• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.15-26
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• 2017

The decrease of green space according to the urbanization has caused many environmental problems as the destruction of habitat, air pollution, heat island effect. With interest growing in natural view recently, proper management of evergreen tree which is lived even the winter season has been on the rise importantly. This study analyzed the distribution area of evergreen tree using vegetation index based on unmanned aerial vehicle (UAV). Firstly, RGB and NIR+RG camera were loaded in fixed-wing UAV and image mosaic was achieved using GCPs based on Pix4d SW. And normalized differences vegetation index (NDVI) and soil adjusted vegetation index (SAVI) was calculated by band math function from acquired ortho mosaic image. validation points were applied to evaluate accuracy of the distribution of evergreen tree for each range value and analysis showed that kappa coefficient marked the highest as 0.822 and 0.816 respectively in "NDVI > 0.5" and "SAVI > 0.7". The area of evergreen tree in "NDVI > 0.5" and "SAVI > 0.7" was $11,824m^2$ and $15,648m^2$ respectively, that was ratio of 4.8% and 6.3% compared to total area. It was judged that UAV could supply the latest and high resolution information to vegetation works as urban environment, air pollution, climate change, and heat island effect.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1027-1036
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• 2020

In this study, a cloud-based processing method using Agisoft Metashape, a commercial software, and Amazon web service, a cloud computing service, is introduced and evaluated to quickly generate high-precision 3D realistic data from large volume UAV images acquired in disaster sites. Compared with on-premises method using a local computer and cloud services provided by Agisoft and Pix4D, the processes of aerial triangulation, 3D point cloud and DSM generation, mesh and texture generation, ortho-mosaic image production recorded similar time duration. The cloud method required uploading and downloading time for large volume data, but it showed a clear advantage that in situ processing was practically possible. In both the on-premises and cloud methods, there is a difference in processing time depending on the performance of the CPU and GPU, but notso much asin a performance benchmark. However, it wasfound that a laptop computer equipped with a low-performance GPU takes too much time to apply to in situ processing.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.68-80
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• 2015

To increase the utilization of the KOrea Multi-Purpose SATellite(KOMPSAT) series imagery being developed pursuant to the national space development program, high quality images with enhanced locational accuracy should be created through standardized post-processing processes. In the present study, using the Value-Added Processing System(VAPS) constructed for the post-processing of KOMPSAT imagery, location correction experiments were conducted using KOMPSAT-2 and -3 imagery from domestic and overseas regions. First, 50 pieces from each of KOMPSAT-2 imagery were selected from South Korean and North Korean regions, and modeling was conducted using GCP Chips. According to the results, the Root Mean Square Errors(RMSE) for South Korea and North Korea were 1.59 pixels and 2.04 pixels, respectively, and the locational accuracy of ortho mosaic imagery using check points were 1.33m(RMSE) and 1.90m(RMSE), respectively. Meanwhile, in the case of overseas regions for which GCP could not be easily obtained, the improvement of locational accuracy could be identified through image corrections using Open Street Map(OSM). The VAPS and reference materials used in the present study are expected to be very useful in constructing a precise image DB for entire global regions.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.705-714
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• 2019

Precision positioning is necessary for various use of high-resolution UAV images. Basically, GCP is used for this purpose, but in case of emergency situations or difficulty in selecting GCPs, the data shall be obtained without GCPs. This study proposed a method of improving positional accuracy for x, y coordinate of UAV based 3 dimensional point cloud data generated without GCPs. Road vector file by the public data (Open Data Portal) was used as reference data for improving location accuracy. The geometric correction of the 2 dimensional ortho-mosaic image was first performed and the transform matrix produced in this process was adopted to apply to the 3 dimensional point cloud data. The straight distance difference of 34.54 m before the correction was reduced to 1.21 m after the correction. By confirming that it is possible to improve the location accuracy of UAV images acquired without GCPs, it is expected to expand the scope of use of 3 dimensional spatial objects generated from point cloud by enabling connection and compatibility with other spatial information data.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.