• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.6
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• pp.148-160
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• 2012

The main purpose of this paper is to deliver a climate analysis and evaluation method based on GIS by using airborne LiDAR data and Biotop type map and to provide spatial information of climate analysis and evaluation based on Biotop type Map. At first stage, the area, slope, slope length, surface, wind corridor function and width, and obstacle factors were analyzed to obtain cold/fresh air production and wind corridor evaluation. In addition, climate evaluation was derived from those two results in the second stage. Airborne LiDAR data are useful in wind corridor analysis during the study. Correlation analysis results show that ColdAir_GRD grade was highly correlated with Surface_GRD (-0.967461139) and WindCorridor_ GRD was highly correlated with Function_GRD (-0.883883476) and Obstacle_GRD (-0.834057656). Climate Evaluation GRID was highly correlated with WindCorridor_GRD (0.927554516) than ColdAir_GRD (0.855051646). Visual validations of climate analysis and evaluation results were performed by using aerial ortho-photo image, which shows that the climate evaluation results were well related with in-situ condition. At the end, we applied climate analysis and evaluation by using Biotop map and airborne LiDAR data in Gwangmyung-Shiheung City, candidate for the Bogeumjari Housing District. The results show that the aerial percentile of the 1st Grade is 18.5%, 2nd Grade is 18.2%, 3rd Grade is 30.7%, 4th Grade is 25.2%, and 5th Grade is 7.4%. This study process provided both the spatial analysis and evaluation of climate information and statistics on behalf of each Biotop type.