Since the use of UAV (Unmanned Aerial Vehicle) is convenient for the acquisition of data on broad or inaccessible regions, it is nowadays used to establish spatial information for various fields, such as the environment, ecosystem, forest, or for military purposes. In this study, the process of estimating FVC (Fractional Vegetation Cover), based on multi-spectral UAV, to overcome the limitations of conventional methods is suggested. Hence, we propose that the FVC map is generated by using multi-spectral imaging. First, two types of result classifications were obtained based on RF (Random Forest) using RGB images and NDVI (Normalized Difference Vegetation Index) with RGB images. Then, the result map was reclassified into vegetation and nonvegetation. Finally, an FVC map-based RF were generated by using pixel calculation and FVC map-based GI (Gutman and Ignatov) model were indirectly made by fixed parameters. The method of adding NDVI shows a relatively higher accuracy compared to that of adding only RGB, and in particular, the GI model shows a lower RMSE (Root Mean Square Error) with 0.182 than RF. In this regard, the availability of the GI model which uses only the values of NDVI is higher than that of RF whose accuracy varies according to the results of classification. Our results showed that the GI mode ensures the quality of the FVC if the NDVI maintained at a uniform level. This can be easily achieved by using a UAV, which can provide vegetation data to improve the estimation of FVC. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Compare to other industrial sites, the civil construction work not only takes longer time but also has made of complicated processes, such as the integrated management, process control, and quality control until the completion. However, it is hard to take control the construction sites, since numerous issues are always emerged. The study purposes on providing the dataset to synthetically manage and monitor the civil construction site, main design, drawings, process, construction cost, and others at real-time by using the low altitude closerange aerial images, based on UAV, and the GPS surveying method for treating the three-dimensional spatial information quickly and accurately. As a result, we could provide the latest information for the quick decisionmaking following from planning to completion of the construction, and objective site evaluation by the highresolution three-dimensional spatial information and drawings. Also, the present map, longitudinal map, and cross sectional view are developed to provide various datasets rapidly, such as earthwork volume This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Land characteristics should be surveyed in an accurate and objective manner as they are important data to the formation of land prices. The ambiguous survey and estimation guidelines, however, make it possible for surveyors to intervene with their subjective judgments. There is thus a definite need for improvement. It is also extremely important to survey the characteristics of individual land lots in an accurate and objective manner in order to estimate officially assessed land prices in a swift and accurate way. For objective land appraisal and evaluation, this study set out to objectively identify the characteristics of lots according to various topographical conditions by using UAV based high quality geospatial information, panorama VR images, and GIS analysis technique and thus make a contribution to a rational and consistent estimation system of officially assessed land prices. Trying to assess the technique proposed in the study, the investigator analyzed the old data about the officially assessed land prices of the subject areas and then the evaluation data of certified public appraisers.
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