• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.165-170
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• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.109-116
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• 2000

GeoNet is java-based remotely sensed image processing system. It is based on java Ibject-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing softwares made by java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increasement of remotely sensed data.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.29-37
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• 1985

A low cost image processing system based on a CROMEMCO microcomputer called KAIS-MIPS, is developed for processing remotely sensed Landsat data. It hardware system can be easily interfacd with other peripheral devices. The software system provides flexibility, expansibility, portability, and maintainability as well as extensive processing capacity. As an example, processing and land use classification of Landsat 2 data for the Inchun city and its 6vicinity in Korea are provided.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.361-369
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• 1998

Recently, the improvement of on-board satellite sensors covering hyperspectral image sensors, high spatial resolution sensors provide data on earth in diverse aspect. The application field relating remotely sensed data also varies depending on what type of job one wants. The various resolution of sensors from low to extremely high is also available on the market with a user defined specific location. The expense to purchase remote sensed data is going down compare to the cost it need past few years ago in terms of research or private use. Now, the satellite remote sensed data is used on the field of forecasting, forestry, agriculture, urban reconstruction, geology, or other research field in order to extract meaningful information by applying special techniques of image processing. There are many image processing packages available worldwide and one common aspect is that they are expensive. There need to be a advanced satellite data processing package for people who can not afford commercial packages to apply special remote sensing techniques on their data and produce valued-added product. The study was carried out with the purpose of developing a special satellite data processing package which covers almost every satellite produced data with normal image processing functions and also special functions needed on specific research field with friendly graphical user interface (GUI). And for the people with any background of remote sensing with windows platform.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.145-156
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• 2000

Clustering is the process of partitioning a data set into meaningful clusters. As the data to process increase, a laster algorithm is required than ever. In this paper, we propose a clustering algorithm to partition a multispectral remotely sensed image data set into several clusters using a hash search algorithm. The processing time of our algorithm is compared with that of clusters algorithm using other speed-up concepts. The experiment results are compared with respect to the number of bands, the number of clusters and the size of data. It is also showed that the processing time of our algorithm is shorter than that of cluster algorithms using other speed-up concepts when the size of data is relatively large.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.939-944
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• 2002

In this paper, we propose and apply new classification method to the remotely sensed image acquired from airborne multi-spectral scanner. This is a neuro-fuzzy image classifier derived from the generic model of a 3-layer fuzzy perceptron. We implement a classification software system with the proposed method for land cover image classification. Comparisons with the proposed and maximum-likelihood classifiers are also presented. The results show that the neuro-fuzzy classification method classifies more accurately than the maximum likelihood method. In comparing the maximum-likelihood classification map with the neuro-fuzzy classification map, it is apparent that there is more different as amount as 7.96% in the overall accuracy. Most of the differences are in the "Building" and "Pine tree", for which the neuro-fuzzy classifier was considerably more accurate. However, the "Bare soil" is classified more correctly with the maximum-likelihood classifier rather than the neuro-fuzzy classifier.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.75-81
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• 2014

Until recently, photogrammetric applications for processing the satellite images and remotely sensed data have been used in different structure of functions and interfaces for sensor modeling by each developer. Thus, a standardized utilization procedure was necessary to solve the problems, such as expandability, cost, inefficiency of sources which were resulted from different approaches. Therefore, National Geospatial Intelligence Agency (NGA) provided unified interfaces by developing Community Sensor Model (CSM) to sensor models in same way. In this study, we suggested the method of design and analyzed main functions needed modeling for the frame sensor using CSM Application Program Interface (API) provided by NGA. We also applied the designed structure to the modeling. The implemented CSM was verified by groundToImage and imageToGround. In the future, the active R&D is expected with using CSM due to the cost saving effect of software development and remarkable expandability of sensor.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.561-570
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• 2010

The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.13-30
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• 1997

Recent improvements of satellite remote sensing sensors which are represented by hyperspectral imaging sensors and high spatial resolution sensors provide a large amount of data, typically several hundred megabytes per one scene. Moreover, increasing information exchange via internet and information super-highway requires the developments of more active service systems for processing and analysing of remote sensing data in order to provide value-added products. In this sense, an advanced satellite data processing system is being developed to achive high performance in computing speed and efficieney in processing a huge volume of data, and to make possible network computing and easy improving, upgrading and managing of systems. JAVA internet programming language provides several advantages for developing software such as object-oriented programming, multi-threading and robust memory managent. Using these features, a satellite data processing system named as GeoPixel has been developing using JAVA language. The GeoPixel adopted newly developed techniques including object-pipe connect method between each process and multi-threading structure. In other words, this system has characteristics such as independent operating platform and efficient data processing by handling a huge volume of remote sensing data with robustness. In the evaluation of data processing capability, the satisfactory results were shown in utilizing computer resources(CPU and Memory) and processing speeds.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.151-159
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• 2004

The diversity, expansion of human activity and rapid urbanization make modem society to faced with problems like damage of nature and drain of natural resources. Under these circumstances rapid and accurate change detection techniques, which can detect wide range utilization changes, are needed for efficient management and utilization plan of national territory. In this study to perform change detection from remote sensing images, space analysis technique contained in Geographic Information System is applied. And from this technique, the software. that can execute new change detection algorithm, query, inquiry and analysis, is produced. This software is on the basis of graphic user interface and has many functions such as format conversion, grid calculation, statistical processing, display and reference. In this study, simultaneously change detection for multi-temporal satellite images can be performed and integrated one change image about four different periods was produced. Further more software user can acquire land cover change information for an specific area through querying and questioning about yearly changes. Finally making of every application module for change detection into one window based visual basic program, can be produced user convenience and automatic performances.