• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1281-1283
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• 2003

By use of RS and GIS, the QuickBird image and geographic map were used for the survey of the foreshore resources of Shanghai. The image was processed and interpreted. The distribution maps of sea dike, foreshore, vegetation, soil, hydraulic structures, landscape, topography, and so on were extracted in manual classification. These data have been integrated into the information management system for the shoreline and foreshore. It plays an important role in the evolvement analysis of the shoreline and foreshore.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.2
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• pp.55-65
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• 2008

This study was surveyed to analyze vegetation structure of mountainous wetlands in Chung-ju city and around area from September to November, 2006. 6 sites of total 15 potential mountainous wetlands were discriminated throughout field survey. By classification system of mountainous wetlands presented in manual of forest wetlands research, types of wetlands were classified into slant and a flat. Many sites were covered with land plants as Pueraria thunbergiana and so on. To understand vegetation structure of mountainous wetlands, Height, DBH (diameter at breast height), DI (Dominance Index), Sociability and Constancy were surveyed and Based on this result, a projection chart was drawn. As results, Salix koreensis in tree layer and Persicaria thunbergii and Impatiens textori in herb layer were surveyed as broadly distributed species. This study is mainly focused on vegetation condition of mountainous wetlands. But, it will be needed studying on classification system of mountainous wetland type and functional assessment for conservation or management of wetlands.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.90-96
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• 2020

Recently, a method that applies laser scanning (LS) that acquires vegetation information such as the vegetation habitat area and the size of vegetation in a point cloud format has been proposed. When LS is used to investigate the physical shape of vegetation, it has the advantage of more accurate and rapid information acquisition. However, to examine uncertainties that may arise during measurement or post-processing, the process of adjusting the data by the actual data is necessary. Therefore, in this study, the physical structure of stems, branches, and leaves of woody vegetation in an artificially formed river channel was manually investigated. The obtained results then compared with the information acquired using the three-dimensional terrestrial laser scanning (3D TLS) method, which repeatedly scanned the target vegetation in various directions to obtain relevant information with improved precision. The analysis demonstrated a negligible difference between the measurements for the diameters of vegetation and the length of stems; however, in the case of branch length measurement, a relatively more significant difference was observed. It is because the implementation of point cloud information limits the precise differentiation between branches and leaves in the canopy area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.581-590
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• 2014

With rapid land development, land category should be updated on a regular basis. However, manual field surveys have certain limitations. In this study, attempts were made to extract a feature vector considering spectral signature by parcel, PIMP (Percent Imperviousness), texture, and VIs (Vegetation Indices) based on RapidEye satellite image and cadastral map. A total of nine land categories in which feature vectors were significantly extracted from the images were selected and classified using SVM (Support Vector Machine). According to accuracy assessment, by comparing the cadastral map and classification result, the overall accuracy was 0.74. In the paddy-field category, in particular, PO acc. (producer's accuracy) and US acc. (user's accuracy) were highest at 0.85 and 0.86, respectively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Korean Journal of Ecology and Environment
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• v.56 no.2
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• pp.161-171
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• 2023

The medium-large cladoceran species Simocephalus spp. predominantly occur in habitats with developed aquatic vegetation. Accordingly, due to Simocephalus' high contribution to zooplankton community biomass in the lake's littoral zone and wetland habitats, estimating their biomass is important to understand the matter cycling based on biological interactions within the aquatic food web. In this study, we reviewed the length-weight regression equations used previously to estimate Simocephalus biomass, directly measured S. serrulatus' body specification (length, width and area) and their biomass(dry weight) using instruments such as a microscopic digital camera and a microscale, and performed regression analysis between each other. When S. serrulatus biomass was estimated using the equation (Kawabata and Urabe, 1998) presented in 『Biomonitoring Survey and Assessment Manual』, Korea, errors between estimates and measures were relatively large compared to the S. serrulatus species-specific biomass estimate equation developed by Lemke and Benke (2003). In addition, both equations showed not only increasing trends in error (estimate-measure) with increasing S. serrulatus' body length, but also in error variance among similar-sized individuals. The results of regression analysis with dry weight by body specifications indicated that the most appropriate equation for estimating the biomass of S. serrulatus was derived from the width-dry weight exponential regression equation (R²=0.9555). The review and development study of such species-specific biomass estimation equations for zooplankton can be used as a tool to understand their role and function in aquatic ecosystem food webs.