scholarly journals Digital Elevation Model Production Using Point Cloud Acquired by Unmanned Aerial Vehicles

2020 ◽  
Vol 32 (12) ◽  
pp. 4347
Author(s):  
Suk Bae Lee ◽  
Jae Ho Won ◽  
Kap Yong Jung ◽  
Mihwa Song ◽  
Young Joon Ahn
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Digital Elevation Model ◽  
Point Cloud ◽  
Aerial Vehicles ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals Redes sociais e bibliometria sobre a utilização de VANTs no mapeamento do risco hidrológico em áreas urbanas

2021 ◽  
Vol 10 (14) ◽  
pp. e319101422078
Author(s):  
Andrey Gaspar Sorrilha Rodrigues ◽  
Alesson Pires Maciel Guirra ◽  
Daniella Nunes Silveira ◽  
Amanda Letícia Abegg da Silveira ◽  
Jéssica Rabito Chaves ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Digital Elevation Model ◽  
Web Of Science ◽  
Aerial Vehicles ◽  
Digital Elevation ◽  
Elevation Model

Este estudo visa realizar pesquisas na base de dados Scopus e Web of Science sob o intuito de procurar trabalhos relativos ao mapeamento hídrico com o enfoque em áreas de risco utilizando VANTs. O software VOSViewer, gera infográficos fundamentados no sistema de nós exibindo os principais termos da pesquisa, autores, elementos recorrentes e palavras-chave. Categorizando os trabalhos, de forma quantitativa, em autores colaboradores, abordagem referente ao tema, tipos de publicações, principais revistas, índices, principais países, redes de colaboração e palavras-chaves, indicou os principais trabalhos pertinentes ao tema, em que, esses foram discutidos para a verificação de como o tema é abordado. 91,15% dos trabalhos estão escritos em inglês, sendo os EUA o segundo país que mais publica sobre, na retaguarda da China. Os principais termos concatenados a pesquisa são UAV – Unmanned Aerial Vehicles, Photogrammetry e DEM - Digital elevation Model, que fazem alusão ao uso de VANTs para obtenção do MDE e MDS pelo método fotogramétrico. Dentre os trabalhos, 10 apresentaram material metodológico e resultados promissores na utilização de VANT ́para mapeamento de risco hidrológico, com destaque aos trabalhos de Mazzoleni, Muthusamy Annis, Luppichini, que apresentam softwares de processamento de imagem (Agisoft PhotoScan) e de simulações hidrodinâmicas de águas pluviais e fluviais (FLO-2D e HEC-RAS). Logo, esse estudo viabilizou reconhecer condutas metodológicas, tendências, dificuldades e as vantagens da ferramenta VANT, na aplicação técnica, como alta precisão, custo relativamente baixo e alcance em áreas de difícil acesso.

PENENTUAN GARIS PANTAI MENGGUNAKAN FOTO UDARA DARI WAHANA TANPA AWAK (Studi Kasus Pantai Ujong Batee Aceh)

2021 ◽  
pp. 707
Author(s):  
Herjuno Gularso ◽  
Andri Daniel Parapat ◽  
Teguh Sulistian ◽  
Alfian Adi Atmaja
Keyword(s):  
Digital Elevation Model ◽  
Point Cloud ◽  
Control Point ◽  
Ground Control ◽  
Check Point ◽  
Ground Sample ◽  
Ground Control Point ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sample Distance

Garis pantai merujuk Undang-undang No 4 tahun 2011 pasal 13 merupakan garis pertemuan antara daratan dengan lautan yang dipengaruhi oleh pasang surut air laut. Pembentukan garis pantai membutuhkan data Digital Elevation Model (DEM) diwilayah pesisir dengan resolusi dan ketelitian tinggi, sementara teknologi foto udara memiliki kemampuan dalam hal ekstraksi point ketinggian (point cloud) dari titik sekutu antar foto udara yang bertampalan dan juga memiliki kelebihan menghemat waktu pekerjaan dan biaya jika dibandingkan dengan pengukuran terestris. Penelitian ini bertujuan untuk menguji hasil pembentukan DEM dari data foto udara yang selanjutnya digunakan untuk pembentukan garis pantai di pantai Ujong Batee Aceh. Proses pengumpulan data menggunaan wahana Multi rotor DJI Mavic Pro. Jumlah titik Ground Control Point (GCP) adalah 10 titik yang tersebar secara merata untuk seluruh area yang dipetakan. Hasil Ground Sample Distance adalah 1,97 cm/pixel dengan cakupan area yaitu 16,8 hektar. Hasil uji akurasi vertikal DEM menggunakan 167 Independent Check Point (ICP) adalah sebesar 0,863 m, dapat disimpulkan bahwa data foto udara kamera non-metrik dalam penelitian ini memenuhi ketelitian vertikal peta RBI pada skala 1:5.000 kelas I (SNI Ketelitian peta dasar 8202:2019). Pembentukan garis pantai menggunakan DEM dari foto udara yang sudah dikoreksi menggunakan model pasut BIG sehingga datum vertikal dari DEM adalah muka air rata- rata. Garis pantai yang terbentuk pada lokasi penelitian hanya garis pantai pasang tertinggi dan muka air laut rata-rata. Pemotretan udara untuk mendapatkan DEM diwilayah pesisir sebaiknya dilakukan pada saat air surut untuk memperoleh garis pantai air muka laut rata-rata dan pasang tertinggi.

scholarly journals DESIGN A FILTER TO DETECT AND REMOVE VEGETATION FROM ULTRA-CAM-X AERIAL IMAGES’ POINT CLOUD TO PRODUCE AUTOMATICALLY DIGITAL ELEVATION MODEL

2015 ◽  
Vol XL-1-W5 ◽  
pp. 159-162
Author(s):  
H. Enayati ◽  
M. Veissy ◽  
F. Rahimpour
Keyword(s):  
Digital Elevation Model ◽  
Point Cloud ◽  
Spatial Information ◽  
Point Clouds ◽  
Aerial Images ◽  
Segmented Image ◽  
Digital Elevation ◽  
Otsu Method ◽  
Elevation Model ◽  
Is Design

Digital elevation model is one of the most important spatial information for displaying bare earth. Because of existing objects on the ground, manual editing is unavoidable. Aerial images’ point clouds produced by advanced matching methods are good resources for generating DEM. In this paper, the purpose is design a filter for detect and eliminate vegetation from point clouds. For this purpose, point clouds’ texture is used for finding vegetation. Texture of point clouds is segmented by Otsu method. In the next step, segmented image is added to raster of elevation and vegetation elevation is detected. Results is showing that point clouds’ texture is a good data for filtering vegetation and generating DEM automatically.

scholarly journals Creating a digital relief model by aerial photography materials in Civil 3D software

2020 ◽  
Author(s):  
E. Butenko ◽  
◽  
K. Borovyk ◽  
A. Gerin ◽  
B. Gubkin ◽  
...  
Keyword(s):  
Initial Data ◽  
Digital Elevation Model ◽  
Aerial Photography ◽  
Point Cloud ◽  
Point Clouds ◽  
Advantages And Disadvantages ◽  
Digital Elevation ◽  
Elevation Model ◽  
3D Software ◽  
Cloud Of Points

Research of certain aspects of using a digital elevation model (DEM), their classification and methods of obtaining in the Civil 3D software is presented in this article. A land plot with vegetation and the building of the educational building of the NULES of Ukraine was used as an object for the study. The analysis of aerial photography materials of the territory of the research object is carried out. A digital point cloud was created, which was taken as a basis for the further construction of digital elevation models. Сlassification of surfaces in the Civil 3D software is offered in article. An algorithm for the formation of plane components and data filling is considered. Highlighted the problems that arise in a robot with a cloud of points and surface formation using Autodesk ReCap and Civil 3D. The main advantages and disadvantages of building a relief on the basis of point clouds formed on the basis of aerial photography of the terrain are shown. Attention is focused on the main ways to reduce the identified shortcomings. The functionality and capabilities of Civil 3D and Autodesk ReCap software, as well as the features of constructing surfaces based on different initial data, are considered. The comparison of the DEM (generated using the Autodesk Civil 3D software) and the topographic plan (generated as a result of tacheometric survey) is given.

Image Processing and Localization for Detecting and Tracking Wildland Fires

2015 ◽  
Author(s):  
Anoop Sathyan ◽  
Manish Kumar ◽  
Kelly Cohen
Keyword(s):  
Image Processing ◽  
Unmanned Aerial Vehicles ◽  
Wildland Fire ◽  
Wildland Fires ◽  
Geological Data ◽  
Human Presence ◽  
Aerial Vehicles ◽  
Digital Elevation ◽  
Video Feed ◽  
Elevation Model

Unmanned Aerial Vehicles (UAVs) are being used for a wide variety of applications including detecting and tracking wildland fires. Using UAVs for fire-fighting purposes reduces the human involvement for this high risk job. Such a mission involves locating the wildland fire, tracking the direction of spread of the fire and searching for human presence in the region. This paper investigates the algorithmic development for the use of UAVs to detect and track wildland fires. This would involve using the fuzzy toolbox in MATLAB along with MICRODEM, a software which provides the Digital Elevation Model (DEM) for the region. The objective of this research is to accomplish the following: 1) use genetic fuzzy based image processing tools to identify fire from the video feed obtained from the camera attached to the UAV in real time 2) look for human presence in the region and 3) estimate the location of the fire based on the geological data available for the region.

scholarly journals Using Photogrammetric UAV Measurements as Support for Classical Topographical Measurements in Order to Obtain the Topographic Plan for Urban Areas

2017 ◽  
Vol 74 (2) ◽  
pp. 197
Author(s):  
Elemer Emanuel SUBA ◽  
Tudor SĂLĂGEAN ◽  
Ioana POP ◽  
Florica MATEI ◽  
Jutka DEAK ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Urban Areas ◽  
Point Cloud ◽  
Ground Control ◽  
Control Points ◽  
Ground Control Points ◽  
Triangulation Network ◽  
Digital Elevation ◽  
Photogrammetric Method ◽  
Elevation Model

This article aims to highlight the benefits of UAV photogrammetric measurements in addition to classical ones. It will also deal with the processing and integration of the point cloud, respectively the digital elevation model in topo-cadastral works. The main purpose of this paper is to compare the results obtained using the UAV photogrammetric measurements with the results obtained by classical methods. It will briefly present the classical measurements made with the total station. In the present project, the closed-circuit traverse and the supported on the endings traverse were made using known coordinate points. Determining the coordinates of the points used for the traverses was done by GNSS methods. The area on which the measurements were made is 67942m2 and is covered by 31 determined station points. From these points, 13 were used as ground control points, respectively components of the aero-triangulation network and 17 points were used to control the obtained results by comparing their coordinates obtained by classical methods with those obtained by the UAV photogrammetric method. It was intended that the constraint points of the aero triangulation to be uniformly distributed on the studied surface.

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