scholarly journals Accuracy Assessment of Digital Elevation Models Produced From Different Geomatics Data

2020 ◽  
Vol 38 (11A) ◽  
pp. 1580-1592
Author(s):  
Imzahim A. Alwan ◽  
Zina W. Samueel ◽  
Qassim K. Abdullah
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Accuracy Assessment ◽  
Digital Elevation Models ◽  
Ground Cover ◽  
Interferometric Synthetic Aperture Radar ◽  
Sensing Applications ◽  
Digital Elevation ◽  
Source Models ◽  
Remote Sensing Applications

Digital Elevation Models (DEM) are now being used in several geospatial applications. DEMs play an important role in the preliminary surveys for constructing dams and reservoirs, highways, canals, and projects in which earth work is essential. In many remote sensing applications, DEMs have become a significant tool for InSAR (Interferometric Synthetic Aperture Radar) processing, ground cover classification and images ortho-rectification. In this study, the accuracy of DEMs obtained from ALOS V1.1, ASTER V2, SRTM V3 and other obtained from a pair of Pleiades high-resolution (PHR) 1B satellites in a study area were evaluated after comparing them with high accuracy GNSS/RTK checkpoints. The SRTM3, ALOS V1.1, ASTER V2 DEM revealed a Root Mean Square Error (RMSE) of 2.234m, 0.838m, and 15.116m respectively; while the DEM which is produced from a 0.5m resolution of Pleiades 0.5m shows an RMSE of 0.642m. The correct bias Linear transformation algorithm was used and the RMSE results were: SRTM V3 (1.319m), ALOS V1.1 (0.830m), ASTER V2 (3.815m), and PHR (0.433m). The results showed that the ALOS V1.1 model is the most accurate of the open source models followed by the SRTM V3 model and then followed by ASTER V2. The results obtained from a pair by Pleiades high-resolution (PHR) 1B satellites show a higher accuracy than the results obtained from the open source models.

scholarly journals Creating HiRISE digital elevation models for Mars using the open-source Ames Stereo Pipeline

2019 ◽  
Vol 8 (2) ◽  
pp. 293-313 ◽  
Author(s):  
Adam J. Hepburn ◽  
Tom Holt ◽  
Bryn Hubbard ◽  
Felix Ng
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Digital Elevation Models ◽  
Surface Processes ◽  
Simple Application ◽  
Intermediate Data ◽  
Primary Scale ◽  
Digital Elevation ◽  
Global Datasets ◽  
Geomorphic Processes

Abstract. The present availability of sub-decametre digital elevation models on Mars – crucial for the study of surface processes – is scarce. In contrast to low-resolution global datasets, such models enable the study of landforms <10 km in size, which is the primary scale at which geomorphic processes have been active on Mars over the last 10–20 Myr . Stereogrammetry is a means of producing digital elevation models from stereo pairs of images. The HiRISE camera on board the Mars Reconnaissance Orbiter has captured >3000 stereo pairs at 0.25 m pixel−1 resolution, enabling the creation of high-resolution digital elevation models (1–2 m pixel−1). Hitherto, only ∼500 of these pairs have been processed and made publicly available. Existing pipelines for the production of digital elevation models from stereo pairs, however, are built upon commercial software, rely upon sparsely available intermediate data, or are reliant on proprietary algorithms. In this paper, we present and test the output of a new pipeline for producing digital elevation models from HiRISE stereo pairs that is built entirely upon the open-source NASA Ames Stereo Pipeline photogrammetric software, making use of freely available data for cartographic rectification. This pipeline is designed for simple application by researchers interested in the use of high-resolution digital elevation models. Implemented here on a research computing cluster, this pipeline can also be used on consumer-grade UNIX computers. We produce and evaluate four digital elevation models using the pipeline presented here. Each are globally well registered, with accuracy similar to those of digital elevation models produced elsewhere.

scholarly journals A semi-automated method for extracting channels and channel profiles from lidar-derived digital elevation models

Geosphere ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 806-816
Author(s):  
Pinliang Dong ◽  
Ruofei Zhong ◽  
Jisheng Xia ◽  
Shucheng Tan
Keyword(s):  
High Resolution ◽  
Accuracy Assessment ◽  
Digital Elevation Models ◽  
Stream Channels ◽  
Channel Detection ◽  
Automated Method ◽  
San Andreas ◽  
Digital Elevation ◽  
Processing Techniques ◽  
User Friendly

Abstract With the advent of digital elevation models (DEMs) and geographic information systems (GIS), several methods have been proposed to extract channels from raster DEMs. Light detection and ranging (lidar) can produce high-resolution DEMs and poses new challenges to existing methods for channel extraction. This paper introduces a semi-automated method for extracting stream channels and channel profiles from high-resolution DEMs using image processing techniques. Based on user-specified approximate locations of start and end points and a few simple parameters, the method implements five automated steps: (1) channel detection using a local minimum value search; (2) channel delineation using Bresenham’s line algorithm and mathematical morphological operation; (3) vectorization; (4) profile generation; and (5) accuracy assessment. The method is implemented as an ArcGIS Python add-in toolbar named Channel Extraction. The application of the toolbar is demonstrated using a lidar-derived DEM in a study area along the San Andreas fault in California, USA. The software and test data are freely available for download (see Supplemental Files1). The demonstrated samples suggest that this new semi-automated method for extracting channels and channel profiles is flexible and user-friendly and can produce accurate results to support geomorphic studies.

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.

An open-source toolset for automated processing of historic spy photos: sPyMicMac

2020 ◽  
Author(s):  
Robert McNabb ◽  
Luc Girod ◽  
Christopher Nuth ◽  
Andreas Kääb
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Digital Elevation Models ◽  
Automated Detection ◽  
The Arctic ◽  
Ground Control ◽  
High Mountain ◽  
Landsat 8 ◽  
Elevation Change ◽  
Digital Elevation

&lt;p&gt;First launched in 1971, the KH-9 &amp;#8220;Hexagon&amp;#8221; reconnaissance satellites were operational until 1986. In addition to the high-resolution main cameras, the satellites had a secondary camera system, the mapping camera, which acquired images at approximately 6-10m ground resolution. These images, declassified in 2002, provide an unparalleled ability to extend records of elevation change over areas of the world where older data, typically from aerial photogrammetry, are missing, unavailable, or unreliable, including High Mountain Asia and the Arctic. These images are not, however, free from challenges. Storage and film processing have introduced warping into the images, and the large film format means that images are scanned in halves which must be precisely re-aligned for photogrammetric processing.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Building on previous efforts, we have developed an open-source toolset, based in python, that performs several of the steps necessary for processing digital elevation models (DEMs) from the raw imagery within MicMac. These include precise re-alignment based on dense keypoint detection, automated detection of the reseau field to aid in un-warping of the images, color balancing to increase contrast in low-contrast areas, and automated detection of ground control points using modern orthorectified satellite images such as Sentinel-2 and Landsat 8, and high-resolution digital elevation models such as ArcticDEM. Each of these tools interface with the MicMac photogrammetry software package that performs each of the steps necessary for DEM extraction.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;We have tested this toolset on scenes from Alaska, Iceland, and Norway. Comparison to external elevation datasets such as NASA&amp;#8217;s Ice, Cloud and Elevation Satellite (ICESat), ArcticDEM, and national elevation products yields agreement of better than 10 m root mean square error over stable terrain, even in mountainous areas. In particular, we obtain satisfactory results in remote areas where precise ground control measurements are difficult to obtain. This toolset provides the ability to easily extend records of precise elevation change in areas where very little historic data exist. In addition, the GCP matching routine can be used to process other air photo datasets, providing a useful tool for processing older photo archives.&lt;/p&gt;

scholarly journals Creating HiRISE digital elevation models for Mars using the open-source Ames Stereo Pipeline

2019 ◽  
Author(s):  
Adam J. Hepburn ◽  
Tom Holt ◽  
Bryn Hubbard ◽  
Felix Ng
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Digital Elevation Models ◽  
Surface Processes ◽  
Low Resolution ◽  
Commercial Software ◽  
Pixel Resolution ◽  
Intermediate Data ◽  
Digital Elevation ◽  
The Creation

Abstract. The present availability of sub-decametre digital elevation models on Mars – crucial for the study of surface processes – is scarce. In contrast to the globally-available but low-resolution datasets, such models enable the study of landforms  3000 stereo pairs at 25 cm/pixel resolution, enabling the creation of high-resolution digital elevation models (1–2 m/pixel). However, only ~ 500 of these pairs have been processed and made publicly available to date. Existing pipelines for the production of digital elevation models from stereo-pairs, however, are built upon commercial software, rely upon sparsely-available intermediate data, or are reliant on proprietary algorithms. Here, we present and test the output of a new pipeline for producing digital elevation models from HiRISE stereo pairs that is built entirely upon the open source NASA Ames Stereo Pipeline photogrammetric software, making use of freely available data for cartographic rectification. This pipeline is implemented here on a research computing cluster, but can also be used on consumer-grade UNIX computers. The four output digital elevation models produced using the pipeline presented here are globally well-registered, with accuracy similar to those of multiple digital elevation models produced elsewhere.

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