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.

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 Compartimentação dos elementos do relevo da bacia hidrográfica do arroio Pantanoso – Canguçu/RS, através da proposta dos geomorphons

2020 ◽  
Vol 13 (2) ◽  
pp. 713
Author(s):  
Danilo Da Silva Dutra ◽  
André Ricardo Furlan ◽  
Luís Eduardo De Souza Robaina
Keyword(s):  
Digital Elevation Model ◽  
River Basin ◽  
Spatial Resolution ◽  
Advantages And Disadvantages ◽  
Digital Elevation ◽  
Relief Elements ◽  
Gis Environment ◽  
Elevation Model

O relevo é a base onde todas as populações vivem e desenvolvem suas atividades, derivando dessa relação vantagens e desvantagens, daí a importância de conhecê-lo através do estudo de suas diferentes formas e elementos. Nesse contexto insere-se a importância de metodologias para o seu estudo, sendo que atualmente vivencia-se a expressividade de dados disponíveis para aplicação de geoprocessamento. A partir das geotecnologias pode-se empreender diversas análises sobre o relevo, destacando-se nesse contexto, a proposta dos geomorphons a qual foi aplicada na bacia hidrográfica do arroio Pantanoso. O objetivo da pesquisa é a identificação e análise dos elementos do relevo definido por geomorphons, quais sejam: 1) Planos, 2) Picos, 3) Cristas, 4) Ressaltos, 5) Crista secundária, 6) Encostas, 7) Escavado, 8) Base de encosta, 9) Vales e 10) Fosso. A determinação dos geomorphons foi a partir do processamento em ambiente SIG do Modelo Digital de Elevação (MDE) do Shuttle Radar Topograph Mission (SRTM) com resolução espacial 3 arcsec (90 metros), “L” Lookup (distância em metros) definiu-se como de 20 pixels (1800 metros) e o “T” Theresholdt (nivelamento em graus) definiu-se em 2º. Para visualização do comportamento dos elementos do relevo na área de estudo realizaram-se trabalhos de campo, o que contribuiu para evidenciar a padronização desses elementos. Os quatro elementos geomorphons mais representativos são encostas, vales, cristas e planos. Subdivision of relief elements through the proposal of geomorphons: river basin of arroio Pantanoso - Canguçu/RS A B S T R A C TRelief is the basis where all populations live and develop their activities, deriving from this relation advantages and disadvantages, hence the importance of knowing it through the study of its different forms and elements. In this context, the importance of methodologies for its study is inserted and geoprocessing application for data available for is currently experienced. From the geotechnologies one can undertake several analyzes on the relief, highlighting in this context, the proposal of the geomorphons which was applied in Pantanoso stream basin. The objective of the research is to identify and analyze the elements of the relief defined by geomorphons, namely: 1) Flats, 2) Peaks, 3) Ridges, 4) Shoulders, 5) Spurs, 6)Slopes, 7) Hollows, 8) Footslope, 9) Valley and 10) Pits. The determination of the geomorphons was based on the GIS environment of the Shuttle Radar Topograph Mission (SRTM) Digital Elevation Model (DEM) with spatial resolution 3 arcsec (90 meters), "L" Lookup (distance in meters) was defined as of 20 pixels (1800 meters) and the "T" Theresholdt (leveling in degrees) was defined in 2º. In order to visualize the behavior of the relief elements in the study area, fieldwork was carried out, which contributed to the standardization of these elements. The four most representative geomorphons, which are: Slopes, Valleys, Ridges and Flat.Keywords: SIG, Geomorphons; Canguçu/RS; relief

scholarly journals CREATING DIGITAL ELEVATION MODEL USING A MOBILE DEVICE

2017 ◽  
Vol IV-4/W4 ◽  
pp. 203-207 ◽  
Author(s):  
A. İ. Durmaz
Keyword(s):  
Mobile Devices ◽  
Digital Elevation Model ◽  
Mobile Device ◽  
Point Clouds ◽  
Lidar Data ◽  
Government Agencies ◽  
Gps Data ◽  
Digital Elevation ◽  
The World ◽  
Elevation Model

DEM (Digital Elevation Models) is the best way to interpret topography on the ground. In recent years, lidar technology allows to create more accurate elevation models. However, the problem is this technology is not common all over the world. Also if Lidar data are not provided by government agencies freely, people have to pay lots of money to reach these point clouds. In this article, we will discuss how we can create digital elevation model from less accurate mobile devices’ GPS data. Moreover, we will evaluate these data on the same mobile device which we collected data to reduce cost of this modeling.

scholarly journals PERFORMANCE EVALUATION OF DIFFERENT GROUND FILTERING ALGORITHMS FOR UAV-BASED POINT CLOUDS

2016 ◽  
Vol XLI-B1 ◽  
pp. 245-251 ◽  
Author(s):  
C. Serifoglu ◽  
O. Gungor ◽  
V. Yilmaz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Good Alternative ◽  
Lidar Data ◽  
Filtering Algorithms ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images

Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.

scholarly journals Creation of the digital elevation model with the use of unmanned aerial vehicle

2019 ◽  
Vol 49 (3) ◽  
pp. 70-78
Author(s):  
A. I. Pavlova ◽  
V. K. Kalichkin ◽  
A. V. Kalichkin
Keyword(s):  
Digital Elevation Model ◽  
Unmanned Aerial Vehicle ◽  
Aerial Photography ◽  
Statistical Processing ◽  
Satellite Measurements ◽  
Support Points ◽  
Novosibirsk Region ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model

The necessary sequence of stages has been developed and the unmanned technology for creating a digital elevation model by the example of the land use of Novosibirsk region has been implemented. The technology consists of a set of stages: reconnaissance of the terrain, fi xing reference signs, satellite measurements, aerial photography fl ights, processing the results of aerial photography and the construction of digital elevation model. The technological process was signifi cantly affected by unfavorable weather conditions - low clouds, gusty wind, high air humidity. Remote sensing study with the use of unmanned aerial vehicle of the Supercam S 250 F type made it possible to create a large-scale orthophotoplan and a digital elevation model on the farm territory (M 1 : 1000). For photogrammetric processing of digital data obtained on the farm, a two-stage method of satellite determination was used. The essence of this method was to obtain a large number of satellite measurements in a static mode and further statistical processing. For statistical processing of satellite measurements, information was used on the coordinate location of two base ground stations of the Novosibirsk Region satellite network - Kochenevo and Novosibirsk. Remoteness of support points from the ground satellite station of Novosibirsk was at a distance of over 90 km. As a result of equalization calculations, the obtained average square displacement errors of the planned and high-altitude position of the support points in various test sites were under 0.02 m in the plan, and under 0.03 m by height. In the process of photogrammetric processing of the results of aerial photography with the use of unmanned aerial vehicle, the tasks of transferring the position of points on a digital image in the pixel coordinate system into the coordinate system of the area, building digital irregular (TIN, Triangulated Irregular Network) and regular (DEM, Digital Elevation Model) surface models, and based on them, textured terrain models (TTM, Textured Terrain Model) and orthophotoplans, were solved.

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 PERFORMANCE EVALUATION OF DIFFERENT GROUND FILTERING ALGORITHMS FOR UAV-BASED POINT CLOUDS

2016 ◽  
Vol XLI-B1 ◽  
pp. 245-251 ◽  
Author(s):  
C. Serifoglu ◽  
O. Gungor ◽  
V. Yilmaz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Good Alternative ◽  
Lidar Data ◽  
Filtering Algorithms ◽  
Aerial Photos ◽  
Digital Elevation ◽  
Aerial Vehicle ◽  
Elevation Model ◽  
Uav Images

Digital Elevation Model (DEM) generation is one of the leading application areas in geomatics. Since a DEM represents the bare earth surface, the very first step of generating a DEM is to separate the ground and non-ground points, which is called ground filtering. Once the point cloud is filtered, the ground points are interpolated to generate the DEM. LiDAR (Light Detection and Ranging) point clouds have been used in many applications thanks to their success in representing the objects they belong to. Hence, in the literature, various ground filtering algorithms have been reported to filter the LiDAR data. Since the LiDAR data acquisition is still a costly process, using point clouds generated from the UAV images to produce DEMs is a reasonable alternative. In this study, point clouds with three different densities were generated from the aerial photos taken from a UAV (Unmanned Aerial Vehicle) to examine the effect of point density on filtering performance. The point clouds were then filtered by means of five different ground filtering algorithms as Progressive Morphological 1D (PM1D), Progressive Morphological 2D (PM2D), Maximum Local Slope (MLS), Elevation Threshold with Expand Window (ETEW) and Adaptive TIN (ATIN). The filtering performance of each algorithm was investigated qualitatively and quantitatively. The results indicated that the ATIN and PM2D algorithms showed the best overall ground filtering performances. The MLS and ETEW algorithms were found as the least successful ones. It was concluded that the point clouds generated from the UAVs can be a good alternative for LiDAR data.

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
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