드론을 이용한 지적측량 방식 효과 측정 및 개선방안에 관한 연구

드론을 활용한 지적측량의 효과를 측정하고 개선방안을 연구했다.

A drone, a complex of cutting-edge technologies such as aviation, electronic sensors, software and ICT, is steadily expanding its usefulness not only in education and research, industry, military, and agriculture but also in private areas such as personal hobbies or leisure activities and sports. Currently, the digital platform government is also promoting the development of the drone industry at the national level through the New Growth 4.0 promotion strategy and is actively encouraging the use of drones by the government and public institutions.

This study demonstrates drone cadastral surveying, which is in the early stages of implementation, to actual cadastral surveying work to quantitatively and qualitatively confirm the effectiveness of drone cadastral surveying compared to existing cadastral surveying. The purpose of this study is to suggest the need for widespread use of drone cadastral surveying in the future by suggesting operational improvements required when applying drone cadastral surveying to actual work and ways to improve related systems.

For this purpose, an urban area (Singil-dong, Yeongdeungpo-gu, Seoul, approximately 3.6㎢) and agricultural land (Nowon-ri, Iwol-myeon, Jincheon-gun, approximately 4.6㎢) were selected as research areas, and this study was conducted at an altitude of 120M using the Matrice300 RTK model manufactured by DJI for 4 days and 3 days, respectively. Drone images with 80% longitudinal overlap, 70% lateral overlap, and 1.5 cm spatial resolution were acquired. In order to improve the quality of 3D images in densely populated areas, the gimbal angle was set to 30° and multi-directional oblique photos were taken using the Smart Oblique function.

A total of 33,435 drone images (499 GB) for urban areas and a total of 28,448 drone images (479 GB) for agricultural areas were acquired by using a parallel processing system for 2 days, 5 hours and 2 minutes. After 15 hours and 48minutes of data processing each day, one drone orthophoto was produced. To analyze the accuracy of the processed data, the data processing result report generated after data processing in the data processing software (Skyline's Photomesh 8.3) was cited. The maximum error among the horizontal (X, Y) errors with respect to the ground reference point in the urban area was 0.03m, the standard deviation was 0.013m, and the average error was 0.018m.

The maximum error among the horizontal (X, Y) errors of the inspection point was 0.05m, the standard deviation was 0.017m, and the average error was 0.041m, and the maximum error among the horizontal (X, Y) errors with respect to the ground reference point for agricultural land was 0.023m. , the standard deviation was 0.008m and the average error was 0.012m. Among the horizontal errors (X, Y) of the inspection point, the maximum error was 0.047m, the standard deviation was 0.014m, and the average error was 0.030m.

The result of this study satisfies the provisions of Article 12, Paragraph 4 of the Drone Cadastral Survey Regulations: The difference in the position between the orthophoto reference point and the ground reference point must be within ±0.05 meters in the plane and can be confirmed in the orthophoto production program result report. Consequently, it was determined that it was data that could be used for cadastral surveying.

In order to use the drone orthophotos and stereoscopic images of urban areas and agricultural fields constructed in this study for cadastral surveying, the study was conducted in compliance with the “Drone Cadastral Survey Regulations” through the following procedures: data investigation → field survey → result writing. The reason for excluding drone filming and data post-processing is to compare the time and efficiency of common work processes in current cadastral surveying and drone cadastral surveying. In the case of urban areas, drone cadastral surveying was applied to 5 survey cases received in the area in November after establishing data for the study area.

In the case of urban areas, due to their characteristic buildings and various facilities are densely packed, and it is difficult to check cadastral boundaries and reference points such as actual roads, fences, and structures due to vehicles parked along roadsides and street trees using drone orthophotos taken from the air. In many cases, it is not possible or impossible. In addition, a large number of lots are included in a small area, it is not easy to observe the boundaries inside the building. It was confirmed that the quantitative effect of the drone cadastral survey method was to reduce work time by 88.8% to 93.1% compared to the existing method.

In the case of agricultural land, drone cadastral surveying was applied to 5 survey cases received in the area for about a month after establishing the research area data. In the case of agricultural land, the efficiency of drone cadastral surveying was expected to be higher than that of existing methods. Owing to the characteristic of agricultural land, the area of the fields and hillsides is large, so it takes a relatively long time for the surveyor to move to observe the current shape of the lot boundary and the fields. Fields are more accurate than the exact location of the cadastral boundary points of clear fixtures such as road boundary stones, fences, and fences.

The reason is that the location of relatively low-accuracy cadastral boundary points, such as the bottom and top of land are distributed in large numbers, so it can be estimated that the field observation time can be significantly reduced if replaced with a drone chord line. It was confirmed that the quantitative effect of the drone cadastral survey method was that work hours were reduced by 60.6% to 70.5% compared to the existing method. Compared to the downtown area, there was a 28.2% difference in the maximum shortening ratio and a 22.6% difference in the minimum shortening ratio. This result indicates that drone cadastral surveying is more