Research on the Processing Technology of Low-altitude Unmanned Aerial Vehicle Images

被引：0

作者：

Tang Shihua ^{[1
,2
]}

Liu Yintao ^{[1
,2
]}

Li Feida ^{[1
,2
]}

Zhou Conglin ^{[1
,2
]}

Huang Qing ^{[1
,2
]}

Xu Hongwei ^{[1
,2
]}

机构：

[1] Guilin Univ Technol, Coll Geomat Engn & Geoinformat, Guilin 541004, Guangxi, Peoples R China

[2] Guangxi Key Lab Spatial Informat & Geomat, Guilin 541004, Guangxi, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON INTELLIGENT EARTH OBSERVING AND APPLICATIONS 2015 | 2015年 / 9808卷

关键词：

Unmanned Aerial Vehicle; UASMaster; digital orthophoto map; precision analysis;

D O I：

10.1117/12.2207583

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

The UAV system acts as one of the infrastructure of earth observation, with its mobility, high speed, flexibility, economy and other remarkable technical advantages, has been widely used in various fields of the national economic construction, such as agricultural monitoring, resource development, disaster emergency treatment. Taking an actual engineering as a case study in this paper, the method and the skill of making digital orthophoto map was stated by using the UASMaster, the professional UAV data processing software, based on the eBee unmanned aerial vehicle. Finally, the precision of the DOM was analyzed in detail through two methods, overlapping the DOM with the existing DLG of the region and contrasting the points of the existing DLG of 1: 1000 scale with the corresponding checkpoints of the stereomodel.

引用

页数：7

共 50 条

[31] Unmanned aerial vehicles for plant protection and precision agriculture: a study on low-altitude route planning method of unmanned aerial vehicles
Hu, Weijun
Quan, Jiale
Ma, Xianlong
[J]. PAKISTAN JOURNAL OF AGRICULTURAL SCIENCES, 2023, 60 (02): : 435 - 445
[32] Extraction of soybean planting area based on feature fusion technology of multi-source low altitude unmanned aerial vehicle images
Yang, Qi
She, Bao
Huang, Linsheng
Yang, Yuying
Zhang, Gan
Zhang, Mai
Hong, Qi
Zhang, Dongyan
[J]. ECOLOGICAL INFORMATICS, 2022, 70
[33] Autonomous, Onboard Vision-Based Trash and Litter Detection in Low Altitude Aerial Images Collected by an Unmanned Aerial Vehicle
Kraft, Marek
Piechocki, Mateusz
Ptak, Bartosz
Walas, Krzysztof
[J]. REMOTE SENSING, 2021, 13 (05) : 1 - 17
[34] AIOD-YOLO: an algorithm for object detection in low-altitude aerial images
Yan, Peng
Liu, Yong
Lyu, Lu
Xu, Xianchong
Song, Bo
Wang, Fuqiang
[J]. JOURNAL OF ELECTRONIC IMAGING, 2024, 33 (01)
[35] Research on Visual Navigation Technology of Unmanned Aerial Vehicle Landing
Yang Songpu
Wang Yangzhu
[J]. 2013 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA), 2013, : 463 - 467
[36] Low-Altitude Aerial Methane Concentration Mapping
Emran, Bara J.
Tannant, Dwayne D.
Najjaran, Homayoun
[J]. REMOTE SENSING, 2017, 9 (08)
[37] Virtual Image Generation from Low Altitude Unmanned Aerial Vehicle Digital Aerial camera
Cui Hongxia
Lin Zongjian
Meng Wenli
[J]. PROCEEDINGS OF THE FIRST INTERNATIONAL WORKSHOP ON EDUCATION TECHNOLOGY AND COMPUTER SCIENCE, VOL II, 2009, : 697 - 699
[38] Energy System Optimization and Simulation for Low-Altitude Solar-Powered Unmanned Aerial Vehicles
Li, Ke
Wu, Yansen
Bakar, Abu
Wang, Shaofan
Li, Yuangan
Wen, Dongsheng
[J]. AEROSPACE, 2022, 9 (06)
[39] PRESERVING AND DISSEMINATING LOW-ALTITUDE AERIAL PHOTOGRAPHS
MYERS, JW
[J]. AMERICAN JOURNAL OF ARCHAEOLOGY, 1988, 92 (02) : 250 - 250
[40] Influence of flight altitude and control points in the georeferencing of images obtained by unmanned aerial vehicle
Santos Santana, Lucas
Araujo E Silva Ferraz, Gabriel
Bedin Marin, Diego
Dienevam Souza Barbosa, Brenon
Mendes Dos Santos, Luana
Ferreira Ponciano Ferraz, Patricia
Conti, Leonardo
Camiciottoli, Stefano
Rossi, Giuseppe
[J]. EUROPEAN JOURNAL OF REMOTE SENSING, 2021, 54 (01) : 59 - 71

← 1 2 3 4 5 →