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21 pages, 27265 KiB

Open AccessArticle

Gradiometry Processing Techniques for Large-Scale of Aeromagnetic Data for Structural and Mining Implications: The Case Study of Bou Azzer Inlier, Central Anti-Atlas, Morocco

by Ayoub Soulaimani, Saïd Chakiri, Saâd Soulaimani, Zohra Bejjaji, Abdelhalim Miftah and Ahmed Manar

Appl. Sci. 2023, 13(17), 9962; https://doi.org/10.3390/app13179962 - 04 Sep 2023

Viewed by 948

Abstract

Due to its unique geographic and tectonic location, the Bou Azzer inlier has drawn increased interest in mining studies. The inlier’s basement structure remains subject to investigation meanwhile faults and igneous rocks affect the local geology. In order to comprehend the Bou Azzer [...] Read more.

Due to its unique geographic and tectonic location, the Bou Azzer inlier has drawn increased interest in mining studies. The inlier’s basement structure remains subject to investigation meanwhile faults and igneous rocks affect the local geology. In order to comprehend the Bou Azzer inlier’s structure, we use aeromagnetic data. The edge enhancement method described in this work is based on the gradiometry tensor analysis (GTA) of aeromagnetic data, which yields estimated magnetic tensors, rotational invariants, horizontal invariants, computed strike lines, and Eigensystems. This study’s primary objective is to use GTA to define structural boundaries in complicated geological and tectonic environments. The vertical and horizontal positions of the geological border’s limits have been determined via analysis of the acquired answers. The borders of the anomalous sources are marked in space by the lowest eigenvalue. According to the research, the inlier demonstrates potential for further mineralization with regard to its complicated structure, which is mostly dominated by WNW-ESE, ENE-WSW, NE-SW and E-W trending lineaments with varying depths between 3.45 and 9.06 km. Certainly, the derived structural scheme has enabled the identification of various formations that may be favorable for the circulation of mineralizing fluids, facilitating the concentration of economically valuable mineral deposits, similar to existing metal reserves in the examined area. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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11 pages, 8103 KiB

Open AccessArticle

Multi-Classifier Pipeline for Olive Groves Detection

by Priscilla Indira Osa, Anne-Laure Beck, Louis Kleverman and Antoine Mangin

Appl. Sci. 2023, 13(1), 420; https://doi.org/10.3390/app13010420 - 29 Dec 2022

Cited by 1 | Viewed by 1307

Abstract

Pixel-based classification is a complex but well-known process widely used for satellite imagery classification. This paper presents a supervised multi-classifier pipeline that combined multiple Earth Observation (EO) data and different classification approaches to improve specific land cover type identification. The multi-classifier pipeline was [...] Read more.

Pixel-based classification is a complex but well-known process widely used for satellite imagery classification. This paper presents a supervised multi-classifier pipeline that combined multiple Earth Observation (EO) data and different classification approaches to improve specific land cover type identification. The multi-classifier pipeline was tested and applied within the SCO-Live project that aims to use olive tree phenological evolution as a bio-indicator to monitor climate change. To detect and monitor olive trees, we classify satellite images to precisely locate the various olive groves. For that first step we designed a multi-classifier pipeline by the concatenation of a first classifier which uses a temporal Random-Forest model, providing an overall classification, and a second classifier which uses the result from the first classification. IOTA2 process was used in the first classifier, and we compared Multi-layer Perceptron (MLP) and One-class Support Vector Machine (OCSVM) for the second. The multi-classifier pipelines managed to reduce the false positive (FP) rate by approximately 40% using the combination RF/MLP while the RF/OCSVM combination lowered the FP rate by around 13%. Both approaches slightly raised the true positive rate reaching 83.5% and 87.1% for RF/MLP and RF/OCSVM, respectively. The overall results indicated that the combination of two classifiers pipeline improves the performance on detecting the olive groves compared to pipeline using only one classifier. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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25 pages, 3404 KiB

Open AccessArticle

A Scalable Earth Observation Service to Map Land Cover in Geomorphological Complex Areas beyond the Dynamic World: An Application in Aosta Valley (NW Italy)

by Tommaso Orusa, Duke Cammareri and Enrico Borgogno Mondino

Appl. Sci. 2023, 13(1), 390; https://doi.org/10.3390/app13010390 - 28 Dec 2022

Cited by 19 | Viewed by 2311

Abstract

Earth Observation services guarantee continuous land cover mapping and are becoming of great interest worldwide. The Google Earth Engine Dynamic World represents a planetary example. This work aims to develop a land cover mapping service in geomorphological complex areas in the Aosta Valley [...] Read more.

Earth Observation services guarantee continuous land cover mapping and are becoming of great interest worldwide. The Google Earth Engine Dynamic World represents a planetary example. This work aims to develop a land cover mapping service in geomorphological complex areas in the Aosta Valley in NW Italy, according to the newest European EAGLE legend starting in the year 2020. Sentinel-2 data were processed in the Google Earth Engine, particularly the summer yearly median composite for each band and their standard deviation with multispectral indexes, which were used to perform a k-nearest neighbor classification. To better map some classes, a minimum distance classification involving NDVI and NDRE yearly filtered and regularized stacks were computed to map the agronomical classes. Furthermore, SAR Sentinel-1 SLC data were processed in the SNAP to map urban and water surfaces to improve optical classification. Additionally, deep learning and GIS updated datasets involving urban components were adopted beginning with an aerial orthophoto. GNSS ground truth data were used to define the training and the validation sets. In order to test the effectiveness of the implemented service and its methodology, the overall accuracy was compared to other approaches. A mixed hierarchical approach represented the best solution to effectively map geomorphological complex areas to overcome the remote sensing limitations. In conclusion, this service may help in the implementation of European and local policies concerning land cover surveys both at high spatial and temporal resolutions, empowering the technological transfer in alpine realities. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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16 pages, 6864 KiB

Open AccessArticle

Vertical Electrical Sounding (VES) Technique to Map Potential Aquifers of the Guigou Plain (Middle Atlas, Morocco): Hydrogeological Implications

by Said El Makrini, Mustapha Boualoul, Younes Mamouch, Hassane El Makrini, Abdelhamid Allaoui, Giovanni Randazzo, Allal Roubil, Mohammed El Hafyani, Stefania Lanza and Anselme Muzirafuti

Appl. Sci. 2022, 12(24), 12829; https://doi.org/10.3390/app122412829 - 14 Dec 2022

Cited by 8 | Viewed by 3179

Abstract

Vertical electrical sounding (VES) as a geoelectrical method has proven its effectiveness throughout the history of groundwater geophysical investigation. In this sense, VES was carried out 47 in the study area with the aim of determining the geometry and limits of Quaternary basaltic [...] Read more.

Vertical electrical sounding (VES) as a geoelectrical method has proven its effectiveness throughout the history of groundwater geophysical investigation. In this sense, VES was carried out 47 in the study area with the aim of determining the geometry and limits of Quaternary basaltic aquifer formations and, above all, the location of electrical discontinuities in the area located in the north of Morocco, between the center of Almis Guigou and the city of Timahdite. This area is experiencing an overexploitation of the groundwater due to excessive pumping and the development of intensive agriculture activities, resulting in a continuous decrease in piezometric levels. The processing of the diagrams by WINSEV software showed the presence of an electrically resistant surface level, attributed to basaltic formations, of the Quaternary age, whose thicknesses reach at least 150 m to the SW of the area. This level is superimposed on a moderately conductive horizon which, according to local geology, corresponds to Pliocene marl and limestone alternations. The correlation of VES interpretation models allowed us to elaborate thematic maps and geoelectrical sections which illustrate the vertical and lateral extension of the basaltic reservoir as well as its thickness, which decreases in general from the south-west to the north-east; however, the main electrical discontinuities also correspond to faults and fractures, and they show a NE–SW direction sub-parallel to the major accidents of the Middle Atlas. A prospectivity map of the local aquifer was generated, coinciding with regional fault lines and confirmed by the alignment of very good flowing water boreholes. This geophysical study by electrical sounding shed light on the geometry and extension of the aquifer and opened avenues to draw further conclusions on its physical and hydrodynamic characteristics, as well as to optimize the future siting of groundwater exploitation boreholes through the elaboration of the local aquifer prospectivity map. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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13 pages, 11521 KiB

Open AccessArticle

The Geomorphological and Geological Structure of the Samaria Gorge, Crete, Greece—Geological Models Comprehensive Review and the Link with the Geomorphological Evolution

by Emmanouil Manoutsoglou, Ilias Lazos, Emmanouil Steiakakis and Antonios Vafeidis

Appl. Sci. 2022, 12(20), 10670; https://doi.org/10.3390/app122010670 - 21 Oct 2022

Cited by 12 | Viewed by 2484

Abstract

The Samaria Gorge is a dominant geomorphological and geological structure on Crete Island and it is one of the national parks established in Greece. Due to the complex tectonics and the stratigraphic ambiguities imprinted in the geological formations of the area, a comprehensive [...] Read more.

The Samaria Gorge is a dominant geomorphological and geological structure on Crete Island and it is one of the national parks established in Greece. Due to the complex tectonics and the stratigraphic ambiguities imprinted in the geological formations of the area, a comprehensive review of the geological models referring to the geological evolution of the area is essential in order to clarify its geomorphological evolution. In particular, the study area is geologically structured by the Gigilos formation, the Plattenkalk series and the Trypali unit. Regarding lithology, the Gigilos formation predominantly includes phyllites and slates, while the Plattenkalk series and the Trypali unit are mainly structured by metacarbonate rocks; the Plattenkalk series metacarbonate rocks include cherts, while the corresponding ones of the Trypali unit do not. Furthermore, the wider region was subjected to compressional tectonics, resulting in folding occurrences and intense faulting, accompanied by high dip angles of the formations, causing similar differentiations in the relief. Significant lithological differentiations are documented among them, which are further analyzed in relation to stratigraphy, the tectonics, and the erosion rate that changes, due to differentiations of the lithological composition. In addition, the existing hydrological conditions are decisive for further geomorphological evolution. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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15 pages, 5114 KiB

Open AccessArticle

The Influence of Flight Direction and Camera Orientation on the Quality Products of UAV-Based SfM-Photogrammetry

by Shaker Ahmed, Adel El-Shazly, Fanar Abed and Wael Ahmed

Appl. Sci. 2022, 12(20), 10492; https://doi.org/10.3390/app122010492 - 18 Oct 2022

Cited by 3 | Viewed by 1610

Abstract

Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This [...] Read more.

Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This is especially true when using low-cost UAV systems equipped with GNSS receivers for navigation. In this study, the influence of UAV flight direction and camera orientation on positioning accuracy in an urban area on the west bank of the Euphrates river in Iraq was investigated. Positioning accuracy was tested in this study with different flight directions and camera orientation settings using a UAV autopilot app (Pix4Dcapture software (Ver. 4.11.0)). The different combinations of these two main parameters (camera orientation and flight direction) resulted in 11 different flight cases for which individual planimetric and vertical accuracies were evaluated. Eleven flight sets of dense point clouds, DEMs, and ortho-imagery were created in this way to compare the achieved positional accuracies. One set was created using the direct georeferencing method (without using GCPs), while the other ten sets were created using the indirect georeferencing approach based on ground truth measurements of five artificially created GCPs. Positional accuracy was found to vary depending on the user-defined flight plan settings, despite an approximately constant flight altitude. However, it was found that the horizontal accuracy achieved was better than the vertical accuracy for all flight sets. This study revealed that combining multiple sets of images with different flight directions and camera orientations can significantly improve the overall positional accuracy to reach several centimeters. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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21 pages, 11934 KiB

Open AccessArticle

Spatiotemporal Variation of Land Surface Temperature Retrieved from FY-3D MERSI-II Data in Pakistan

by Bilawal Abbasi, Zhihao Qin, Wenhui Du, Jinlong Fan, Shifeng Li and Chunliang Zhao

Appl. Sci. 2022, 12(20), 10458; https://doi.org/10.3390/app122010458 - 17 Oct 2022

Cited by 2 | Viewed by 1454

Abstract

The concept of land surface temperature (LST) encompasses both surface energy balance and land surface activities. The study of climate change greatly benefits from an understanding of the geographical and temporal fluctuations of LST. In this study, we utilized an improved version of [...] Read more.

The concept of land surface temperature (LST) encompasses both surface energy balance and land surface activities. The study of climate change greatly benefits from an understanding of the geographical and temporal fluctuations of LST. In this study, we utilized an improved version of the TFSW algorithm to retrieve the LST from the Medium resolution spectral imager II (MERSI-II) data for the first time in Pakistan. MERSI-II is a payload for the Chinese meteorological satellite Fengyun 3D (FY-3D), and it has the capability for use in various remote sensing applications such as climate change and drought monitoring, with higher spatial and temporal resolutions. Once the LSTs were retrieved, accuracy of the LSTs were investigated. Later, LST datasets were used to detect the spatiotemporal variations of LST in Pakistan. Monthly, seasonal, and annual datasets were utilized to detect increasing and decreasing LST trends in the regions, with Mann–Kendall and Sen’s slope estimator tool. In addition, we further revealed the long-term spatiotemporal variations of LST by utilizing Moderate Resolution Imaging Spectrometer (MODIS) LST observations. The cross-validation analysis shows that the retrieved LST of MERSI-II was more consistent with the MODIS MYD11A1 LST product compared to the MYD21A1. The spatial distribution of LSTs demonstrates that the mean LST exhibits a pattern of spatial variability, with high values in the southern areas and low values in the northern areas; there are areas that do not follow this trend, possibly due to reasons of elevation and types of land cover also influencing the LST’s spatial distribution. The annual mean LST trend increases in the northern regions and decreases in the southern regions, ranging between −0.013 and 0.019 °C/year. The trend of long-term analysis were also consistent with MERSI-II, excepting region II, with increasing effects. This study will be helpful for various environmental and climate change studies. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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14 pages, 10455 KiB

Open AccessArticle

Enhancing 3D Reconstruction Model by Deep Learning and Its Application in Building Damage Assessment after Earthquake

by Zhonghua Hong, Yahui Yang, Jun Liu, Shenlu Jiang, Haiyan Pan, Ruyan Zhou, Yun Zhang, Yanling Han, Jing Wang, Shuhu Yang and Changyue Zhong

Appl. Sci. 2022, 12(19), 9790; https://doi.org/10.3390/app12199790 - 28 Sep 2022

Cited by 4 | Viewed by 2160

Abstract

A timely and accurate damage assessment of buildings after an earthquake is critical for the safety of people and property. Most of the existing methods based on classification and segmentation use two-dimensional information to determine the damage level of the buildings, which cannot [...] Read more.

A timely and accurate damage assessment of buildings after an earthquake is critical for the safety of people and property. Most of the existing methods based on classification and segmentation use two-dimensional information to determine the damage level of the buildings, which cannot provide the multi-view information of the damaged building, resulting in inaccurate assessment results. According to the knowledge of the authors, there is no related research using the deep-learning-based 3D reconstruction method for the evaluation of building damage. In this paper, we first applied the deep-learning-based MVS model to reconstruct the 3D model of the buildings after an earthquake using multi-view UAV images, to assist the building damage assessment task. The method contains three main steps. Firstly, the camera parameters are calculated. Then, 3D reconstruction is conducted based on CasMVSNet. Finally, a building damage assessment is performed based on the 3D reconstruction result. To evaluate the effectiveness of the proposed method, the method was tested in multi-view UAV aerial images of Yangbi County, Yunnan Province. The results indicate that: (1) the time efficiency of CasMVSNet is significantly higher than that of other deep learning models, which can meet the timeliness requirement of post-earthquake rescue and damage assessment. In addition, the memory consumption of CasMVSNet is the lowest; (2) CasMVSNet exhibits the best 3D reconstruction result in both high and small buildings; (3) the proposed method can provide detail and multi-view information of damaged buildings, which can be used to assist the building damage assessment task. The results of the building damage assessment are very similar to the results of the field survey. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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19 pages, 8227 KiB

Open AccessArticle

A Classification Feature Optimization Method for Remote Sensing Imagery Based on Fisher Score and mRMR

by Chengzhe Lv, Yuefeng Lu, Miao Lu, Xinyi Feng, Huadan Fan, Changqing Xu and Lei Xu

Appl. Sci. 2022, 12(17), 8845; https://doi.org/10.3390/app12178845 - 02 Sep 2022

Cited by 4 | Viewed by 1712

Abstract

In object-oriented remote sensing image classification experiments, the dimension of the feature space is often high, leading to the “dimension disaster”. If a reasonable feature selection method is adopted, the classification efficiency and accuracy of the classifier can be improved. In this study, [...] Read more.

In object-oriented remote sensing image classification experiments, the dimension of the feature space is often high, leading to the “dimension disaster”. If a reasonable feature selection method is adopted, the classification efficiency and accuracy of the classifier can be improved. In this study, we took GF-2 remote sensing imagery as the research object and proposed a feature dimension reduction algorithm combining the Fisher Score and the minimum redundancy maximum relevance (mRMR) feature selection method. First, the Fisher Score was used to construct a feature index importance ranking, following which the mRMR algorithm was used to select the features with the maximum correlation and minimum redundancy between categories. The feature set was optimized using this method, and remote sensing images were automatically classified based on the optimized feature subset. Experimental analysis demonstrates that, compared with the traditional mRMR, Fisher Score, and ReliefF methods, the proposed Fisher Score–mRMR (Fm) method provides higher accuracy in remote sensing image classification. In terms of classification accuracy, the accuracy of the Fm feature selection method with RT and KNN classifiers is improved compared with that of single feature selection method, reaching 95.18% and 96.14%, respectively, and the kappa coefficient reaches 0.939 and 0.951, respectively. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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17 pages, 3960 KiB

Open AccessArticle

Hydro Statistical Assessment of TRMM and GPM Precipitation Products against Ground Precipitation over a Mediterranean Mountainous Watershed (in the Moroccan High Atlas)

by Myriam Benkirane, Nour-Eddine Laftouhi, Saïd Khabba and África de la Hera-Portillo

Appl. Sci. 2022, 12(16), 8309; https://doi.org/10.3390/app12168309 - 19 Aug 2022

Cited by 2 | Viewed by 1423

Abstract

The tropical Rainfall Measuring Mission TRMM 3B42 V7 product and its successor, the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM IMERG high-resolution product GPM IMERG V5, have been validated against rain gauges precipitation in an arid mountainous basin where ground-based observations of [...] Read more.

The tropical Rainfall Measuring Mission TRMM 3B42 V7 product and its successor, the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM IMERG high-resolution product GPM IMERG V5, have been validated against rain gauges precipitation in an arid mountainous basin where ground-based observations of precipitation are sparse, or spatially undistributed. This paper aims to evaluate hydro-statically the performances of the TRMM 3B42 V7 and GPM IMERG V05 satellite precipitations products SPPs, at multiple temporal scales, from 2014 to 2017. SPPs are compared with the gauge station and show good results for both statistical and contingency metrics with notable values R > 0.94. Moreover, the rainfall-runoff events implemented on the hydrological model were performed at 3-hourly time steps and showed satisfactory results based on the obtained Nash–Sutcliffe criteria ranging from 94.50% to 57.50%, and from 89.3% to 51.2%, respectively. The TRMM product tends to underestimate and not capture extreme precipitation events. In contrast, the GPM product can identify the variability of precipitation at small time steps, although a slight underestimation in the detection of extreme events can be corrected during the validation steps. The proposed method is an interesting approach for solving the problem of insufficient observed data in the Mediterranean regions. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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34 pages, 13785 KiB

Open AccessArticle

Morphology of Dome- and Tepee-Like Landforms Generated by Expansive Hydration of Weathering Anhydrite: A Case Study at Dingwall, Nova Scotia, Canada

by Adrian Jarzyna, Maciej Bąbel, Damian Ługowski and Firouz Vladi

Appl. Sci. 2022, 12(15), 7374; https://doi.org/10.3390/app12157374 - 22 Jul 2022

Cited by 2 | Viewed by 1533

Abstract

The gypsum-anhydrite rocks in the abandoned quarry at Dingwall (Nova Scotia, Canada) are subjected to physical and chemical weathering, including hydration of the anhydrite, i.e., its transformation into secondary gypsum under the influence of water. This process is known to lead to the [...] Read more.

The gypsum-anhydrite rocks in the abandoned quarry at Dingwall (Nova Scotia, Canada) are subjected to physical and chemical weathering, including hydration of the anhydrite, i.e., its transformation into secondary gypsum under the influence of water. This process is known to lead to the localized volume increase of the rock and the formation of spectacular hydration landforms: domes, tepees and ridges. Cavities appearing in the interior of these domes are often unique hydration caves (Quellungshöhlen in German). For the first time, this paper gives detailed geomorphometric characteristics of the 77 dome- and tepee-like hydration landforms growing today at Dingwall based on their digital surface models and orthophotomaps, made with the method of photogrammetry integrated with direct measurements. The length of hydration landforms varies from 1.86 to 23.05 m and the relative height varies from 0.33 to 2.09 m. Their approximate shape in a plan view varies from nearly circular, through oval, to elongated with a length-to-width ratio rarely exceeding 5:2. Length, width and relative height are characterized by moderate mutual correlation with proportional relations expressed by linear equations, testifying that the hydration landforms generally preserve the same or very similar shape independent of their sizes. The averaged thickness of the detached rock layer ranges from 6 to 46 cm. The size of the forms seems to depend on this thickness—the forms larger in extent (longer) generally have a thicker detached rock layer. Master (and other) joints and, to a lesser extent, layering in the bedrock influence the development of hydration landforms, particularly by controlling the place where the entrances are open to internal cavities or caves. Three structural types of the bedrock influencing the growth of hydration forms were recognized: with master joints, with layering and with both of them. The latter type of bedrock has the most complex impact on the morphology of hydration landforms because it depends on the number of master joint sets and the mutual orientation of joints and layering, which are changeable across the quarry. The durability of the hydration forms over time depends, among others, on the density of fractures in the detached rock layer. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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25 pages, 4149 KiB

Open AccessArticle

Characterisation of Coastal Sediment Properties from Spectral Reflectance Data

by Jasper Knight and Mohamed A. M. Abd Elbasit

Appl. Sci. 2022, 12(13), 6826; https://doi.org/10.3390/app12136826 - 05 Jul 2022

Cited by 2 | Viewed by 2371

Abstract

Remote sensing of coastal sediments for the purpose of automated mapping of their physical properties (grain size, mineralogy and carbonate content) across space has not been widely applied globally or in South Africa. This paper describes a baseline study towards achieving this aim [...] Read more.

Remote sensing of coastal sediments for the purpose of automated mapping of their physical properties (grain size, mineralogy and carbonate content) across space has not been widely applied globally or in South Africa. This paper describes a baseline study towards achieving this aim by examining the spectral reflectance signatures of field sediment samples from a beach–dune system at Oyster Bay, Eastern Cape, South Africa. Laboratory measurements of grain size and carbonate content of field samples (n = 134) were compared to laboratory measurements of the spectral signature of these samples using an analytical spectral device (ASD), and the results interrogated using different statistical methods. These results show that the proportion of fine sand, CaCO₃ content and the distributional range of sediment grain sizes within a sample (here termed span) are the parameters with greatest statistical significance—and thus greatest potential interpretive value—with respect to their spectral signatures measured by the ASD. These parameters are also statistically associated with specific wavebands in the visible and near infrared, and the shortwave infrared parts of the spectrum. These results show the potential of spectral reflectance data for discriminating elements of grain size properties of coastal sediments, and thus can provide the baseline towards achieving automated spatial mapping of sediment properties across coastal beach–dune environments using hyperspectral remote sensing techniques. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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24 pages, 5754 KiB

Open AccessArticle

The Influence of the Quality of Digital Elevation Data on the Modelling of Terrain Vehicle Movement

by Marian Rybansky and Josef Rada

Appl. Sci. 2022, 12(12), 6178; https://doi.org/10.3390/app12126178 - 17 Jun 2022

Cited by 1 | Viewed by 1433

Abstract

This study investigated digital terrain models and options for their evaluation and effective usage. The most important result of this study was the introduction of the slope reduction method for low-detail elevation models. It enabled accurate results of passability analyses by performing adjustments [...] Read more.

This study investigated digital terrain models and options for their evaluation and effective usage. The most important result of this study was the introduction of the slope reduction method for low-detail elevation models. It enabled accurate results of passability analyses by performing adjustments of slopes. In addition, the goal was to determine the strengths and weaknesses of selected data for use in cross-country mobility analyses, followed by recommendations on how to use these databases efficiently to obtain accurate results. The selection of elevation databases (1 m, 5 m, 10 m, 30 m) was determined by the focus of data development projects of NATO and current scientific research projects of the Ministry of Defence of the Czech Republic. Key findings showed potential for use in practise for all tested elevation models. Efficient usage of low-detail models in CCM analyses is limited; nevertheless, they can be augmented with additional vector data or automated remote-sensing technologies. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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13 pages, 3696 KiB

Open AccessArticle

An Algorithm to Generate a Weighted Network Voronoi Diagram Based on Improved PCNN

by Xiaomin Lu and Haowen Yan

Appl. Sci. 2022, 12(12), 6011; https://doi.org/10.3390/app12126011 - 13 Jun 2022

Viewed by 1713

Abstract

The network Voronoi diagram has been extensively applied in many fields, such as influence area construction, location selection and urban planning, owing to its high accuracy and validity in space division. Taking advantage of parallel processing and auto-wave division of the pulse coupled [...] Read more.

The network Voronoi diagram has been extensively applied in many fields, such as influence area construction, location selection and urban planning, owing to its high accuracy and validity in space division. Taking advantage of parallel processing and auto-wave division of the pulse coupled neural network (PCNN), an algorithm for generating a weighted network Voronoi diagram is proposed in this paper. First, in order to better accommodate the scenes of urban facility points and road networks, the PCNN is improved. Second, the speed of the auto-wave in the improved PCNN is calculated by the weights of the facility points and the attributes of the related road network. Third, the nodes in the road network are considered as neurons, the facility points are projected onto the nearest road segments and the projected points are treated as initial neurons. The initial neurons generate auto-waves simultaneously, and the auto-waves transmit along the shortest path from neurons to other neurons with the calculated speed until all the neurons are fired. During this procedure, the road network and the corresponding space are assigned to the initial neurons and the weighted network Voronoi diagram is constructed. The experiments on the specific region with the real POIs present the feasibility, applicability and efficiency of the algorithm. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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14 pages, 3832 KiB

Open AccessArticle

Determination of Forest Structure from Remote Sensing Data for Modeling the Navigation of Rescue Vehicles

by Marian Rybansky

Appl. Sci. 2022, 12(8), 3939; https://doi.org/10.3390/app12083939 - 13 Apr 2022

Cited by 9 | Viewed by 1572

Abstract

One of the primary purposes of forest fire research is to predict crisis situations and, also, to optimize rescue operations during forest fires. The research results presented in this paper provide a model of Cross-Country Mobility (CCM) of fire brigades in forest areas [...] Read more.

One of the primary purposes of forest fire research is to predict crisis situations and, also, to optimize rescue operations during forest fires. The research results presented in this paper provide a model of Cross-Country Mobility (CCM) of fire brigades in forest areas before or during a fire. In order to develop a methodology of rescue vehicle mobility in a wooded area, the structure of a forest must first be determined. We used a Digital Surface Model (DSM) and Digital Elevation Model (DEM) to determine the Canopy Height Model (CHM). DSM and DEM data were scanned by LiDAR. CHM data and field measurements were used for determining the approximate forest structure (tree height, stem diameters, and stem spacing between trees). Due to updating the CHM and determining the above-mentioned forest structure parameters, tree growth equations and vegetation growth curves were used. The approximate forest structure with calculated tree density (stem spacing) was used for modeling vehicle maneuvers between the trees. Stem diameter data were used in cases where it was easier for the vehicle to override the trees rather than maneuver between them. Although the results of this research are dependent on the density and quality of the input LiDAR data, the designed methodology can be used for modeling the optimal paths of rescue vehicles across a wooded area during forest fires. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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Review

Jump to: Research

22 pages, 8198 KiB

Open AccessReview

Reconstruction of Land and Marine Features by Seismic and Surface Geomorphology Techniques

by Dicky Harishidayat, Abdullatif Al-Shuhail, Giovanni Randazzo, Stefania Lanza and Anselme Muzirafuti

Appl. Sci. 2022, 12(19), 9611; https://doi.org/10.3390/app12199611 - 24 Sep 2022

Cited by 7 | Viewed by 2601

Abstract

Seismic reflection utilizes sound waves transmitted into the subsurface, reflected at rock boundaries, and recorded at the surface. Interpretation of their travel times and amplitudes are the key for reconstructing various geomorphological features across geological time (e.g., reefs, dunes, and channels). Furthermore, the [...] Read more.

Seismic reflection utilizes sound waves transmitted into the subsurface, reflected at rock boundaries, and recorded at the surface. Interpretation of their travel times and amplitudes are the key for reconstructing various geomorphological features across geological time (e.g., reefs, dunes, and channels). Furthermore, the integration of surface geomorphology technique mapping, such as digital elevation models, with seismic geomorphology can increase land and marine feature modelling and reduce data uncertainty, as well. This paper presents an overview of seismic and surface geomorphology techniques and proposes an integrated workflow for better geological mapping, 3D surface imaging, and reconstruction. We intend to identify which techniques are more often used and which approaches are more appropriate for better output results. We noticed that an integration of surface and subsurface geomorphology techniques could be beneficial for society in landscape mapping, reservoir characterization, and city/regional planning. Full article

(This article belongs to the Special Issue Geomorphology in the Digital Era)

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