scholarly journals BADANIE MOŻLIWOŚCI WYKORZYSTANIA ZOBRAZOWAŃ DYNAMICZNYCH (WIDEO) Z NISKIEGO PUŁAPU LOTNICZEGO (BSP) DO OPRACOWAŃ FOTOGRAMETRYCZNYCH

1970 ◽  
pp. 53-64
Author(s):  
ADAM MŁYNARCZYK ◽  
SŁAWOMIR KRÓLEWICZ ◽  
PAWEŁ RUTKOWSKI
Keyword(s):  
High Altitude ◽  
Unmanned Aerial Vehicles ◽  
Point Cloud ◽  
Digital Terrain Model ◽  
Image Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Aerial Vehicles ◽  
The Creation ◽  
Recorded Image

The use of unmanned aerial vehicles is becoming more and more popular for making high-altitude and orthophotomap models. In this process, series of images are taken at specific intervals, usually lasting several seconds. This article demonstrates the ability to make models and orthophotomaps from dynamic images – video recorded from UAV. The best mutual coverage of photographs was indicated (95–96%) and the photogrammetric process for joining images was presented, through the creation of a point cloud to obtain a digital terrain model and the orotfotomap. The data was processed in 150 different variants and the usefulness of this method was demonstrated. Problems and errors that may occur during the processing of recorded image data are also described.

scholarly journals Polymodal Method of Improving the Quality of Photogrammetric Images and Models

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3457
Author(s):  
Pawel Burdziakowski
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Digital Terrain Model ◽  
Object Model ◽  
Quality Requirements ◽  
Terrain Model ◽  
Geometry Model ◽  
Digital Terrain ◽  
Lighting Conditions ◽  
Aerial Vehicles

Photogrammetry using unmanned aerial vehicles has become very popular and is already commonly used. The most frequent photogrammetry products are an orthoimage, digital terrain model and a 3D object model. When executing measurement flights, it may happen that there are unsuitable lighting conditions, and the flight itself is fast and not very stable. As a result, noise and blur appear on the images, and the images themselves can have too low of a resolution to satisfy the quality requirements for a photogrammetric product. In such cases, the obtained images are useless or will significantly reduce the quality of the end-product of low-level photogrammetry. A new polymodal method of improving measurement image quality has been proposed to avoid such issues. The method discussed in this article removes degrading factors from the images and, as a consequence, improves the geometric and interpretative quality of a photogrammetric product. The author analyzed 17 various image degradation cases, developed 34 models based on degraded and recovered images, and conducted an objective analysis of the quality of the recovered images and models. As evidenced, the result was a significant improvement in the interpretative quality of the images themselves and a better geometry model.

scholarly journals Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Joseph P. Hupy ◽  
Cyril O. Wilson
Keyword(s):  
Soil Erosion ◽  
Point Cloud ◽  
Empirical Evaluation ◽  
Digital Terrain Model ◽  
Surface Flow ◽  
Sediment Loading ◽  
Terrain Model ◽  
Digital Terrain ◽  
Statistical Measures ◽  
Geospatial Datasets

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM.

scholarly journals ASSESSMENT OF THE QUALITY OF DIGITAL TERRAIN MODEL PRODUCED FROM UNMANNED AERIAL SYSTEM IMAGERY

2016 ◽  
Vol XLI-B1 ◽  
pp. 893-899
Author(s):  
M. Kosmatin Fras ◽  
A. Kerin ◽  
M. Mesarič ◽  
V. Peterman ◽  
D. Grigillo
Keyword(s):  
Quality Assessment ◽  
Point Cloud ◽  
Digital Terrain Model ◽  
Quality Parameter ◽  
Unmanned Aerial System ◽  
Test Field ◽  
Absolute Deviation ◽  
Terrain Model ◽  
Digital Terrain

Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.

scholarly journals Presenting a Morphological Based Approach for Filtering The Point Cloud to Extract the Digital Terrain Model

2019 ◽  
Vol 6 (4) ◽  
pp. 73-96
Author(s):  
Parham Pahlavani ◽  
Hamid Reza Sahraiian ◽  
Behnaz Bigdeli ◽  
◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Reduction Method for Mobile Laser Scanning Data

2018 ◽  
Vol 7 (7) ◽  
pp. 285 ◽  
Author(s):  
Wioleta Błaszczak-Bąk ◽  
Zoltan Koppanyi ◽  
Charles Toth
Keyword(s):  
Data Reduction ◽  
Point Cloud ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
New Approach ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser ◽  
Short Time ◽  
Mls Method

Mobile Laser Scanning (MLS) technology acquires a huge volume of data in a very short time. In many cases, it is reasonable to reduce the size of the dataset with eliminating points in such a way that the datasets, after reduction, meet specific optimization criteria. Various methods exist to decrease the size of point cloud, such as raw data reduction, Digital Terrain Model (DTM) generalization or generation of regular grid. These methods have been successfully applied on data captured from Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS), however, they have not been fully analyzed on data captured by an MLS system. The paper presents our new approach, called the Optimum Single MLS Dataset method (OptD-single-MLS), which is an algorithm for MLS data reduction. The tests were carried out in two variants: (1) for raw sensory measurements and (2) for a georeferenced 3D point cloud. We found that the OptD-single-MLS method provides a good solution in both variants; therefore, the choice of the reduction variant depends only on the user.

Presenting a morphological based approach for filtering the point cloud to extract the digital terrain model

2018 ◽  
Vol 6 (3) ◽  
pp. 75-99
Author(s):  
Behnaz Bigdeli ◽  
Hamed Amini Amirkolaee Amini Amirkolaee ◽  
Parham Pahlavani ◽  
◽  
◽  
...  
Keyword(s):  
Point Cloud ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals ASSESMENT OF THE INFLUENCE OF UAV IMAGE QUALITY ON THE ORTHOPHOTO PRODUCTION

2015 ◽  
Vol XL-1/W4 ◽  
pp. 1-8 ◽  
Author(s):  
D. Wierzbicki ◽  
M. Kedzierski ◽  
A. Fryskowska
Keyword(s):  
Large Scale ◽  
Digital Terrain Model ◽  
Image Data ◽  
Weather Conditions ◽  
Noticeable Increase ◽  
Terrain Model ◽  
Digital Terrain ◽  
Lighting Conditions ◽  
Terrain Models ◽  
Uav Image

Over the past years a noticeable increase of interest in using Unmanned Aerial Vehicles (UAV) for acquiring low altitude images has been observed. This method creates new possibilities of using geodata captured from low altitudes to generate large scale orthophotos. Because of comparatively low costs, UAV aerial surveying systems find many applications in photogrammetry and remote sensing. One of the most significant problems with automation of processing of image data acquired with this method is its low accuracy. This paper presents the following stages of acquisition and processing of images collected in various weather and lighting conditions: aerotriangulation, generating of Digital Terrain Models (DTMs), orthorectification and mosaicking. In the research a compact, non-metric camera, mounted on a fuselage powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. Aerotriangulation and point cloud accuracy as well as generated digital terrain model and mosaic exactness were examined. Dense multiple image matching was used as a benchmark. The processing and analysis were carried out with INPHO UASMaster programme. Based on performed accuracy analysis it was stated that images acquired in poor weather conditions (cloudy, precipitation) degrade the final quality and accuracy of a photogrammetric product by an average of 25%.

Sign in / Sign up

Export Citation Format

Share Document