TM image that is used to the monitoring of the wide area. In this study, it is analyzed the land cover change of rural and urban area by time series using satellite images and is proposed the vision for a urban balanced development. It execute an analysis for urban change which is a fundamental data of city planning through the integration of the spatial analysis technique of GIS and Remote Sensing using satellite data.

• International journal of advanced smart convergence
• /
• v.10 no.1
• /
• pp.216-224
• /
• 2021

Aim of this research was to classify forest types at Wando in Jeonnam Province and develop warm temperate forest management system with application of Remote Sensing and GIS. Another emphasis was given to the analysis of satellite images to compare forest type changes over 10 year periods from 2009 to 2019. We have accomplished this study by using ArcGIS Pro and ENVI. For this research, Landsat satellite images were obtained by means of terrestrial, airborne and satellite imagery. Based on the field survey data, all land uses and forest types were divided into 5 forest classes; Evergreen broad-leaved forest, Evergreen Coniferous forest, Deciduous broad-leaved forest, Mixed fores, and others. Supervised classification was carried out with a random forest classifier based on manually collected training polygons in ROI. Accuracy assessment of the different forest types and land-cover classifications was calculated based on the reference polygons. Comparison of forest changes over 10 year periods resulted in different vegetation biomass volumes, producing the loss of deciduous forests in 2019 probably due to the expansion of residential areas and rapid deforestation.

• Bulletin of the Korean Space Science Society
• /
• 1995.10a
• /
• pp.15-15
• /
• 1995

No Abstract, See Full Text

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.5
• /
• pp.413-422
• /
• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.