• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.72-75
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• 2008

Image segmentation techniques becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Seeded Region Growing (SRG) and Edge Information. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying SRG. Finally the region merging process, using region adjacency graph (RAG), was carried out to get the final segmentation result. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.394-397
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• 2008

This research aimed at developing a technique for estimating the tree height using BRF (Bi-directional Reflectance Factor) through the clarification of the relation between shape of the tree crown and the tree height and the relations between the shape of the tree crown and BRF. This paper, reports the results of analyses of data acquired by field measurements done to clarify relation between crown shape and tree height.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.345-348
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• 2007

This research aimed at developing a technique for estimating the tree height using BRF (Bi-directional Reflectance Factor) through the clarification of the relation between shape of the tree crown and the tree height and the relations between the shape of the tree crown and BRF. This paper, reports the results of analyses of data acquired by field measurements done to clarify relation between crown shape and tree height.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.422-425
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• 2007

Traditionally, surface energy fluxes are obtained by model simulations or empirical equations with auxiliary meteorological data. These methods may not effectively represent the surface heat fluxes in a regional scale due to scene variability. On the other hand, remote sensing has the advantage to acquire data of a large area in an instantaneous view. The remotely sensed data can be further used to retrieve surface radiation and heat fluxes over a large area. In this study, the airborne and satellite images in conjunction with meteorological data and ground observations were used to estimate the surface heat fluxes over Taiwan's Chaiyi Plain. The results indicate that surface heat fluxes can be properly determined from both airborne and satellite images. The correlation coefficient of surface heat fluxes with in situ corresponding observations is over 0.60. We also observe that the remotely sensed data can efficiently provide a long term monitoring of surface heat fluxes over Taiwan's Chaiyi Plain.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.370-375
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• 1998

Spectral reflectance signatures of upland crops at OSMI bands were collected and evaluated for the feasibility of crop discrimination knowledge-based on crop calendar. Effective bands and their ratio values for discriminating corn from two other legumes were defined with OSMI equivalent bands and their ratio values. June 22 among measurements dates was the best date for corn discrimination from two other legumes, peanut and soybean, because all OSMI equivalent bands and their ratio values in June 22 were highly significant for corn separability. Phenological growth stage of a silage corn (rs510) could be estimated as a function of spectral reflectance signatures in vegetative stage. Five growth stage prediction models were generated by the SAS procedures REG and STEPWISE with OSMI equivalent bands and their ratio values in vegetative stage.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.52 no.4
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• pp.393-402
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• 2007

Remote sensing data can be integrated into crop models, making simulation improved. A crop model that uses remote sensing data was evaluated for its capability, which was performed through comparing three different methods of canopy measurement for cotton(Gossypium hirsutum L.). The measurement methods used were leaf area index(LAI), hand-held remotely sensed perpendicular vegetation index(PVI), and satellite remotely sensed PVI. Simulated values of cotton growth and lint yield showed reasonable agreement with the corresponding measurements when canopy measurements of LAI and hand-held remotely sensed PVI were used for model calibration. Meanwhile, simulated lint yields involving the satellite remotely sensed PVI were in rough agreement with the measured lint yields. We believe this matter could be improved by using remote sensing data obtained from finer resolution sensors. The model not only has simple input requirements but also is easy to use. It promises to expand its applicability to other regions for crop production, and to be applicable to regional crop growth monitoring and yield mapping projects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.329-332
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• 2002

In this study, we reviews the application of GIS(Geographic Information system) and RS(Remote sensing) for many fields of the fisheries and ocean science. GIS and RS plays an important role as a advanced science and technology, and becomes a powerful tool of the study and research in various fields of Earth Science. In future, GIS and RS will be greatly used to observed and predict various phenomena associated with the fisheries and ocean environments.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.500-505
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• 2002

Based on the real-time monitoring by remote sensing and dynamic management by GIS on agricultural land and water resources in arid area, we solved the practicability and popularization of small-scale spatial information service system. Through demonstration, the standards of spatial information service database of agricultural land and water resources is set up, and the agricultural land and water resources management system in Shehezi City of Xinjiang Autonomy is established, which provides periodically the spatial information services needed by agricultural production to support for sustainable development in arid area.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1310-1311
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• 2003

Oil Field Geographical Information System (OFGIS) manages multiple spatial data, attribute data, and topographic data, which include almost every kind of ground info rmation and underground information. Subsystems managed by OFGIS include petroleum exploration subsystem (PESS), petroleum development and engineering subsystem (PDESS), petrochemical subsystem (PCSS), petroleum storage and transportation subsystem (PSTSS), petroleum sale subsystem (PSSS), etc. A basic OFGIS framework consists of oil field infrastructure coverage (OFIC), oil field specialized information coverage (OFSIC) and oil field synthesis and decision service coverage (OFSDSC). Basic function of OFGIS includes database management, geographic information management, spatial information processing and application.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1209-1211
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• 2003

The wavelet and semivariogram analysis method are used to identify the city landscape and farmland landscape pattern on the 1m resolution IKONOS images. The results prove that wavelet method is a potential way for landscape pattern analysis. Compared to semivariogram analysis, Wavelet analysis can not only detect the overall spatial pattern, but also find multi-scale and direction structures. In this experiment, the wavelet analysis results indicate: (1) the city landscape image is mainly composed of three level structures whose spatial pattern characters appear at 2m, 16m, 128m and 256m accordingly; (2) the farmland landscape is mainly two scale spatial patterns appearing at the 2m, 128m and 256m. IKONOS Remote sensing, with the high spatial and spectral information, is a powerful tool that can use in many ecological systems research and sustainable management.