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Drones
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Drones in Geography
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Drones in Geography

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: closed (15 January 2021) | Viewed by 33044

Special Issue Editors

Dr. Anthony R. Cummings

E-Mail Website
Guest Editor
Geospatial Information Sciences, School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA
Interests: UAS; human–environment interactions; citizen science; natural resource monitoring
Dr. Adam J. Mathews

E-Mail Website
Guest Editor
Department of Geography, Western Michigan University, Kalamazoo, MI 49008, USA
Interests: GIScience; remote sensing; UAS; lidar; geography
Dr. Stephanie R. Rogers

E-Mail Website
Guest Editor
Department of Geosciences, Auburn University, Auburn, AL 36849, USA
Interests: GIScience; remote sensing; UAS; water; environmental applications
Special Issues, Collections and Topics in MDPI journals
Dr. Kunwar K. Singh

E-Mail Website
Guest Editor
Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
Interests: urban and ex-urban land change; biological invasion; natural resources assessments; remote sensing data integration; light detection and ranging; UAV

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit manuscripts to the MDPI Drones Special Issue on “Drones in Geography”.

Low-cost and relatively easy-to-use drones (or unoccupied aerial/aircraft systems (UAS), unmanned aerial vehicles (UAV), and small remotely piloted aircraft (sRPA)) have enabled geographers to collect very high resolution (e.g., <2-cm spatial resolution) geospatial data and imagery at an unprecedented rate from a wide variety of remote sensors (e.g., multispectral, thermal, lidar, and atmospheric variables). Geographers from a variety of subfields (e.g., remote sensing, GIS, photogrammetry, geomorphology, and biogeography) have adopted drones to capture data for dynamic natural systems into their research to map and model geospatial processes. As leaders in geospatial science and technologies, geographers are vital to the advancement of the use of drones for mapping purposes (i.e., geographers commonly blend knowledge areas of photogrammetry, geographic information science, and remote sensing). This Special Issue will document a variety of research produced by geographers using drones as a geospatial tool, and how drones are being incorporated into geography education.

This Special Issue is inspired by the success of the UAS Symposium, organized by the editors and collaborators, held at the American Association of Geographers (AAG) Annual Meeting in 2018 and 2019. The UAS Symposium has continued to bring together geographers from around the world to share their findings of drone applications through research presentations and posters, summarize and conceptualize the contributions of geographers to this developing subfield (i.e., drone remote sensing) through panel sessions, and more. While those who have participated in a previous symposium, or plan to participate in the 2020 UAS Symposium, are highly encouraged to submit a manuscript, we welcome and encourage submissions from geographers outside of this group.

Within this context, we invite manuscripts for this Special Issue on “Drones in Geography”. Papers are solicited in areas directly related to these topics, both conceptual and applied in nature, including, but not limited to, the following:

  • Land use and land cover change
  • Citizen science and participatory mapping research
  • Invasive species mapping and modeling
  • Archaeology and cultural resource studies
  • Landscape modeling
  • Applications in land rights issues
  • Natural resources monitoring and management
  • Natural hazard assessment (e.g., earthquake, landslides, and sea-level rise)
  • Geomorphological and fluvial processes
  • Algorithmic advances in computer vision (e.g., structure from motion and multi-view stereo) for mapping purposes
  • Analytical developments in the areas of point cloud analytics, 3D analyses, geographic object-based image analysis (GEOBIA), etc.
  • Critique of drone mapping applications including ethical and legal issues
  • Drone integration into the higher education geography curriculum and/or in the higher education geography classroom
  • Measurement of (and integration with) social and cultural data (and methodologies).
Dr. Anthony R. Cummings
Dr. Adam J. Mathews
Dr. Stephanie R. Rogers
Dr. Kunwar K. Singh
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. Drones is an international peer-reviewed open access monthly 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 2600 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

  • geography
  • geographic information science
  • remote sensing
  • drones
  • UAS
  • mapping
  • geospatial

Published Papers (4 papers)

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20 pages, 7741 KiB  
Article
An Integrated Spectral–Structural Workflow for Invasive Vegetation Mapping in an Arid Region Using Drones
by Arnold Chi Kedia, Brandi Kapos, Songmei Liao, Jacob Draper, Justin Eddinger, Christopher Updike and Amy E. Frazier
Drones 2021, 5(1), 19; https://doi.org/10.3390/drones5010019 - 8 Mar 2021
Cited by 14 | Viewed by 5348
Abstract
Mapping invasive vegetation species in arid regions is a critical task for managing water resources and understanding threats to ecosystem services. Traditional remote sensing platforms, such as Landsat and MODIS, are ill-suited for distinguishing native and non-native vegetation species in arid regions due [...] Read more.
Mapping invasive vegetation species in arid regions is a critical task for managing water resources and understanding threats to ecosystem services. Traditional remote sensing platforms, such as Landsat and MODIS, are ill-suited for distinguishing native and non-native vegetation species in arid regions due to their large pixels compared to plant sizes. Unmanned aircraft systems, or UAS, offer the potential to capture the high spatial resolution imagery needed to differentiate species. However, in order to extract the most benefits from these platforms, there is a need to develop more efficient and effective workflows. This paper presents an integrated spectral–structural workflow for classifying invasive vegetation species in the Lower Salt River region of Arizona, which has been the site of fires and flooding, leading to a proliferation of invasive vegetation species. Visible (RGB) and multispectral images were captured and processed following a typical structure from motion workflow, and the derived datasets were used as inputs in two machine learning classifications—one incorporating only spectral information and one utilizing both spectral data and structural layers (e.g., digital terrain model (DTM) and canopy height model (CHM)). Results show that including structural layers in the classification improved overall accuracy from 80% to 93% compared to the spectral-only model. The most important features for classification were the CHM and DTM, with the blue band and two spectral indices (normalized difference water index (NDWI) and normalized difference salinity index (NDSI)) contributing important spectral information to both models. Full article
(This article belongs to the Special Issue Drones in Geography)
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18 pages, 17732 KiB  
Article
Developing an Introductory UAV/Drone Mapping Training Program for Seagrass Monitoring and Research
by Bo Yang, Timothy L. Hawthorne, Margot Hessing-Lewis, Emmett J. Duffy, Luba Y. Reshitnyk, Michael Feinman and Hunter Searson
Drones 2020, 4(4), 70; https://doi.org/10.3390/drones4040070 - 3 Nov 2020
Cited by 25 | Viewed by 11217
Abstract
Unoccupied Aerial Vehicles (UAVs), or drone technologies, with their high spatial resolution, temporal flexibility, and ability to repeat photogrammetry, afford a significant advancement in other remote sensing approaches for coastal mapping, habitat monitoring, and environmental management. However, geographical drone mapping and in situ [...] Read more.
Unoccupied Aerial Vehicles (UAVs), or drone technologies, with their high spatial resolution, temporal flexibility, and ability to repeat photogrammetry, afford a significant advancement in other remote sensing approaches for coastal mapping, habitat monitoring, and environmental management. However, geographical drone mapping and in situ fieldwork often come with a steep learning curve requiring a background in drone operations, Geographic Information Systems (GIS), remote sensing and related analytical techniques. Such a learning curve can be an obstacle for field implementation for researchers, community organizations and citizen scientists wishing to include introductory drone operations into their work. In this study, we develop a comprehensive drone training program for research partners and community members to use cost-effective, consumer-quality drones to engage in introductory drone mapping of coastal seagrass monitoring sites along the west coast of North America. As a first step toward a longer-term Public Participation GIS process in the study area, the training program includes lessons for beginner drone users related to flying drones, autonomous route planning and mapping, field safety, GIS analysis, image correction and processing, and Federal Aviation Administration (FAA) certification and regulations. Training our research partners and students, who are in most cases novice users, is the first step in a larger process to increase participation in a broader project for seagrass monitoring in our case study. While our training program originated in the United States, we discuss our experiences for research partners and communities around the globe to become more confident in introductory drone operations for basic science. In particular, our work targets novice users without a strong background in geographic research or remote sensing. Such training provides technical guidance on the implementation of a drone mapping program for coastal research, and synthesizes our approaches to provide broad guidance for using drones in support of a developing Public Participation GIS process. Full article
(This article belongs to the Special Issue Drones in Geography)
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21 pages, 5526 KiB  
Article
Ground Control Point Distribution for Accurate Kilometre-Scale Topographic Mapping Using an RTK-GNSS Unmanned Aerial Vehicle and SfM Photogrammetry
by Eilidh Stott, Richard D. Williams and Trevor B. Hoey
Drones 2020, 4(3), 55; https://doi.org/10.3390/drones4030055 - 8 Sep 2020
Cited by 63 | Viewed by 9711
Abstract
Unmanned Aerial Vehicles (UAVs) have revolutionised the availability of high resolution topographic data in many disciplines due to their relatively low-cost and ease of deployment. Consumer-grade Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) equipped UAVs offer potential to reduce or eliminate ground [...] Read more.
Unmanned Aerial Vehicles (UAVs) have revolutionised the availability of high resolution topographic data in many disciplines due to their relatively low-cost and ease of deployment. Consumer-grade Real Time Kinematic Global Navigation Satellite System (RTK-GNSS) equipped UAVs offer potential to reduce or eliminate ground control points (GCPs) from SfM photogrammetry surveys, removing time-consuming target deployment. Despite this, the removal of ground control can substantially reduce the georeferencing accuracy of SfM photogrammetry outputs. Here, a DJI Phantom 4 RTK UAV is deployed to survey a 2 × 0.5 km reach of the braided River Feshie, Scotland that has local channel-bar relief of c.1 m and median grain size c.60 mm. Five rectangular adjacent blocks were flown, with images collected at 20° from the nadir across a double grid, with strips flown in opposing directions to achieve locally convergent imagery geometry. Check point errors for seven scenarios with varying configurations of GCPs were tested. Results show that, contrary to some published Direct Georeferencing UAV investigations, GCPs are not essential for accurate kilometre-scale topographic modelling. Using no GCPs, 3300 independent spatially-distributed RTK-GNSS surveyed check points have mean z-axis error −0.010 m (RMSE = 0.066 m). Using 5 GCPs gave 0.016 m (RMSE = 0.072 m). Our check point results do not show vertical systematic errors, such as doming, using either 0 or 5 GCPs. However, acquiring spatially distributed independent check points to check for systematic errors is recommended. Our results imply that an RTK-GNSS UAV can produce acceptable errors with no ground control, alongside spatially distributed independent check points, demonstrating that the technique is versatile for rapid kilometre-scale topographic survey in a range of geomorphic environments. Full article
(This article belongs to the Special Issue Drones in Geography)
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15 pages, 4932 KiB  
Article
Measuring High Levels of Total Suspended Solids and Turbidity Using Small Unoccupied Aerial Systems (sUAS) Multispectral Imagery
by Elizabeth M. Prior, Frances C. O’Donnell, Christian Brodbeck, Wesley N. Donald, George Brett Runion and Stephanie L. Shepherd
Drones 2020, 4(3), 54; https://doi.org/10.3390/drones4030054 - 8 Sep 2020
Cited by 6 | Viewed by 4562
Abstract
Due to land development, high concentrations of suspended sediment are produced from erosion after rain events. Sediment basins are commonly used for the settlement of suspended sediments before discharge. Stormwater regulations may require frequent sampling and monitoring of these basins, both of which [...] Read more.
Due to land development, high concentrations of suspended sediment are produced from erosion after rain events. Sediment basins are commonly used for the settlement of suspended sediments before discharge. Stormwater regulations may require frequent sampling and monitoring of these basins, both of which are time and labor intensive. Potential remedies are small, unoccupied aerial systems (sUAS). The goal of this study was to demonstrate whether sUAS multispectral imagery could measure high levels of total suspended solids (TSS) and turbidity in a sediment basin. The sediment basin at the Auburn University Erosion and Sediment Control Testing Facility was used to simulate a local 2-year, 24-h storm event with a 30-min flow rate. Water samples were collected at three depths in two locations every 15 min for six hours with corresponding sUAS multispectral imagery. Multispectral pixel values were related to TSS and turbidity in separate models using multiple linear regressions. TSS and turbidity regression models had coefficients of determination (r2) values of 0.926 and 0.851, respectively. When water column measurements were averaged, the r2 values increased to 0.965 and 0.929, respectively. The results indicated that sUAS multispectral imagery is a viable option for monitoring and assessing sediment basins during high-concentration events. Full article
(This article belongs to the Special Issue Drones in Geography)
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