scholarly journals How to decide which oblique image has the highest mapping potential for monoplotting method: a case studies on river erosion and floods

2014 ◽  
Vol II-5 ◽  
pp. 379-384 ◽  
Author(s):  
M. Triglav-Čekada ◽  
V. Bric ◽  
M. Zorn
Keyword(s):  
Digital Elevation Model ◽  
Laser Scanning ◽  
Incidence Angle ◽  
Aerial Images ◽  
Oblique View ◽  
Common Features ◽  
Digital Elevation ◽  
Elevation Model ◽  
Oblique Images ◽  
Matching Techniques

When studying the development of different geomorphic processes, floods, glaciers or even cultural heritage through time, one cannot rely only on regular photogrammetrical procedures and metrical images. In a majority of cases the only available images are the archive images with unknown parameters of interior orientation showing the object of interest in oblique view. With the help of modern high resolution digital elevation models derived from aerial or terrestrial laser scanning (lidar) or from photogrammetric stereo-images by automatic image-matching techniques even single nonmetric high or low oblique image from the past can be applied in the monoplotting procedure to enable 3D-data extraction of changes through time. The first step of the monoplotting procedure is the orientation of an image in the space by the help of digital elevation model (DEM). When using oblique images tie points between an image and DEM are usually too sparse to enable automatic exterior orientation, still the manual interactive orientation using common features can resolve such shortages. The manual interactive orientation can be very time consuming. Therefore, before the start of the manual interactive orientation one should be certain if one can expect useful results from the chosen image. But how to decide which image has the highest mapping potential before we introduce a certain oblique image in orientation procedure? The test examples presented in this paper enable guidance for the use of monoplotting method for different geoscience applications. The most important factors are the resolution of digital elevation model (the best are the lidar derived ones), the presence of appropriate common features and the incidence angle of the oblique images (low oblique images or almost vertical aerial images are better). First the very oblique example of riverbank erosion on Dragonja river, Slovenija, is presented. Than the test example of September 2010 floods on Ljubljana moor is discussed. Finally, case study from November 2012 floods is presented. During November 2012 floods an initiative was launched to gather as much non-metrical images of floods as possible from casual observers (volunteered image gathering). From all gathered images the guidelines presented before helped to pick out 21% images which were used for monoplotting.

scholarly journals Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

2017 ◽  
Vol 66 (1) ◽  
pp. 137-148 ◽  
Author(s):  
Małgorzata Woroszkiewicz ◽  
Ireneusz Ewiak ◽  
Paulina Lulkowska
Keyword(s):  
Digital Elevation Model ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Shuttle Radar Topography Mission ◽  
Reference Points ◽  
Airborne Lidar ◽  
Surface Model ◽  
Digital Elevation ◽  
Elevation Model ◽  
German Aerospace

Abstract The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.

scholarly journals Research on colorized physical terrain modeling for intelligent vehicle navigation

2018 ◽  
Vol 10 (7) ◽  
pp. 168781401878741
Author(s):  
Jingbin Hao ◽  
Hansong Ji ◽  
Hao Liu ◽  
Zhongkai Li ◽  
Haifeng Yang
Keyword(s):  
Digital Elevation Model ◽  
Land Use Planning ◽  
Three Dimensional ◽  
Aerial Images ◽  
Surface Model ◽  
File Format ◽  
Terrain Model ◽  
Digital Elevation ◽  
Model File ◽  
Elevation Model

Colorized physical terrain models are needed in many applications, such as intelligent navigation, military strategy planning, landscape architecting, and land-use planning. However, current terrain elevation information is stored as digital elevation model file format, and terrain color information is generally stored in aerial images. A method is presented to directly convert the digital elevation model file and aerial images of a given terrain to the colorized virtual three-dimensional terrain model, which can be processed and fabricated by color three-dimensional printers. First, the elevation data and color data were registered and fused. Second, the colorized terrain surface model was created by using the virtual reality makeup language file format. Third, the colorized three-dimensional terrain model was built by adding a base and four walls. Finally, the colorized terrain physical model was fabricated by using a color three-dimensional printer. A terrain sample with typical topographic features was selected for analysis, and the results demonstrated that the colorized virtual three-dimensional terrain model can be constructed efficiently and the colorized physical terrain model can be fabricated precisely, which makes it easier for users to understand and make full use of the given terrain.

scholarly journals Extração de Obstruções Perspectivas de Edifícios ao Longo de Vias Urbanas

2006 ◽  
Vol 33 (2) ◽  
pp. 101
Author(s):  
ANTONIO JULIANO FAZAN ◽  
ALUIR PORFÍRIO DAL POZ ◽  
EDINÉIA APARECIDA DOS SANTOS GALVANIN
Keyword(s):  
High Resolution ◽  
Digital Elevation Model ◽  
Digital Image ◽  
Aerial Images ◽  
Perspective Projection ◽  
Object Space ◽  
Digital Elevation ◽  
Intensity Image ◽  
Elevation Model

This paper presents an approach for extraction of perspective obstructions in high-resolution aerial images caused by the perspective projection of buildings onto adjacent urban ways. The proposed methodology consists in firstly extracting the contours of building roofs and urban ways from an intensity image generated by a conversion of a Digital Elevation Model (DEM). In the following, the polygons representing the roof contours are projected through the perspective bundle onto the respective mean planes of adjacent ways. Intersections between polygons representing roof contours and local segments of adjacent ways allow the extraction of the perspective obstructions in the object-space. The perspective obstruction polygons are finally projected onto the digital image basically using the collinearity equations. The results obtained by methodology allow the verification of its performance and show its potential for extraction of perspective obstructions in high-resolution aerial images.

scholarly journals A Comparative Study of Three Non-Geostatistical Methods for Optimising Digital Elevation Model Interpolation

2018 ◽  
Vol 7 (8) ◽  
pp. 300 ◽  
Author(s):  
Serajis Salekin ◽  
Jack Burgess ◽  
Justin Morgenroth ◽  
Euan Mason ◽  
Dean Meason
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Laser Scanning ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Global Navigation Satellite Systems ◽  
Digital Elevation ◽  
Dem Accuracy ◽  
Elevation Model ◽  
Gnss Data

It is common to generate digital elevation models (DEMs) from aerial laser scanning (ALS) data. However, cost and lack of knowledge may preclude its use. In contrast, global navigation satellite systems (GNSS) are seldom used to collect and generate DEMs. These receivers have the potential to be considered as data sources for DEM interpolation, as they can be inexpensive, easy to use, and mobile. The data interpolation method and spatial resolution from this method needs to be optimised to create accurate DEMs. Moreover, the density of GNSS data is likely to affect DEM accuracy. This study investigates three different deterministic approaches, in combination with spatial resolution and data thinning, to determine their combined effects on DEM accuracy. Digital elevation models were interpolated, with resolutions ranging from 0.5 m to 10 m using natural neighbour (NaN), topo to raster (ANUDEM), and inverse distance weighted (IDW) methods. The GNSS data were thinned by 25% (0.389 points m−2), 50% (0.259 points m−2), and 75% (0.129 points m−2) and resulting DEMs were contrast against a DEM interpolated from unthinned data (0.519 points m−2). Digital elevation model accuracy was measured by root mean square error (RMSE) and mean absolute error (MAE). It was found that the highest resolution, 0.5 m, produced the lowest errors in resulting DEMs (RMSE = 0.428 m, MAE = 0.274 m). The ANUDEM method yielded the greatest DEM accuracy from a quantitative perspective (RMSE = 0.305 m and MAE = 0.197 m); however, NaN produced a more visually appealing surface. In all the assessments, IDW showed the lowest accuracy. Thinning the input data by 25% and even 50% had relatively little impact on DEM quality; however, accuracy decreased markedly at 75% thinning (0.129 points m−2). This study showed that, in a time where ALS is commonly used to generate DEMs, GNSS-surveyed data can be used to create accurate DEMs. This study confirmed the need for optimization to choose the appropriate interpolation method and spatial resolution in order to produce a reliable DEM.

scholarly journals Accuracy Assessment of Open Source Digital Elevation Models

2018 ◽  
Vol 26 (3) ◽  
pp. 23-33
Author(s):  
Aqeel Abboud Abdul Hassan
Keyword(s):  
Open Source ◽  
Digital Elevation Model ◽  
Laser Scanning ◽  
Accuracy Assessment ◽  
Statistical Tests ◽  
Digital Elevation Models ◽  
Three Dimensional ◽  
Digital Elevation ◽  
And Performance ◽  
Elevation Model

Digital Elevation Model is a three-dimensional representation of the earth's surface, which is essential for Geoscience and hydrological implementations. DEM can be created utilizing Photogrammetry techniques, radar interferometry, laser scanning and land surveying. There are some world agencies provide open source digital elevation models which are freely available for all users, such as the National Aeronautics and Space Administration (NASA), Japan Aerospace Exploration Agency’s (JAXA) and others. ALOS, SRTM and ASTER are satellite based DEMs which are open source products. The technologies that are used for obtaining raw data and the methods used for its processing and on the other hand the characteristics of natural land and land cover type, these and other factors are the cause of implied errors produced in the digital elevation model which can't be avoided. In this paper, ground control points observed by the differential global positioning system DGPS were used to compare the validation and performance of different satellite based digital elevation models. For validation, standard statistical tests were applied such as Mean Error (ME) and Root Mean Square Error (RMSE) which showed ALOS DEM had ME and RMSE are -1.262m and 1.988m, while SRTM DEM had ME of -0.782m with RMSE of 2.276m and ASTER DEM had 4.437m and 6.241m, respectively. These outcomes can be very helpful for analysts utilizing such models in different areas of work.

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 Study of Digital Elevation Model (DEM) Extraction using Stereo Radargrammetry TerraSAR-X in Madiun Area – Elevation Accuracy Improvement

2019 ◽  
Vol 94 ◽  
pp. 04003 ◽  
Author(s):  
Inggit L. Sari ◽  
Rachmat Maulana ◽  
Haris S. Dyatmika ◽  
Agus Suprijanto ◽  
Rahmat Arief ◽  
...  
Keyword(s):  
High Resolution ◽  
Digital Elevation Model ◽  
Field Observation ◽  
Incidence Angle ◽  
Accuracy Assessment ◽  
Surface Elevation ◽  
Accuracy Improvement ◽  
Digital Elevation ◽  
High Resolution Images ◽  
Elevation Model

High resolution images data from Terrasar-X are used to extract digital elevation model (DEM) using stereo radargrammetry in the attempt to achieve better resolution of terrain surface in Indonesia. As sample in this study, stereo pairs images from TerraSAR-X StripMap mode (~3m resolution) on Madiun city is used with difference of incidence angle around ~18.88 degree to extract the elevation of the area. Furthermore, field observation on the selected area will be used on elevation accuracy assessment. The digital surface elevation (DSM) generated by stereo radargrammetry in this study shows us high resolution with spatial pixel spacing 5.57 meter and elevation accuracy around ~4 meter.

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