• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.223-235
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• 2020

In this study, we propose an approach for calibrating the elevation of a DEM (Digital Elevation Model), one of the key data in realizing unmanned aerial vehicle image-based precision agriculture. First of all, radiometric correction is performed on the orthophoto, and then ExG (Excess Green) is generated. The non-vegetation area is extracted based on the threshold value estimated by applying the Otsu method to ExG. Subsequently, the elevation of the DEM corresponding to the location of the non-vegetation area is extracted as EIFs (Elevation Invariant Features), which is data for elevation correction. The normalized Z-score is estimated based on the difference between the extracted EIFs to eliminate the outliers. Then, by constructing a linear regression model and correcting the elevation of the DEM, high-quality DEM is produced without GCPs (Ground Control Points). To verify the proposed method using a total of 10 DEMs, the maximum/minimum value, average/standard deviation before and after elevation correction were compared and analyzed. In addition, as a result of estimating the RMSE (Root Mean Square Error) by selecting the checkpoints, an average RMSE was derivsed as 0.35m. Comprehensively, it was confirmed that a high-quality DEM could be produced without GCPs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.671-679
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• 2020

In order to increase the food self-sufficiency rate, monitoring and analysis of crop conditions in the cultivated area is important, and the existing measurement methods in which agricultural personnel perform measurement and sampling analysis in the field are time-consuming and labor-intensive for this reason inefficient. In order to overcome this limitation, it is necessary to develop an efficient method for monitoring crop information in a small area where many exist. In this study, RGB images acquired from unmanned aerial vehicles and vegetation index calculated using RGB image were applied as deep learning input data to classify complex upland crops in small farmland. As a result of each input data classification, the classification using RGB images showed an overall accuracy of 80.23% and a Kappa coefficient of 0.65, In the case of using the RGB image and vegetation index, the additional data of 3 vegetation indices (ExG, ExR, VDVI) were total accuracy 89.51%, Kappa coefficient was 0.80, and 6 vegetation indices (ExG, ExR, VDVI, RGRI, NRGDI, ExGR) showed 90.35% and Kappa coefficient of 0.82. As a result, the accuracy of the data to which the vegetation index was added was relatively high compared to the method using only RGB images, and the data to which the vegetation index was added showed a significant improvement in accuracy in classifying complex crops.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.127-134
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• 2018

Electric transmission towers are facilities to transport electrical power from a plant to an electrical substation. The towers are connected using power lines that are installed with a proper sag by loosening the cable to lower the tension and to secure the sufficient clearance from the ground or nearby objects. The power line sag may extend over the tolerance due to the weather such as strong winds, temperature changes, and a heavy snowfall. Therefore the periodical mapping of the power lines is required but the poor accessibility to the power lines limit the work because most power lines are placed at the mountain area. In addition, the manual mapping of the power lines is also time-consuming either using the terrestrial surveying or the aerial surveying. Therefore we utilized multiple overlapping images acquired from a low-cost drone to automatically reconstruct the power lines in the object space. Two overlapping images are selected for epipolar image resampling, followed by the line extraction for the resampled images and the redundant images. The extracted lines from the epipolar images are matched together and reconstructed for the power lines primitive that are noisy because of the multiple line matches. They are filtered using the extracted line information from the redundant images for final power lines points. The experiment result showed that the proposed method successfully generated parabolic curves of power lines by interpolating the power lines points though the line extraction and reconstruction were not complete in some part due to the lack of the image contrast.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.46-52
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• 2018

This paper is to study the development of three dimensional Digital Surface Model (DSM) using photogrammetry technique based on self-developed Drone (Unmanned Aerial Vehicle (UAV)). To develop DSM, we selected a study area in Jeju island and took 24 pictures from the drone. The three dimensional coordinates of the photos were made by Differential Global Positioning System (DGPS) surveying with 10 ground control points (GCP). From the calculated three dimensional coordinates, we produced orthographic image and DSM. The accuracy of DSM was calculated using three GCPs. The average accuracy of X and Y was from 8.8 to 14.7 cm, and the accuracy of Z was 0.8 to 12.4 cm. The accuracy was less than the reference accuracy of 1/1,000 digital map provided by National Geographic Information Institute (NGII). From the results, we found that the self-developed drone and the photogrammetry technique are a useful tool to make DSM and digital map of Jeju.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.537-546
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• 2008

The digital map has been updated in every five years in the past. However, it has been changed to make corrections and updated in every two years for metropolitan region and every four years for other regions since year 2008. Although, the correctness and reliability were decreased and updating work is being delayed due to the updating work in a lump. The period update spends a lot of money because this method uses aerial photogrammetry, and the digital map has the time gap between periods. Therefore, this study provides information necessary for digital map produced by the government and develops digital map production system based on objects which can be updated frequently in order to save state and local government budgets that double investment are generated to update digital map. In order to analyze usefulness of the developed system, subject area was selected and errors of updated data were analyzed. As the result of analysis, checked 66 errors were corrected and saved in the database.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.153-158
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• 2006

A new High Resolution Geometry or HRG imaging instrument is developed by CNES to be carried on-board SPOT 5. The HRG instrument offers a higher ground resolution than that of the HRV/HRVIR on SPOT 1 - 4 satellites. The field width of HRG is 60 km, same as SPOT constellation. With two HRG instruments, a maximum swath of 120 km at 5 m resolution can be achieved. The generation of Digital Elevation Models (DEMs) from satellite stereo images scores over conventional methods of DEM generation using topographic maps and aerial photographs. This global availability of satellite images allows for quicker data processing for an equivalent area. In this study, a HRG stereo images of SPOT 5 over JECHEON has been used with Leica Photogrammetry Suite OrthoBASE Pro tool for the creation of a digital elevation model (DEM). The extracted DEM was compared to the reference DEM obtained from the contours of digital topographic map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.195-202
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• 2017

Ortho images created by aerial photogrammetry have been used in large areas but they are uneconomical for small areas and continuous change observation. The drones have been developed for military purposes, and recently they are being used crop management and analysis, broadcast relay, meteorological observation and disaster investigation and so on. Also there were a lot of studies of expensive commercial drone. In this paper, lower price self-assembly drone usable for in small areas, Obtained images and produced Orthomosaic and DSM using mission planner which is a normal digital camera and open source program, and postprocessing was used Pix4d software. GCP errors are X-coordinate 3.4cm, Y-coordinate 2.4cm, Z-coordinate 4.2cm. It seems like the self-assembly drone can be used for various fields.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.22-30
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• 2007

It is difficult to generate DTM using aerial photographs because trees usually cover disaster occurred areas. So, this study proposed how to filter by moving window using digital aerial photographs and generate accurate DTM. The results were compared with those of adaptive filtering by commercial digital photogrammetry software (Socet set) to find out the effect of tree removal by window size in forest soil sediment disaster. And then they were compared with DTM generated from LiDAR data. As a result, it was showed that the accuracy of moving filtering DTM was lower than that of LiDAR DTM while it was higher by 6m than that of Adaptive filtering.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.25-31
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• 2004

To obtain the 3-D coordinates of the urban roads from aerial images, the accurate matching technique in road areas is required. In this paper, we suggest the relational matching method that is performed by comparison of relationships of road pavement markings after they are extracted from aerial images using geometric properties and spatial relationships of the pavement markings. Relational matching requires not only high level description of features but also the solution for inexact matching problems. In addition, it needs a lot of tests for the reliable final result. In this research, we described features as calculating geometric properties of the pavement markings, suggested the solution for inextact matching problems, and performed tests to decide whether the result is acceptable or not, which use the property that road areas are flat. In order to evaluate the accuracy of matching, we made a visual evaluation and compared the result of this technique with those measured by analytical photogrammetry.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.73-80
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• 1994

Most terrain information have been generally acquired by map. Because the map presents the real terrain, not by real figure but by contours, geometric figures, symbols, texts, and colors, it is not easy to interpret the real terrain by map. For this reason, aerial photos or terrestrial photos also have been used sometimes in the terrain analysis. But photos have geometrical displacement caused by the position of camera at the exposition time and the relief of the object. So, for accurate posional analysis, orthophoto maps produced by optical rectifier have been used. But, it is hard to produce orthophoto map by optical rectifier and the process is so slow. This study aims to present an accurate and rapid method to produce orthophoto map by generating digital elevation model from stereo aerial photos on common computer using the digital photogrammetric technique and producing orthophoto map digitally using the digital elevation model.