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Special Issue "Unmanned Aerial Systems and Digital Terrain Modeling"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 4013

Special Issue Editors

Dr. Alessandro Fornaciai
E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia (INGV), via della Faggiola 32, 56126 Pisa, Italy
Interests: digital terrain modeling and analysis; digital elevation models; unmanned aerial vehicles; LiDAR; tsunami hazard and modeling; lava flow hazard and modeling; topographic change detection; geomorphometry
Dr. Nicole Richter
E-Mail Website
Guest Editor
Observatoire Volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris - Sorbonne Paris Cité (OVPF-IPGP), La Plaine des Cafres, La Réunion, France
Interests: digital elevation models; InSAR; LiDAR; terrestrial laser scanning; unmanned aerial vehicles; volcano deformation; volcano morphology; evolution of volcanic landscapes; volcano edifice structure and stability; lava flow simulation and hazard assessment
Mr. Massimiliano Favalli
E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia (INGV), via della Faggiola 32, 56126 Pisa, Italy
Interests: digital elevation models; unmanned aerial vehicles; LiDAR; physical volcanology; lava flow simulation; tsunami simulation; geomorphometry
Mr. Luca Nannipieri
E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia (INGV), via della Faggiola 32, 56126 Pisa, Italy
Interests: Unmanned Aerial Vehicles; 3D modeling; High-Performance Computing; Networking; Web services

Special Issue Information

Dear Colleagues,

The Earth’s surface is shaped by complex geomorphological processes and the interplay between endogenous and exogenous forces. As a consequence, landforms and landscapes archive information about the environmental conditions and geological processes and dynamics that created and transformed them over time. At the same time, gravity-driven, terrain-following mass flows (e.g. water, debris and mud flows, landslides, lava flows, pyroclastic density currents), which can threaten human life and property, as well as infrastructure, are largely controlled by topography. Therefore, topographic data, mainly in the form of Digital Elevation Models (DEMs), have been widely generated and applied throughout essentially all geosciences. Various active and passive sensing techniques have been developed for producing DEM data, which include but are not limited to: stereo- and multi-view photogrammetry, light detection and ranging (LiDAR), and interferometric synthetic aperture radar (InSAR).

Recently, unmanned aerial vehicles (UAVs), more colloquially referred to as “drones”, have emerged as a new, efficient, and low-cost platform to facilitate topographic data acquisition. UAVs’ flexibility of operation, the capability of flying below layers of clouds, and its capacity of overflying large areas in relatively short time make UAV-mounted sensors systems an outstanding method for digital terrain modeling. The high spatio-temporal resolutions of resulting DEMs allow for improvement of existing methodologies and development of new ones to better integrate topography, morphology, and morphogenetic processes at a wide range of spatio-temporal scales. This significantly improves our means of monitoring, analyzing, and understanding the dynamics of Earth’s surface changes.

This Special Issue is open to research papers that use UAVs for digital terrain modeling. This includes studies demonstrating technological advancements of UAVs and on-board instrumentation, as well as research concerned with the interpretation and analysis of UAV-based topographic data and data products. We encourage submissions that make use of the high spatio-temporal data resolutions that can be obtained employing UAVs in order to push the boundaries beyond existing knowledge on gravity-driven mass flow behavior and related hazards.

Contributions may include, but are not limited to:

  • Technical advances of UAV systems and sensors that facilitate topographic data acquisition more efficiently and at unprecedented detail and quality.
  • Innovative integration of different data sources, such as optical cameras, GNSS sensors, and LiDAR systems, resulting in advanced data products.
  • Guidelines, recommendations and best practices regarding UAV surveys and data collection that have proved to perform well and produce optimal raw-data density, data point distribution and relative location accuracy.
  • New or improved DEM data processing methods and techniques, such as optimized Structure from Motion (SfM) algorithms and improved performance of other computer vision approaches.
  • Accuracy analyses and error assessments of UAV-acquired data and derived DEMs, including error detection, quantification, and propagation, as well as the comparison of different surface reconstruction methods.
  • Geomorphological mapping and morphometric analysis of landforms and landscapes based on UAV-derived DEMs, with particular emphasis on the advantages of high spatio-temporal DEM resolutions for the detection of topographic features and changes on very fine scales.
  • Topographic change detection and quantification by differentiating pre-, co-, and post-event UAV-derived DEMs aimed to quantify the volume added or removed by Earth surface processes as well as to improve the comprehension of their transport and emplacement mechanism.
  • Advancement in understanding the role of topography in the transport and emplacement mechanisms of gravity-driven flows and the resulting morphologies.
  • Advancement in the hazard assessment and management of hazardous phenomena (flooding, debris and mud flows, landslide, lava flow, and pyroclastic density current, etc.) thanks to the availability of UAV-based rapid and low-cost topographic updates and progresses in monitoring such phenomena through almost real-time topographic reconstruction.
  • Improvement in the computer modeling of gravity-driven flows resulting from the increase in the spatio-temporal resolution of UAV-derived topographic data.

Dr. Alessandro Fornaciai
Dr. Nicole Richter
Mr. Massimiliano Favalli
Mr. Luca Nannipieri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Unmanned Aerial Vehicles
  • Topographic mapping and change detection
  • Structure from Motion
  • Digital Terrain Modeling
  • Digital Elevation Models
  • Topography
  • Landscape evolution
  • Earth's surface processes
  • Geomorphometry

Published Papers (2 papers)

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Research

Article
Tracking the Evolution of Riverbed Morphology on the Basis of UAV Photogrammetry
Remote Sens. 2021, 13(4), 829; https://doi.org/10.3390/rs13040829 - 23 Feb 2021
Cited by 4 | Viewed by 1606
Abstract
Unmanned aerial vehicle (UAV) photogrammetry has recently become a widespread technique to investigate and monitor the evolution of different types of natural processes. Fluvial geomorphology is one of such fields of application where UAV potentially assumes a key role, since it allows for [...] Read more.
Unmanned aerial vehicle (UAV) photogrammetry has recently become a widespread technique to investigate and monitor the evolution of different types of natural processes. Fluvial geomorphology is one of such fields of application where UAV potentially assumes a key role, since it allows for overcoming the intrinsic limits of satellite and airborne-based optical imagery on one side, and in situ traditional investigations on the other. The main purpose of this paper was to obtain extensive products (digital terrain models (DTMs), orthophotos, and 3D models) in a short time, with low costs and at a high resolution, in order to verify the capability of this technique to analyze the active geomorphic processes on a 12 km long stretch of the French–Italian Roia River at both large and small scales. Two surveys, one year apart from each other, were carried out over the study area and a change detection analysis was performed on the basis of the comparison of the obtained DTMs to point out and characterize both the possible morphologic variations related to fluvial dynamics and modifications in vegetation coverage. The results highlight how the understanding of different fluvial processes may be improved by appropriately exploiting UAV-based products, which can thus represent a low-cost and non-invasive tool to crucially support decisionmakers involved in land management practices. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Digital Terrain Modeling)
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Article
Influence of Topographic Resolution and Accuracy on Hydraulic Channel Flow Simulations: Case Study of the Versilia River (Italy)
Remote Sens. 2019, 11(13), 1630; https://doi.org/10.3390/rs11131630 - 09 Jul 2019
Cited by 8 | Viewed by 1900
Abstract
The Versilia plain, a well-known and populated tourist area in northwestern Tuscany, is historically subject to floods. The last hydrogeological disaster of 1996 resulted in 13 deaths and in loss worth hundreds of millions of euros. A valid management of the hydraulic and [...] Read more.
The Versilia plain, a well-known and populated tourist area in northwestern Tuscany, is historically subject to floods. The last hydrogeological disaster of 1996 resulted in 13 deaths and in loss worth hundreds of millions of euros. A valid management of the hydraulic and flooding risks of this territory is therefore mandatory. A 7.5 km-long stretch of the Versilia River was simulated in one-dimension using river cross-sections with the FLO-2D Basic model. Simulations of the channel flow and of its maximum flow rate under different input conditions highlight the key role of topography: uncertainties in the topography introduce much larger errors than the uncertainties in roughness. The best digital elevation model (DEM) available for the area, a 1-m light detection and ranging (LiDAR) DEM dating back to 2008–2010, does not reveal all the hydraulic structures (e.g., the 40 cm thick embankment walls), lowering the maximum flow rate to only 150 m3/s, much lower than the expected value of 400 m3/s. In order to improve the already existing input topography, three different possibilities were considered: (1) to add the embankment walls to the LiDAR data with a targeted Differential GPS (DGPS) survey, (2) to acquire the cross section profiles necessary for simulation with a targeted DGPS survey, and (3) to achieve a very high resolution topography using structure from motion techniques (SfM) from images acquired using an unmanned aerial vehicle (UAV). The simulations based on all these options deliver maximum flow rates in agreement with estimated values. Resampling of the 10 cm cell size SfM-DSM allowed us to investigate the influence of topographic resolution on hydraulic channel flow, demonstrating that a change in the resolution from 30 to 50 cm alone introduced a 10% loss in the maximum flow rate. UAV-SfM-derived DEMs are low cost, relatively fast, very accurate, and they allow for the monitoring of the channel morphology variations in real time and to keep the hydraulic models updated, thus providing an excellent tool for managing hydraulic and flooding risks. Full article
(This article belongs to the Special Issue Unmanned Aerial Systems and Digital Terrain Modeling)
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