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Remote Sensing for Geomorphological Mapping

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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 (30 September 2020) | Viewed by 30404

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Prof. Dr. Ulrich Kamp

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Earth and Environment Discipline, Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Rd., 211 Science Faculty Center, Dearborn, MI 48128, USA
Interests: cryosphere; environmental change; environmental hazards; human-environment interactions; mountain geography; quaternary geology
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Dear Colleagues,

The Earth’s surface is the interface where lithosphere, atmosphere, hydrosphere, biosphere, and humansphere meet. Geomorphology, “the study of the Earth’s form”, is an exciting field that is concerned with this surface. It sits at the intersection of disciplines such as geology, hydrology, climatology, pedology, biology, ecology, environmental sciences and studies, social sciences, economics, and others. Natural and anthropogenic hazards like landslides, hurricanes, and dam failures mainly affect the Earth’s thin skin. Hence, knowledge about landscapes and landforms, geomorphological processes, and their evolution is essential in planning for improved humanscapes.

The first steps in understanding geomorphologic features are detecting and mapping them, followed by scientific analysis and interpretation. Today, geographical information science tools, i.e., remote sensing and geographic information systems, represent the standard approach in geomorphological mapping that—like the technologies themselves—is advancing rapidly. New satellite sensors deliver increasingly detailed spatial, multispectral and multitemporal information, and unmanned aerial systems (UAVs) allow for inexpensive ad hoc missions.

This Special Issue aims to collect contributions that represent the frontier in geomorphological mapping as a geospatial analysis tool without any restriction to the diversity of ideas and experiences. It aims to portray new techniques, methodologies, and applications. Both qualitative and quantitative approaches are of interest.

Prof. Dr. Ulrich Kamp
Guest Editor

Manuscript Submission Information

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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 2700 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
mapping
remote sensing

Published Papers (7 papers)

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Research

28 pages, 13535 KiB

Open AccessArticle

Non-Invasive Methodological Approach to Detect and Characterize High-Risk Sinkholes in Urban Cover Evaporite Karst: Integrated Reflection Seismics, PS-InSAR, Leveling, 3D-GPR and Ancillary Data. A NE Italian Case Study

by Alice Busetti, Chiara Calligaris, Emanuele Forte, Giulia Areggi, Arianna Mocnik and Luca Zini

Remote Sens. 2020, 12(22), 3814; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12223814 - 20 Nov 2020

Cited by 15 | Viewed by 2825

Abstract

Sinkholes linked to cover evaporite karst in urban environments still represent a challenge in terms of their clear identification and mapping considering the rehash and man-made structures. In the present research, we have proposed and tested a methodology to identify the subsiding features through an integrated and non-invasive multi-scale approach combining seismic reflection, PS-InSAR (PSI), leveling and full 3D Ground Penetrating Radar (GPR), and thus overpassing the limits of each method. The analysis was conducted in a small village in the Alta Val Tagliamento Valley (Friuli Venezia Giulia region, NE Italy). Here, sinkholes have been reported for a long time as well as the hazards linked to their presence. Within past years, several houses have been demolished and at present many of them are damaged. The PSI investigation allowed the identification of an area with higher vertical velocities; seismic reflection imagined the covered karst bedrock, identifying three depocenters; leveling data presented a downward displacement comparable with PSI results; 3D GPR, applied here for the first time in the study and characterization of sinkholes, defined shallow sinking features. Combining all the obtained results with accurate field observations, we identified and mapped the highest vulnerable zone. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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29 pages, 7949 KiB

Open AccessArticle

Uncertainty and Overfitting in Fluvial Landform Classification Using Laser Scanned Data and Machine Learning: A Comparison of Pixel and Object-Based Approaches

by Zsuzsanna Csatáriné Szabó, Tomáš Mikita, Gábor Négyesi, Orsolya Gyöngyi Varga, Péter Burai, László Takács-Szilágyi and Szilárd Szabó

Remote Sens. 2020, 12(21), 3652; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12213652 - 07 Nov 2020

Cited by 10 | Viewed by 4077

Abstract

Floodplains are valuable scenes of water management and nature conservation. A better understanding of their geomorphological characteristic helps to understand the main processes involved. We performed a classification of floodplain forms in a naturally developed area in Hungary using a Digital Terrain Model (DTM) of aerial laser scanning. We derived 60 geomorphometric variables from the DTM and prepared a geomorphological map of 265 forms (crevasse channels, point bars, swales, levees). Random Forest classification was conducted with Recursive Feature Elimination (RFE) on the objects (mean pixel values by forms) and on the pixels of the variables. We also evaluated the classification probabilities (CP), the spatial uncertainties (SU), and the overfitting in the function of the number of the variables. We found that the object-based method had a better performance (95%) than the pixel-based method (78%). RFE helped to identify the most important 13–20 variables, maintaining the high model performance and reducing the overfitting. However, CP and SU were not efficient measures of classification accuracy as they were not in accordance with the class level accuracy metric. Our results help to understand classification results and the specific limits of laser scanned DTMs. This methodology can be useful in geomorphologic mapping. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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21 pages, 6682 KiB

Open AccessArticle

Riverine Sediment Changes and Channel Pattern of a Gravel-Bed Mountain Torrent

by Gernot Seier, Stefan Schöttl, Andreas Kellerer-Pirklbauer, Raphael Glück, Gerhard K. Lieb, Daniel N. Hofstadler and Wolfgang Sulzer

Remote Sens. 2020, 12(18), 3065; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12183065 - 19 Sep 2020

Cited by 6 | Viewed by 7743

Abstract

The alluvial channel of the Langgriesgraben (Austria) is a highly active geomorphic riverine subcatchment of the Johnsbach River with intermittent discharge and braided river structures. The high sediment yield entails both issues and opportunities. For decades, the riverbed was exploited as a gravel pit. Today, as part of the Gesäuse National Park and after renaturation, the sediment yield endangers a locally important bridge located at the outlet of the subcatchment. High-resolution geospatial investigations are vital for the quantification of sediment redistribution, which is relevant in terms of river management. Based on unmanned aerial system (UAS) surveys in 2015 (July, September, and October) and 2019 (August and October), high-resolution digital elevation models (DEMs) were generated, which enable us to quantify intra- and multiannual sediment changes. As surface runoff at the subcatchment occurs on only a few days per year with flash floods and debris flows that are not predictable and thus hardly observable, the subsurface water conditions were assessed based on electrical resistivity tomography (ERT) measurements, which were conducted in 2019 (November) and 2020 (May, June). Results of the UAS-based surveys showed that, considering the data quality, intra-annual sediment changes affected only small subareas, whereas multiannual changes occurred in the entire study area and amount to net sediment deposition of ≈0.3–0.4 m³m⁻², depending on the channel section. In addition, the elevation differences for both intra-annual surveys revealed linear patterns that can be interpreted as braided river channels. As in both survey periods the same areas were affected by changes, it can be concluded that the channel mainly affected by reshaping persisted within the 4-year observation period. The subsurface investigations showed that although both near-surface and groundwater conditions changed, near-surface sediments are mostly dry with a thickness of several meters during the observations. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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29 pages, 28141 KiB

Open AccessArticle

Combining Satellite Multispectral Imagery and Topographic Data for the Detection and Mapping of Fluvial Avulsion Processes in Lowland Areas

by Giulia Iacobucci, Francesco Troiani, Salvatore Milli, Paolo Mazzanti, Daniela Piacentini, Marta Zocchi and Davide Nadali

Remote Sens. 2020, 12(14), 2243; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12142243 - 13 Jul 2020

Cited by 10 | Viewed by 3901

Abstract

Fluvial avulsion is an important process in the dynamics of the riverscapes and plays a key role in the drainage network evolution in lowland areas, also influencing past and present social processes and economic activities. Crevasse splays represent significant geomorphological features for understanding the fluvial morphodynamics in lowland areas dominated by avulsion processes. Within wide floodplains characterized by very low elevation ranges, the detection and accurate mapping of crevasse splay morphology and features, such as crevasse channels, levees, and deposit, can be very challenging considering floodplain extension, anthropic impact on the natural channels network, logistic difficulties, and in some cases, climate conditions that prevent field work. This research aims at improving the detection and mapping of crevasse splays in lowland areas through the combination of different remote sensing techniques based on optical multispectral imagery and topographic data derived from satellite earth observation missions. The Lower Mesopotamia Plain (LMP) offers a unique opportunity to study the avulsion processes because it presents numerous examples of crevasse splays, characterized by different sizes and states of activity. Furthermore, in this area, a strong correlation exists between the formation and development of crevasse splays and the expansion of agriculture and early societies since the Early Holocene. Different supervised classification (SC) methods of Landsat 8 satellite images have been tested together with topographic analysis of the microrelief, carried out based on two different 1-arcsec DEMs (AW3D30 and GDEM2). The results of this study demonstrate that the combination of multispectral imagery analysis and topographic analysis of the microrelief is useful for discerning different crevasse elements, distinguishing between active and relict landforms. The methodological approach proved helpful for improving the mapping of erosional and depositional landforms generated by the avulsion process and, in the study area, provided the best results for the active landforms. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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31 pages, 34377 KiB

Open AccessArticle

Small Lava Caves as Possible Exploratory Targets on Mars: Analogies Drawn from UAV Imaging of an Icelandic Lava Field

by Lydia Sam, Anshuman Bhardwaj, Shaktiman Singh, F. Javier Martin-Torres, Maria-Paz Zorzano and Juan Antonio Ramírez Luque

Remote Sens. 2020, 12(12), 1970; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12121970 - 19 Jun 2020

Cited by 5 | Viewed by 4842

Abstract

Volcanic-aeolian interactions and processes have played a vital role in landscape evolution on Mars. Martian lava fields and associated caves have extensive geomorphological, astrobiological, and in-situ resource utilization (ISRU) implications for future Mars missions which might be focused on subsurface exploration. Although several possible cave “skylights” of tens to >100 m diameter have been spotted in lava fields of Mars, there is a possibility of prevalence of meter-scale features which are an order of magnitude smaller and difficult to identify but could have vital significance from the scientific and future exploration perspectives. The Icelandic volcanic-aeolian environment and fissure volcanoes can serve as analogs to study lava flow-related small caves such as surface tubes, inflationary caves, liftup caves, and conduits. In the present work, we have tried to explore the usability of unmanned aerial vehicle (UAV)-derived images for characterizing a solidified lava flow and designing a sequential methodology to identify small caves in the lava flow. In the mapped area of ~0.33 km², we were able to identify 81 small cave openings, five lava flow morphologies, and five small cave types using 2 cm/pixel high-resolution images. The results display the usefulness of UAV imaging for such analogous research, and also highlight the possibility of the widespread presence of similar small cave openings in Martian lava fields. Such small openings can facilitate optimal air circulation within the caves while sheltering the insides from physical weathering and harmful radiations. Using the available best resolution remote sensing images, we extend the analogy through the contextual and geomorphological analysis of several possible pit craters in the Tharsis region of Mars, in a region of extremely vesicular and fragile lava crust with pahoehoe-type morphology. We report two possible pit craters in this region, with diameters as small as ~20 m. The possibility that such small cave openings can lead to vast subterranean hollow spaces on Mars cannot be ruled out considering its low gravity. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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25 pages, 9575 KiB

Open AccessArticle

Unpiloted Aerial System (UAS)-Supported Biogeomorphic Analysis of Restored Sierra Nevada Montane Meadows

by Jerry Davis, Leonhard Blesius, Michelle Slocombe, Suzanne Maher, Michael Vasey, Peter Christian and Philip Lynch

Remote Sens. 2020, 12(11), 1828; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12111828 - 05 Jun 2020

Cited by 7 | Viewed by 2808

Abstract

The benefits of meadow restoration can be assessed by understanding the connections among geomorphology, hydrology, and vegetation; and multispectral imagery captured from unpiloted aerial systems (UASs) can provide the best method in terms of cost, resolution, and support for vegetation indices. Our field studies were conducted on northern Sierra montane meadows (with ≤70 km² watershed area). The meadows exist in various stages of ecological restoration. Field survey methods included GPS + laser-leveling channel survey, cross-sections, LiDAR, vegetation sampling, soil measurements, and UAS imaging. A sensor captured calibrated blue (465–485 nm), green (550–570 nm), red (663–673 nm), near infrared (NIR) (820–860 nm), and red-edge (712–722 nm) bands at 5.5 cm resolution (as well as thermal at 81 cm resolution) and provided multispectral images and derivative vegetation indices such as the normalized difference vegetation index (NDVI) and red-edge chlorophyll index (Cl_re). This fine-scale imagery extended our morphometric assessment of post-restoration channel bedform patterns and sinuosity related to Carex-influenced soil properties and Salix influence, and also documented groundwater-related effects via Carex patterns evident from spring snowmelt images, as well as NDVI and Cl_re (derived from spring and summer images) in growing to senescent phenological stages. Carex was significantly associated with low bulk density and high soil moisture, NDVI, and Cl_re in low-lying areas, and channel sinuosity was significantly associated with willow influence. Our methods can be applied by restoration managers to assess where projects are threatened by renewed incision and to document levels of carbon sequestration significant to addressing climate change. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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14 pages, 2782 KiB

Open AccessArticle

Badland Erosion and Its Morphometric Features in the Tropical Monsoon Area

by Ci-Jian Yang, Li-Wei Yeh, Yeuan-Chang Cheng, Chia-Hung Jen and Jiun-Chuan Lin

Remote Sens. 2019, 11(24), 3051; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11243051 - 17 Dec 2019

Cited by 8 | Viewed by 3245

Abstract

Climatically driven processes are important controls on the Earth’s surface and on interactions between the hydrological cycle and erosion in drainage basins. As a result, landscape forms such as hillslope topography can be used as an archive to reconstruct historical climatic conditions. Recent progress in the Structure-from-Motion (SfM) photogrammetric technique allows for the construction of high-resolution, low-cost topography data using remote-controlled unmanned aerial vehicle (UAV) surveys. Here, we present the climatic effects on the hillslope erosion rate that can be obtained from the drainage frequency of hillslopes. We quantify the centimeter-scale accuracy of surveys across 72 badland hillslopes in SE Taiwan, which is a tropical monsoon area with an annual precipitation of over 2 m. Our observations indicate that climatic erosion results in a higher drainage frequency and the number of furrows, instead of drainage density. Additionally, the morphometric slope index (MSI) has a strong positive correlation with erosion and its rate but shows a negative correlation with drainage length and a positive correlation with inclination. This suggests that the erosion pattern is due to gravitational mass wasting instead of hydrological erosion. MSI should always be calculated relying on the normalized slope length and is less applicable to landslide-dominated erosion. We, therefore, suggest that UAV-driven digital elevation models (DEMs) are integrated into erosion mapping to aid in identifying erosion patterns. We highlight the unique opportunity for cross-climate zone comparative studies offered by badland landscapes and differential rainfall patterns, with remote sensing techniques and the morphometric slope index. Full article

(This article belongs to the Special Issue Remote Sensing for Geomorphological Mapping)

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