Precision of two topographic methods for generating digital elevation models in the high-andean areas of Peru: study case road fundo bocanegra - Chachapoyas

Computer-assisted forest road design mainly relies on a high-resolution digital elevation model (DEM), which provides terrain data for supporting the analysis of road design features. The resolution and accuracy of the DEM in representing the terrain structures vary depending on the preferred dataset, which then reflects some of the essential road features such as alignment, road slope, and earthwork. In this study, three forest road sections were designed by using high-resolution DEMs generated from UAV photogrammetry data, GNSS-GPS data and Total Station data. NetCAD 7.6 software, developed in Turkey and mostly used in road design applications, was used to perform the road design while calculating horizontal profiles, vertical profiles, curves, cross sections, and earthwork. The DEM generation capabilities for three datasets were compared based on spatial resolution, data collection and data processing stage. Then, the differences between three road sections were evaluated by considering specified road features such as alignment properties, road slope, and earthwork. The results indicated that the UAV (Unmanned Aerial Vehicles) based DEM generation method provided the highest resolution (10 cm), followed by the Total Station (56 cm) and GNSS-GPS (61 cm) based methods. When comparing the time for data collection procedure, it took 14 minutes, 70 minutes, and 110 minutes for UAV data, GNSS-GPS data, and Total Station data, respectively. On the other hand, UAV based method falls into a disadvantageous situation in data processing stage, due to high data processing time (3 hours). However, GNSS-GPS and Total Station based methods work only with spatial point data, so they require less processing time of 15 minutes and 25 minutes, respectively. The results indicated that road lengths were 294.8, 272.4 and 282.1 m and the average road slopes were 3.41%, 3.39%, and 3.31% for the road sections designed by using UAV, GNSS-GPS, and Total Station based DEMs, respectively. The excavation and landfill volumes were 369.16 m3 and 166.98 m3, 285.86 m3 and 201.83 m3, and 433.17 m3 and 183.95 m3, respectively. The results indicated that UAV photogrammetry data generates high-resolution DEMs that can be effectively used to design forest roads.

Presently, various different methods are being used for digital elevation model (DEM) generation. DEMs can be generated from topographic maps obtained with terrestrial measurements, photogrammetric flight data or remote sensing technologies. And also a question can be asked that which method is better than others that's why these DEM generation techniques have been analysed and the accuracies of DEMs have been compared in this study. For Zonguldak test field, three types of DEMs have been used. First DEM has been produced by digitized contour lines of 1:25000 scale topographic maps, second one has been produced by photogrammetric flight project data had been made by Zonguldak Municipality in 2005 and last one has been derived from Shuttle Radar Topography Mission (SRTM) X-band data which has used single-pass interferometric synthetic aperture radar (InSAR) technique for DEM generation. In the study, all these DEMs have been compared one by one based on selected reference. The DEM produced with Photogrammetric method has approximately 5.5 m better accuracy for open and flat, 6.5 m better accuracy for forest areas against the DEM generated from 1:25000 scale topographic maps. SRTM X-band DEM is 4 m less accurate for open, 4.5 m less accurate for forest areas against the DEM produced with photogrammetric method and 9.5 m less accurate for open, 11 m less accurate for forest areas against the DEM generated from 1:25000 scale topographic maps. And at the result, it has been clearly seen that the DEM produced by photogrammetric flight project in 2005 has better accuracy than the others.

Unmanned Aerial Vehicle (UAV) system, nowadays, is highly utilized to solve problems in various applications across different fields due to its low-cost, safety, and its low flying altitude. With photogrammetric techniques and latest available aerial technology, it is possible to utilize UAV for generation of Digital Elevation Model (DEM) and subsequently, determination of elevation on various geomorphology. Previously, this is only possible through deployment of manned aircraft and metric camera which requires monumental cost. This paper reviews the applications and developments of DEM generation. Three main components are presented in this review: (a) a summary of conventional surveying methods to determine elevation, subsequently generate a DEM, (b) a summary of remote sensing methods to generate DEM; namely satellites, and airborne platforms, and (c) findings and future possibilities for further studies. The review reveals that traditionally, DEM is produced through ground surveying methods, traditional photogrammetry methods, and derivation of contours and elevation points from hardcopy topographic maps. The chapters discuss each of the methods and common DEM products derived from them. Most of the studies reviewed herein articulate the mechanism of triangulation which is a method to rectify the DEM to its local geographical and elevation coordinates. So far, only a relatively small number of detailed studies have been conducted on the DEM produced by UAV. From the findings of flying the UAV at 4 different altitudes of 50 m, 80 m, 110 m and 140 m; much more research on the identification of elevation through UAV-based imagery is required from different altitude of flight. Hence, it is possible to use UAV to identify elevation in small areas which has limited project budget and time constraints.

Unmanned aerial vehicles (UAVs) are used more and more widely in various fields of activity and production. Industries using UAV images include agriculture and land use planning. From the images from the UAV, it is possible to generate digital elevation models (DEM) and digital terrain models (DTM) in a stereophotogrammetric manner, which can be used later for design work. At the same time, there is no need to use expensive specialized UAVs, since budget models of the domestic segment also allow to generate digital terrain models of high accuracy. So, for example, using the PHANTOM 4 model and using certain techniques, it is possible to generate DEM with an error of heights of 5-10 mm. However, such results were obtained due to the creation of almost ideal conditions for aerial survey. The authors of this work were tasked with investigating the possibility of DEM generation of a required accuracy with various options for the location of ground reference points, various parameters of aerial survey provided that photogrammetric processing of images will be carried out in the software Agisoft PhotoScan. To achieve these goals, an object for testing was selected, on which a network of reference and control points was created using a total station. According to the previously calculated parameters, aerial survey was carried out with a PHANTOM 4 UAV. Photogrammetric processing of aerial photographs was carried out in the software Agisoft PhotoScan. The accuracy of digital elevation models was assessed using the least squares method. According to the results of the calculations, the corresponding conclusions are made.

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for digital elevation model (DEM) generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the high-density characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented.

DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill

DEM generation from contours and a low-resolution DEM

Abstract. Data collection for digital elevation model (DEM) generation can be carried out by two main methods in space-borne remote sensing such as stereoscopy using optical or radar satellite imagery (stereophotogrammetry, respectively radargrammetry) and interferometry based on interferometric synthetic aperture radar (InSAR) data. These techniques have advantages and disadvantages in comparison against each other. Especially filling the gaps which arise from the problem of cloud coverage in DEM generation by optical imagery, InSAR became operational in recent years and DEMs became the most demanded interferometric products. Essentially, in comparison, DEM generation from synthetic aperture radar (SAR) images is not a simple manner like generation from optical satellite imagery. Interferometric processing has several complicated steps for the production of a DEM. The quality of the data set and used software package come into prominence for the stability of the generated DEM. In the paper, the interferometric processing steps for DEM generation from InSAR data and the crucial threshold values are tried to be explained. For DEM generation, a part of Istanbul (historical peninsula and near surroundings) was selected as the test field because of data availability. The data sets of two different imaging modes (StripMap ~ 3 m resolution and High Resolution Spotlight ~ 1 m resolution) of TerraSAR-X have been used. At the implementation, besides the determination of crucial points at interferometric processing steps, to define the effect of computer software, DEM production have been performed using two different software packages in parallel and the products have been compared In the result section of the paper, besides the colorful visualizations of final products along with the height scales, accuracy evaluations have been performed for both DEMs with the help of a more accurate reference digital terrain model (DTM). This reference model has been achieved by large scale aerial photos. Normally, it has a 5 m original grid spacing, however it has been resampled at a spacing of 1 m towards the needs of the research.

In this study, we generated Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) to confirm the suitability of UAV to the tidal flat study. The DEMs were generated from aerial triangulation method using rotary-wing UAV. For the accurate generation of mosaic images and DEM, the distorted images occurred by interior and exterior orientation were corrected using camera calibration. In addition, we set up a Ground Control Points (GCPs) in order to correct of the UAV position error. Therefore, the DEM was obtained with geometric error less than 30 cm. The height of generated DEM by UAV was compared with the levelled elevation by RTK-GPS and TanDEM-X radar satellite DEM. From this study, we could confirm that accurate DEM of the tidal flat can be generated using UAV and these detailed spatial information about tidal flat will be widely used for tidal flat management.

Forest structure attributes produced from terrestrial laser scanning (TLS) rely on normalisation of the point cloud values from sensor coordinates to height above ground. One method to do this is through the derivation of an accurate and repeatable digital elevation model (DEM) from the TLS point cloud that is used to adjust the height. The primary aim of this paper was to test a number of TLS scan configurations, filtering options and output DEM grid resolutions (from 0.02 m to 1.0 m) to define a best practice method for DEM generation in sub-tropical forest environments. The generated DEMs were compared to both total station (TS) spot heights and a 1-m DEM generated from airborne laser scanning (ALS) to assess accuracy. The comparison to TS spot heights found that a DEM produced using the minimum elevation (minimum Z value) from a point cloud derived from a single scan had mean errors >1 m for DEM grid resolutions <0.2 m at a 25-m plot radius. At a 1-m grid resolution, the mean error was 0.19 m. The addition of a filtering approach that combined a median filter with a progressive morphological filter and a global percentile filter was able to reduce mean error of the 0.02-m grid resolution DEM to 0.31 m at a 25-m plot radius using all returns. Using multiple scan positions to derive the DEM reduced the mean error for all DEM methods. Our results suggest that a simple minimum Z filtering DEM method using a single scan at the grid resolution of 1 m can produce mean errors <0.2 m, but for a small grid resolution, such as 0.02 m, a more complex filtering approach and multiple scan positions are required to reduced mean errors. The additional validation data provided by the 1-m ALS DEM showed that when using the combined filtering method on a point cloud derived from a single scan at the plot centre, errors between 0.1 and 0.5 m occurred in the TLS DEM for all tested grid resolutions at a plot radius of 25 m. These findings present a protocol for DEM production from TLS data at a range of grid resolutions and provide an overview of factors affecting DEMs produced from single and multiple TLS scan positions.

ABSTRACTThis article proposes a digital elevation model (DEM) generation approach using the Shuttle Radar Topography Mission (SRTM) DEM as the elevation constraint without ground control points. First, during the process of image block adjustment, we took advantage of the relatively high vertical accuracy of the SRTM-DEM in flat terrain regions and applied effective constraints on the object-space elevation-corrected value of tie points using the SRTM-DEM, achieving improved vertical accuracy for large-scale block adjustments. Subsequently, for the DEM matching process, multiple two-linear array stereo image pairs were obtained from along-track and across-track images with different look angles over the same region after the block adjustment. Then, the matching result of each stereo image pair underwent weighted fusion, before being used to generate the final DEM product. This approach can effectively enhance the matching quality and grid density of the final DEM product. The DEM generation experiment, using Ziyuan-3 images covering 186,000 km2 of Hubei Province, China, showed that the matching quality of the 10 m grid DEM was excellent. The vertical root mean square errors were 1.5 m in the flat regions and 2.96 m in the mountainous regions, thus achieving China’s 1:25,000 scale specification requirement for DEM products.

Generation of high-resolution Digital Elevation Model (DEM) is essential for space missions like an investigation of the topographic feature, a selection of landing site or a path planning of rover. Fusion of image which contains high-frequency information on the terrain surface and depth information which gives sparse information is an important topic in the generation of DEM. In this paper, the photometric stereo method is used to generate the surface normal information of shadowed region in the crater. Then, the surface normal is fused with interpolated DEM from ground truth DEM. The fusion enhances the lateral resolution of interpolated DEM and generates details of the ground truth DEM which is not shown in interpolated DEM. This method can be adapted to enhance DEM for near polar region, which has a large variation in shadow and has many image dataset due to orbiter's flight orbit.

Introduction: A digital elevation model (DEM) allows for the analysis of specific features on the earth’s surface in three dimensions. The engineering DEM is useful to evaluate resources and design management strategies. Objective: To evaluate the technical-operational feasibility of generating DEMs from total station (TS) topographic surveys, GPS RTK and aerial photogrammetry using an unmanned aerial vehicle (UAV). Methodology: A 20x20 m grid was traced in a plot without vegetation (1.4 ha) located in Montecillo, Estado de México, and topographic surveys were carried out with three methods, from which DEMs were generated for graphic and statistical evaluation and by tracing contour lines. Results: The estimated statistical errors were 0.15, 0.15 and 0.02 m, for TS vs. UAV, GPS RTK vs. UAV and TS vs. GPS RTK, respectively. Study limitations: The instruments used and the geographical conditions of central Mexico may be a reason for variation when extrapolating the results with other devices. Originality: A methodology is provided to generate DEMs accurately. The results allow the user to make reasoned choices based on the equipment available. Conclusion: The DEMs generated with TS and GPS RTK data have a smaller error than the one obtained from UAVs. The use of UAV helps in the representation of the terrain, since it generates a dense cloud of points that strengthens the procedure for topographic surveys.

Digital elevation models (DEMs) are becoming increasingly important components in national and regional spatial data infrastructure. High-quality DEMs can now be derived directly from airborne light detection and ranging (LiDAR) point-cloud data of high spatial density if the derivation process can be verified. However, LiDAR is relatively new compared with other technologies for terrain data collection, and, although offering the potential for providing better spatial resolution than those that have been routinely available before, will not diffuse among DEM users until the results of meeting the verification challenge are favourable enough to inspire re-organisation of spatial data in decision support for catchment management and other third-tier-of-government authorities. By way of exemplification, the research presented in this thesis concerned ways of improving the processing of the airborne LiDAR data for high-quality DEM generation in terms of both accuracy and efficiency, and explored the applications of LiDAR-derived DEMs in the region of the Corangamite Catchment Management Authority, Victoria, Australia. This thesis begins with a review of the traditional technologies for terrain data collection and DEM generation and compares them with the LiDAR technology. Accordingly, a review of the recently-reported advances in LiDAR data deployment for DEM generation is followed by reports of experiments designed to improve selection and deployment of LiDAR data filtering, modelling methods and data reduction, and the achievement of vertical accuracy for different land covers. Also reported are results of deployment of LiDAR data for ground truthing, and application of LiDAR data for the extraction of drainage networks on an area of deranged drainage: the Victorian Volcanic Plain. The show that: (a) the issues of filtering, modelling techniques, interpolation methods, DEM resolution, and data reduction are critical and must be considered carefully when using LiDAR data for a high-quality DEM generation; (b) it is efficient to use survey marks for the accuracy assessment of LiDAR data. Normal distribution must be tested in order to select a suitable measure for the accuracy assessment of LiDAR data over different land covers; (c) LiDAR data reduction can improve the terrain production efficiency without compromising the product quality. The deployment of breaklines made a significant contribution to improving the accuracy of terrain models while allowing for data reduction; (d) it demonstrated the practical feasibility of applying ground control points from LiDAR intensity image and LiDAR-derived DEM in image orthorectification. The resultant orthoimage accuracy was shown to be superior to that achieved by using (lower accuracy) data sources such as those from Vicmap data; and (e) the LiDAR-derived DEM offers the capability of extracting and delineating the drainage networks in much more detail in low¬relief terrain, including areas in which drainage is barely coherent; The advantages of using LiDAR-derived DEM over the lower-accuracy DEM emerge in terms of stream order, stream number and stream length.

With the launch of the Indian remote sensing satellite Cartosat‐1, an along‐track stereoscopic imaging mission of the Indian Space Research Organisation (ISRO), new possibilities for operational availability of high‐resolution stereo‐imagery from space for the remote sensing and cartography user communities have emerged. The high‐resolution stereo data beamed from twin cameras on board the Cartosat‐1 mission facilitates topographic mapping up to 1:25 000 scale. The primary advantage of the Cartosat‐1 mission is seen in the generation of digital elevation models (DEMs) and the production of ortho‐images in an operational set‐up. This also facilitates 3D terrain visualisation for very large tracts of land. Stereo Strip Triangulation (SST) is a software system developed and perfected at the Space Applications Centre of ISRO for operational generation of secondary control and appropriate DEMs for subsequent use in the generation of ortho‐images. This system has been in use for almost 2 years at the National Remote Sensing Agency in Hyderabad, India, and has generated a wealth of data for use in topographic mapping. An initiative to generate a database of seamless, homogeneous DEMs and associated ortho‐image tiles at country level has been undertaken by ISRO. This data‐set has been named CartoDEM. The Cartosat‐1 data processing team has completed the design and testing of software for the generation of the CartoDEM. This software system has undergone detailed evaluation and currently is in the final stage of development of the operational procedures required to make maximum use of the capabilities of the Cartosat‐1 sensors. A data dissemination software system is currently under development. As part of the large‐scale evaluation exercises to finalise the specifications of CartoDEM, it is established that with the 2·5 m ground resolution, a base‐to‐height ratio of 0·62 and with capability to register conjugate points in the stereopair to sub‐pixel level, DEMs can be generated at 0·3 arc second intervals, with a height accuracy of 3 to 4 m, over tracts of undulating land mass up to 15 000 km2 with the use of 10 to 20 ground control points. The Cartosat‐1 data processing and evaluation team regularly monitors the radiometric quality of images. As part of the radiometric characterisation of sensors, the team computed point spread functions (PSFs) for the two cameras of Cartosat‐1. Special filters based on the PSFs then work to improve the radiometric quality of the images. Initial results from these exercises show good promise in image restoration based on PSFs for Cartosat‐1. This paper presents a summary of activities and exercises related to (i) Stereo Strip Triangulation, (ii) CartoDEM, (iii) image quality improvement using the PSF‐based image restoration and (iv) block adjustment exercises using a COTS software package. Also reported are the results of post‐launch experiments, study and evaluation of DEMs vis‐à‐vis ortho‐images from Cartosat‐1.