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Minerals
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Application of UAV and GIS for Geosciences, 2nd Edition
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Application of UAV and GIS for Geosciences, 2nd Edition

A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: closed (15 December 2024) | Viewed by 1504

Special Issue Editor

Prof. Dr. Konstantinos G. Nikolakopoulos

E-Mail Website
Guest Editor
Applied Geology & Geophysics, Department of Geology, University of Patras, ZC 26504 Patras, Greece
Interests: GIS; remote sensing; photogrammetery; hydrology; geological mapping
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Until a few years ago, Unmanned Aerial Vehicles (UAVs), more commonly known as drones, were only introduced to the wide public either as an extremely expensive military project or as a very cheap toy for kids. The use of UAVs for research purposes has recently become possible and affordable due to technological developments such as autopilot systems, lightweight action cameras, miniature GNSS sensors, advances in carbon fiber airframes and the simultaneous development of new processing methodologies based on computer vision including the structure from motion photogrammetry. Carrying different kinds of sensors, such as RGB, multispectral or thermal cameras, hyperspectral or Lidar sensors, or even ground penetrating radar and echo sounders, UAVs provide valuable information at extremely high spatial resolution and accuracy. The complexity of the above-mentioned information can be well stored, described and processed within the frame of a Geographic Information System (GIS), which is defined as a set of tools for the input, storage, management, analysis and cartographic representation of geographic information. This Special Issue aims to highlight the combination of UAV data and GIS techniques for Geosciences. Potential topics include, but are not limited to, the following:

  • Survey and mapping;
  • Mine monitoring;
  • Volcanology;
  • Archaeology and monument inspection;
  • Soil contamination;
  • Coastal erosion;
  • Disaster management;
  • Landslides;
  • Shallow water bathymetry;
  • Coral reef mapping;
  • Hydrology.

Prof. Dr. Konstantinos G. Nikolakopoulos
Guest Editor

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. Minerals 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 2400 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
  • GIS
  • remote sensing
  • photogrammetery
  • GNSS
  • multispectral cameras
  • hyperspectral cameras
  • thermal cameras
  • lidar

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Related Special Issue

Published Papers (2 papers)

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Research

21 pages, 15203 KiB  
Article
Geological and 3D Image Analysis toward Protecting a Geosite: The Case Study of Falakra, Limnos, Greece
by Ioannis K. Koukouvelas, Aggeliki Kyriou, Konstantinos G. Nikolakopoulos, Georgios Dimaris, Ioannis Pantelidis and Harilaos Tsikos
Minerals 2025, 15(2), 148; https://doi.org/10.3390/min15020148 - 31 Jan 2025
Viewed by 351
Abstract
The Falakra geosite is located at the northern shoreline of the island of Limnos, Greece, and exhibits an array of unusual geomorphological features developed in late Cenozoic sandstones. Deposition of the primary clastic sediments was overprinted by later, low-temperature hydrothermal fluid flow and [...] Read more.
The Falakra geosite is located at the northern shoreline of the island of Limnos, Greece, and exhibits an array of unusual geomorphological features developed in late Cenozoic sandstones. Deposition of the primary clastic sediments was overprinted by later, low-temperature hydrothermal fluid flow and interstitial secondary calcite formation associated with nearby volcanic activity. Associated sandstone cannonballs take center stage in a landscape built by joints, Liesengang rings and iron (hydr)oxide precipitates, constituting an intriguing site of high aesthetic value. The Falakra geosite is situated in an area with dynamic erosion processes occurring under humid weather conditions. These have evidently sculpted and shaped the sandstone landscape through a complex interaction of wave- and wind-induced erosional processes aided by salt spray wetting. This type of geosite captivates scientists and nature enthusiasts due to its unique geological and landscape features, making its sustainable conservation a significant concern and topic of debate. Here, we provide detailed geological and remote sensing mapping of the area to improve the understanding of geological processes and their overall impact. Given the significance of the Falakra geosite as a unique tourist destination, we emphasize the importance of developing it under sustainable management. We propose the segmentation of the geosite into four sectors based on the corresponding geological features observed on site. Sector A, located to the west, is occupied by a lander-like landscape; to the southeast, sector B contains clusters of cannonballs and concretions; sector C is characterized by intense jointing and complex iron (hydr)oxide precipitation patterns, dominated by Liesengang rings, while sector D displays cannonball or concretion casts. Finally, we propose a network of routes and platforms to highlight the geological heritage of the site while reducing the impact of direct human interaction with the outcrops. For constructing the routes and platforms, we propose the use of serrated steel grating. Full article
(This article belongs to the Special Issue Application of UAV and GIS for Geosciences, 2nd Edition)
18 pages, 12205 KiB  
Article
An Open-Pit Mines Land Use Classification Method Based on Random Forest Using UAV: A Case Study of a Ceramic Clay Mine
by Yuanrong He, Yangfeng Lai, Bingning Chen, Yuhang Chen, Zhiying Xie, Xiaolin Yu and Min Luo
Minerals 2024, 14(12), 1282; https://doi.org/10.3390/min14121282 - 17 Dec 2024
Viewed by 622
Abstract
Timely and accurate land use information in open-pit mines is essential for environmental monitoring, ecological restoration planning, and promoting sustainable progress in mining regions. This study used high-resolution unmanned aerial vehicle (UAV) imagery, combined with object-oriented methods, optimal segmentation algorithms, and machine learning [...] Read more.
Timely and accurate land use information in open-pit mines is essential for environmental monitoring, ecological restoration planning, and promoting sustainable progress in mining regions. This study used high-resolution unmanned aerial vehicle (UAV) imagery, combined with object-oriented methods, optimal segmentation algorithms, and machine learning algorithms, to develop an efficient and practical method for classifying land use in open-pit mines. First, six land use categories were identified: stope, restoration area, building, vegetation area, arterial road, and waters. To achieve optimal scale segmentation, an image segmentation quality evaluation index is developed, emphasizing both high intra-object homogeneity and high inter-object heterogeneity. Second, spectral, index, texture, and spatial features are identified through out-of-bag (OOB) error of random forest and recursive feature elimination (RFE) to create an optimal multi-feature fusion combination. Finally, the classification of open-pit mines was executed by leveraging the optimal feature combination, employing the random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) classifiers in a comparative analysis. The experimental results indicated that classification of appropriate scale image segmentation can extract more accurate land use information. Feature selection effectively reduces model redundancy and improves classification accuracy, with spectral features having the most significant effect. The RF algorithm outperformed SVM and KNN, demonstrating superior handling of high-dimensional feature combinations. It achieves the highest overall accuracy (OA) of 90.77%, with the lowest misclassification and omission errors and the highest classification accuracy. The disaggregated data facilitate effective monitoring of ecological changes in open-pit mining areas, support the development of mining plans, and help predict the quality and heterogeneity of raw clay in some areas. Full article
(This article belongs to the Special Issue Application of UAV and GIS for Geosciences, 2nd Edition)
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