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GIS and Remote Sensing Applications in Geomorphology

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A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 21191

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Special Issue Editors

Dr. Emmanouil Psomiadis

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Guest Editor

Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
Interests: earth observation; GIS; agriculture; geomorphology; natural resources; disasters
Special Issues, Collections and Topics in MDPI journals

Dr. Konstantinos X. Soulis

E-Mail Website
Guest Editor

Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece
Interests: hydrology; environmental hydrology; hydrological modeling; hydrometry; WRM; irrigation; irrigation water management; soil hydrology; geographical information systems (GIS)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geomorphology is the study of the landforms and landscapes, their processes, form and sediments at the inland or coastal surface of the earth. Geomorphological mapping is the main process for providing data for the analysis of landforms and the management of land and water resources. Geomorphology constitutes the most crucial parameter in understanding Earth's surface processes, relief configuration, and landscape evolution. Furthermore, geomorphological maps and geomorphological process delineation are essential, for several other sectors of environmental research, land and water conservation organizers, natural hazard and risk managers, urban planners and construction engineers, and scientists dealing with landscapes and landforms, as well as inland and coastal land use/cover changes.

Recent advances in remote sensing, geographic information systems (GIS), and availability of a growing number of new sensors (UAV, airborne, and spaceborne) and remote-sensing-based digital elevation models have led to a revolution in the field of geomorphological mapping and enhanced the ability to understand the surface processes more clearly. Innovative remote sensing data are providing data on landform distribution, surface composition, land and water processes, inland and coastal changes, natural disasters with higher spectral, temporal, and spatial resolution. These advanced tools in addition to the extended capabilities of GIS and geospatial analysis considerably expand the capacity of geomorphological mapping.

This Special Issue aims to review and synthesize all the contributions and the newest progress of methodologies and tools of GIS and remote sensing in geomorphological mapping and geomorphological processes, with a focus on natural hazards, coastal geomorphology, land use/cover change, etc.

Prospective authors are encouraged to submit articles concerning the following topics:

Remote sensing and GIS-based mapping of geomorphological characteristics of landforms;
Enhanced algorithms of image analysis for geomorphological mapping;
UAV in geomorphological mapping;
Remote sensing and GIS applications in inland and coastal geomorphological changes;
Methodologies for the assessment and mapping of geomorphological hazard and risk, to support land management and planning and tools for risk mitigation and reduction;
Remote sensing and GIS applications in natural disasters related to geomorphological characteristics;
Remote sensing and GIS applications in land and water processes (soil erosion, coastal processes etc.);
Cartography, digital elevation models, UAV, LiDAR in geomorphological applications.

Dr. Emmanouil Psomiadis
Dr. Konstantinos Soulis
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. ISPRS International Journal of Geo-Information 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 1700 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

geomorphology
GIS
remote sensing
UAV
LiDAR

Published Papers (5 papers)

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Research

27 pages, 17502 KiB

Open AccessArticle

Long and Short-Term Coastal Changes Assessment Using Earth Observation Data and GIS Analysis: The Case of Sperchios River Delta

by Emmanouil Psomiadis

ISPRS Int. J. Geo-Inf. 2022, 11(1), 61; https://doi.org/10.3390/ijgi11010061 - 14 Jan 2022

Cited by 2 | Viewed by 2762

Abstract

The present study provides information about the evolution of the Sperchios River deltaic area over the last 6500 years. Coastal changes, due to natural phenomena and anthropogenic activities, were analyzed utilizing a variety of geospatial data such as historic records, topographic maps, aerial photos, and satellite images, covering a period from 4500 BC to 2020. A qualitative approach for the period, from 4500 BC to 1852, and a quantitative analysis, from 1852 to the present day, were employed. Considering their scale and overall quality, the data were processed and georeferenced in detail based on the very high-resolution orthophoto datasets of the area. Then, the multitemporal shorelines were delineated in a geographical information system platform. Two different methods were utilized for the estimation of the shoreline changes and trends, namely the coastal change area method and the cross-section analysis, by implementing the digital shoreline analysis system with two statistical approaches, the end point rate and the linear regression rate. Significant river flow and coastline changes were observed with the overall increase in the delta area throughout the study period reaching 135 km² (mean annual growth of 0.02 km²/yr) and the higher accretion rates to be detected during the periods 1805–1852, 1908–1945 and 1960–1986, especially at the central and north part of the gulf. During the last three decades, the coastline has remained relatively stable with a decreasing tendency, which, along with the expected sea-level rise due to climate change, can infer significant threats for the coastal zone in the near future. Full article

(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)

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19 pages, 60917 KiB

Open AccessArticle

Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

by Xukai Zhang, Xuelian Meng, Chunyan Li, Nan Shang, Jiaze Wang, Yaping Xu, Tao Wu and Cliff Mugnier

ISPRS Int. J. Geo-Inf. 2021, 10(10), 665; https://doi.org/10.3390/ijgi10100665 - 01 Oct 2021

Cited by 6 | Viewed by 2271

Abstract

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation. Full article

(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)

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19 pages, 22806 KiB

Open AccessArticle

How Image Acquisition Geometry of UAV Campaigns Affects the Derived Products and Their Accuracy in Areas with Complex Geomorphology

by Aggeliki Kyriou, Konstantinos Nikolakopoulos and Ioannis Koukouvelas

ISPRS Int. J. Geo-Inf. 2021, 10(6), 408; https://doi.org/10.3390/ijgi10060408 - 13 Jun 2021

Cited by 24 | Viewed by 3828

Abstract

The detailed and accurate mapping of landscapes and their geomorphological characteristics is a key issue in hazard management. The current study examines whether the image acquisition geometry of unmanned aerial vehicle (UAV) campaigns affects the accuracy of the derived products, i.e., orthophotos, digital surface models (DSMs) and photogrammetric point clouds, while performing a detailed geomorphological mapping of a landslide area. UAV flights were executed and the collected imagery was organized into three subcategories based on the viewing angle of the UAV camera. The first subcategory consists of the nadir imagery, the second is composed of the oblique imagery and the third category blends both nadir and oblique imagery. UAV imagery processing was carried out using structure-from-motion photogrammetry (SfM). High-resolution products were generated, consisting of orthophotos, DSMs and photogrammetric-based point clouds. Their accuracy was evaluated utilizing statistical approaches such as the estimation of the root mean square error (RMSE), calculation of the geometric mean of a feature, length measurement, calculation of cloud-to-cloud distances as well as qualitive criteria. All the quantitative and qualitative results were taken into account for the impact assessment. It was demonstrated that the oblique-viewing geometry as well as the combination of nadir and oblique imagery could be used effectively for geomorphological mapping in areas with complex topography and steep slopes that overpass 60 degrees. Moreover, the accuracy assessment revealed that those acquisition geometries contribute to the creation of significantly better products compared to the corresponding one arising from nadir-viewing imagery. Full article

(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)

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23 pages, 9228 KiB

Open AccessArticle

Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

by Simoni Alexiou, Georgios Deligiannakis, Aggelos Pallikarakis, Ioannis Papanikolaou, Emmanouil Psomiadis and Klaus Reicherter

ISPRS Int. J. Geo-Inf. 2021, 10(6), 367; https://doi.org/10.3390/ijgi10060367 - 29 May 2021

Cited by 20 | Viewed by 5514

Abstract

Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments. Full article

(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)

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22 pages, 5627 KiB

Open AccessArticle

Spatiotemporal Dynamics of Suspended Sediments in the Negro River, Amazon Basin, from In Situ and Sentinel-2 Remote Sensing Data

by Rogério Ribeiro Marinho, Tristan Harmel, Jean-Michel Martinez and Naziano Pantoja Filizola Junior

ISPRS Int. J. Geo-Inf. 2021, 10(2), 86; https://doi.org/10.3390/ijgi10020086 - 19 Feb 2021

Cited by 25 | Viewed by 4026

Abstract

Monitoring suspended sediments through remote sensing data in black-water rivers is a challenge. Herein, remote sensing reflectance (R_rs) from in situ measurements and Sentinel-2 Multi-Spectral Instrument (MSI) images were used to estimate the suspended sediment concentration (SSC) in the largest black-water river of the Amazon basin. The Negro River exhibits extremely low R_rs values (<0.005 sr⁻¹ at visible and near-infrared bands) due to the elevated absorption of coloured dissolved organic matter (aCDOM at 440 nm > 7 m⁻¹) caused by the high amount of dissolved organic carbon (DOC > 7 mg L⁻¹) and low SSC (<5 mg L⁻¹). Interannual variability of R_rs is primarily controlled by the input of suspended sediments from the Branco River, which is a clear water river that governs the changes in the apparent optical properties of the Negro River, even at distances that are greater than 90 km from its mouth. Better results were obtained using the Sentinel-2 MSI Red band (Band 4 at 665 nm) in order to estimate the SSC, with an R² value greater than 0.85 and an error less than 20% in the adjusted models. The magnitudes of water reflectance in the Sentinel-2 MSI Red band were consistent with in situ R_rs measurements, indicating the large spatial variability of the lower SSC values (0 to 15 mg L⁻¹) in a complex anabranching reach of the Negro River. The in situ and satellite data analysed in this study indicates sedimentation processes in the lower Negro River near the Amazon River. The results suggest that the radiometric characteristics of sensors, like sentinel-2 MSI, are suitable for monitoring the suspended sediment concentration in large tropical black-water rivers. Full article

(This article belongs to the Special Issue GIS and Remote Sensing Applications in Geomorphology)

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