드론을 이용한 지적측량 방식 효과 측정 및 개선방안에 관한 연구 = A study on the improvement schemes and measuruing the effectiveness of cadastral surveying methods using drones

다국어 초록 (Multilingual Abstract)

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 effective due to the regional characteristics of agricultural areas compared to urban areas.
The qualitative effect makes it easy to establish a survey plan at the data survey stage, makes it easy to make objective and accurate performance decisions in built-up areas, increases understanding when explaining survey results to civil complainants, and minimizes direct surveys in dangerous areas, making it easier to make objective and accurate performance decisions in built-up areas. Safety is improved and in-house work time is reduced with the help of accurate reference point and on-site understanding. It is utilized as basis for performance associations held when measurement performance decisions are difficult, helps in accurate business communication with team members, and provides a wide range of It was found that it was helpful in understanding the local scene.
Based on this study, first, more specific and differentiated evidence is required to promote the use of drone cadastral surveying. In the Cadastral Survey Enforcement Rules, drone surveying methods were added, and in Article 24 of the Cadastral Service Regulations, surveying geometry was added. Revision of regulations was proposed for related matters.
Second, even if related regulations are enacted, the necessary to produce a “drone cadastral survey detailed operation manual” that surveyors can immediately use in practice was judged; 1. Drone video shooting standards and manual, 2. Drone image quality verification Standards and Manual, 3. Drone image parallel processing system manual, 4. Drone image phenomenon extraction standards and manual production plan were presented.
Third, in order to expand and revitalize drone cadastral surveying, it was anticipated that it would be necessary to build a comprehensive system to systematically and increase the usability of original photos taken by drones and orthophotos produced through a parallel processing system, so a conceptual diagram of the target system was presented.
Finally, as a result of checking the subjects of several domestic universities with cadastral departments, it was revealed that only one school was running a “drone theory and practice” course. Therefore based on this study, it is necessary to institute a new drone cadastral surveying course in each cadastral and spatial information department in the near future to revitalize human resources training in the drone cadastral surveying sector.

목차 (Table of Contents)

• 제 1 장 서 론 1
• 제 1 절 연구의 배경 및 목적 1
• 1. 연구의 배경 1
• 2. 연구의 목적 2
• 제 2 절 연구의 범위 및 방법 3
• 1. 연구의 범위 3
• 2. 연구의 방법 4
• 제 2 장 이론적 고찰 6
• 제 1 절 지적측량 6
• 1. 지적측량 6
• 2. 지적측량의 종류 10
• 3. 지적측량의 방법과 한계 12
• 제 2 절 드론 사진측량의 정의 및 특징 16
• 1. 드론 사진측량의 정의와 기본원리 16
• 2. 드론 사진측량의 특징 20
• 제 3 절 드론 활용 선행연구 고찰 22
• 1. 공간정보 분야 선행연구 22
• 2. 지적측량 분야 선행연구 26
• 3. 선행연구와 차별성 32
• 제 3 장 연구설계 33
• 제 1 절 연구지역 선정 및 연구장비 33
• 1. 연구지역 선정 33
• 2. 연구장비 34
• 제 2 절 드론촬영 및 정사영상 제작 35
• 1. 드론촬영 35
• 2. 지상기준점측량 37
• 3. 정사 및 입체영상 제작 38
• 제 4 장 드론 지적측량 사례분석 및 개선방안 43
• 제 1 절 지적측량 절차 43
• 1. 현행 지적측량 절차 43
• 2. 드론 지적측량 절차 44
• 제 2 절 드론 지적측량 적용 방법 46
• 1. 기초자료 준비 46
• 2. 자료조사 단계 46
• 3. 현장 측량 단계 47
• 4. 성과 작성 단계 49
• 제 3 절 드론 지적측량 사례분석 51
• 1. 도심지 드론 지적측량 51
• 2. 농경지 드론 지적측량 54
• 3. 드론 지적측량 효과 요약 58
• 제 4 절 드론 지적측량 활성화를 위한 개선방안 61
• 1. 드론 지적측량 관련 법·제도 개선 61
• 2. 드론 지적측량 세부 운영 매뉴얼 제작 64
• 3. 드론 영상 관리·활용 시스템 구축 69
• 4. 드론 지적측량 전문인력 양성 70
• 제 5 장 결 론 71
• 제 1 절 연구의 요약 및 시사점 71
• 제 2 절 연구의 한계 및 향후 과제 74