Journal Description

Geomatics

Geomatics is an international, peer-reviewed, open access journal on geomatic science published quarterly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 19.4 days after submission; acceptance to publication is undertaken in 1.9 days (median values for papers published in this journal in the first half of 2022).
Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Geomatics is a companion journal of Remote Sensing.

Imprint Information Journal Flyer Open Access ISSN: 2673-7418

Latest Articles

Open AccessArticle

Detecting Connectivity and Spread Pathways of Land Use/Cover Change in a Transboundary Basin Based on the Circuit Theory

Blessing Kavhu

Zama Eric Mashimbye

and

Linda Luvuno

Geomatics 2022, 2(4), 518-539; https://doi.org/10.3390/geomatics2040028 - 16 Nov 2022

Abstract

Understanding the spatial spread pathways and connectivity of Land Use/Cover (LULC) change within basins is critical to natural resources management. However, existing studies approach LULC change as distinct patches but ignore the connectivity between them. It is crucial to investigate approaches that can detect the spread pathways of LULC change to aid natural resource management and decision-making. This study aims to evaluate the utility of the Circuit Theory to detect the spread and connectivity of LULC change within the Okavango basin. Patches of LULC change sites that were derived from change detection of LULC based on the Deep Neural Network (DNN) for the period between 2004 and 2020 were used. The changed sites were categorized based on the nature of the change of the classes, namely Category A (natural classes to artificial classes), Category B (artificial classes to natural classes), and Category C (natural classes to natural classes). In order to generate the resistance layer; an ensemble of machine learning algorithms was first calibrated with social-ecological drivers of LULC change and centroids of LULC change patches to determine the susceptibility of the landscape to LULC change. An inverse function was then applied to the susceptibility layer to derive the resistance layer. In order to analyze the connectivity and potential spread pathways of LULC change, the Circuit Theory (CT) model was built for each LULC change category. The CT model was calibrated using the resistance layer and patches of LULC change in Circuitscape 4.0. The corridor validation index was used to evaluate the performance of CT modeling. The use of the CT model calibrated with a resistance layer (derived from susceptibility modeling) successfully established the spread pathways and connectivity of LULC change for all the categories (validation index > 0.60). Novel maps of LULC change spread pathways in the Okavango basin were generated. The spread pathways were found to be concentrated in the northwestern, central, and southern parts of the basin for Category A transitions. As for category B transitions, the spread pathways were mainly concentrated in the northeastern and southern parts of the basin and along the major rivers. While for Category C transitions were found to be spreading from the central towards the southern parts, mainly in areas associated with semi-arid climatic conditions. A total of 186 pinch points (Category A: 57, Category B: 71, Category C: 58) were detected. The pinch points can guide targeted management LULC change through the setting up of conservation areas, forest restoration projects, drought monitoring, and invasive species control programs. This study provides a new decision-making method for targeted LULC change management in transboundary basins. The findings of this study provide insights into underlying processes driving the spread of LULC change and enhanced indicators for the evaluation of LULC spread in complex environments. Such information is crucial to inform land use planning, monitoring, and sustainable natural resource management, particularly water resources. Full article

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Open AccessArticle

Soil Loss Estimation Using Remote Sensing and RUSLE Model in Koromi-Federe Catchment Area of Jos-East LGA, Plateau State, Nigeria

Andrew Ayangeaor Ugese

Jesugbemi Olaoye Ajiboye

Esther Shupel Ibrahim

Efron Nduke Gajere

Atang Itse

and

Halilu Ahmad Shaba

Geomatics 2022, 2(4), 499-517; https://doi.org/10.3390/geomatics2040027 - 12 Nov 2022

Abstract

Soil loss caused by erosion has destroyed landscapes, as well as depositing sterile material on fertile lands and rivers, clogged waterways and accelerated flash floods, declined the populations of fish and other species, and diminish soil fertility. In some places, erosion has also destroyed buildings, caused mudflow, create new landforms, displaced people, and slowed down the economy of the affected community by destroying roads and homes. Erosion is aggravated by climate change and anthropogenic factors such as deforestation, overgrazing, inappropriate methods of tillage, and unsustainable agricultural practices. In this study, remote sensing (RS) and geographic information (GIS) data and tools were used to model erosion and estimate soil loss in the catchment area of Koromi-Federe in Jos East, Plateau State Nigeria which is our study area. Soil loss estimation was performed using the revised universal soil loss equation (RUSLE) model and was computed by substituting the corresponding values of each factor inherent in the equation (rainfall erosivity, soil erodibility, slope steepness and slope length, cover management, and conservation practices) using RS and GIS tools. Soil data was obtained from the study area and analyzed in the laboratory, rainfall data, land cover, digital elevation model (DEM), as well as the management practice of the study area were the parameters computed in spatial analyst tool using map algebra based on RUSLE. The soil loss generated was classified into four classes and the results revealed 95.27% of the catchment with a tolerable loss of less than 10 t/h⁻¹/y⁻¹. At 3.6%, a low or minimal loss of 10–20 t/h⁻¹/y⁻¹, at 1.03% there exists a moderate loss of 20–50 t/h⁻¹/y⁻¹, while there was and critical or high loss of >50 t/h⁻¹/y⁻¹ at 0.12% of the catchment. The result showed that critical soil loss in the catchment area is exacerbated by the influence of the slope length and steepness, and the amount of rainfall received. This poses great concern with annual rainfall projected to increase up to 12% in West Africa. However, our sensitivity analysis revealed that it can be reduced with the effect of vegetated cover and management practices. This is an important finding as it can guide sustainability practices to control erosion and the loss of valuable lands in the region, especially now under climate change. Full article

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Open AccessArticle

Denmark’s Depth Model: Compilation of Bathymetric Data within the Danish Waters

Giuseppe Masetti

Ove Andersen

Nicki R. Andreasen

Philip S. Christiansen

and

Geomatics 2022, 2(4), 486-498; https://doi.org/10.3390/geomatics2040026 - 11 Nov 2022

Abstract

Denmark’s Depth Model (DDM) is a Digital Bathymetric Model based on hundreds of bathymetric survey datasets and historical sources within the Danish Exclusive Economic Zone. The DDM represents the first publicly released model covering the Danish waters with a grid resolution of 50 m. When modern datasets are not available for a given area, historical sources are used, or, as the last resort, interpolation is applied. The model is generated by averaging depths values from validated sources, thus, not targeted for safety of navigation. The model is available by download from the Danish Geodata Agency website. DDM is also made available by means of Open Geospatial Consortium web services (i.e., Web Map Service). The original datasets—not distributed with the model—are described in the auxiliary layers to provide information about the bathymetric sources used during the compilation. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Open AccessReview

Three Dimensional Change Detection Using Point Clouds: A Review

Abderrazzaq Kharroubi

and

Geomatics 2022, 2(4), 457-485; https://doi.org/10.3390/geomatics2040025 - 17 Oct 2022

Abstract

Change detection is an important step for the characterization of object dynamics at the earth’s surface. In multi-temporal point clouds, the main challenge is to detect true changes at different granularities in a scene subject to significant noise and occlusion. To better understand new research perspectives in this field, a deep review of recent advances in 3D change detection methods is needed. To this end, we present a comprehensive review of the state of the art of 3D change detection approaches, mainly those using 3D point clouds. We review standard methods and recent advances in the use of machine and deep learning for change detection. In addition, the paper presents a summary of 3D point cloud benchmark datasets from different sensors (aerial, mobile, and static), together with associated information. We also investigate representative evaluation metrics for this task. To finish, we present open questions and research perspectives. By reviewing the relevant papers in the field, we highlight the potential of bi- and multi-temporal point clouds for better monitoring analysis for various applications. Full article

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Open AccessArticle

A Workflow for Collecting and Preprocessing Sentinel-1 Images for Time Series Prediction Suitable for Deep Learning Algorithms

Waytehad Rose Moskolaï

Wahabou Abdou

Albert Dipanda

and

Kolyang

Geomatics 2022, 2(4), 435-456; https://doi.org/10.3390/geomatics2040024 - 01 Oct 2022

Abstract

The satellite image time series are used for several applications such as predictive analysis. New techniques such as deep learning (DL) algorithms generally require long sequences of data to perform well; however, the complexity of satellite image preprocessing tasks leads to a lack of preprocessed datasets. Moreover, using conventional collection and preprocessing methods is time- and storage-consuming. In this paper, a workflow for collecting, preprocessing, and preparing Sentinel-1 images to use with DL algorithms is proposed. The process mainly consists of using scripts for collecting and preprocessing operations. The goal of this work is not only to provide the community with easily modifiable programs for image collection and batch preprocessing but also to publish a database with prepared images. The experimental results allowed the researchers to build three time series of Sentinel-1 images corresponding to three study areas, namely the Bouba Ndjida National Park, the Dja Biosphere Reserve, and the Wildlife Reserve of Togodo. A total of 628 images were processed using scripts based on the SNAP graph processing tool (GPT). In order to test the effectiveness of the proposed methodology, three DL models were trained with the Bouba Ndjida and Togodo images for the prediction of the next occurrence in a sequence. Full article

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Open AccessFeature PaperArticle

Comprehensive Analysis of Ocean Current and Sea Surface Temperature Trend under Global Warming Hiatus of Kuroshio Extent Delineated Using a Combination of Spatial Domain Filters

Mohammed Abdul Athick AS

and

Shih-Yu Lee

Geomatics 2022, 2(4), 415-434; https://doi.org/10.3390/geomatics2040023 - 25 Sep 2022

Abstract

The effect of climate prevails on a diverse time scale from days to seasons and decades. Between 1993 and 2013, global warming appeared to have paused even though there was an increase in atmospheric greenhouse gases. The variations in oceanographic variables, like current speed and sea surface temperature (SST), under the influence of the global warming hiatus (1993–2013), have drawn the attention of the global research community. However, the magnitude of ocean current and SST characteristics oscillates and varies with their geographic locations. Consequently, investigating the spatio-temporal changing aspects of oceanographic parameters in the backdrop of climate change is essential, specifically in coastal regions along Kuroshio current (KC), where fisheries are predominant. This study analyzes the trend of ocean current and SST induced mainly during the global warming hiatus, before and till the recent time based on the daily ocean current data from 1993 to 2020 and SST between 1982 and 2020. The Kuroshio extent is delineated from its surrounding water masses using an aggregation of raster classification, stretching, equalization, and spatial filters such as edge detection, convolution, and Laplacian. Finally, on the extracted Kuroshio extent, analyses such as time series decomposition (additive) and statistical trend computation methods (Yue and Wang trend test and Theil–Sen’s slope estimator) were applied to dissect and investigate the situations. An interesting downward trend is observed in the KC between the East coast of Taiwan and Tokara Strait (Tau = −0.05, S = −2430, Sen’s slope = −5.19 × 10⁻⁵, and Z = −2.61), whereas an upward trend from Tokara Strait to Nagoya (Tau = 0.89, S = 4344, Sen’s slope = 8.4 × 10⁻⁵, and Z = 2.56). In contrast, a consistent increasing SST in trend is visualized in the southern and mid-KC sections but with varying magnitude. Full article

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Open AccessArticle

Modelling the Impact of Temperature under Climate Change Scenarios on Native and Invasive Vascular Vegetation on the Antarctic Peninsula and Surrounding Islands

Elissa Penfound

Christopher Wellen

and

Eric Vaz

Geomatics 2022, 2(4), 390-414; https://doi.org/10.3390/geomatics2040022 - 23 Sep 2022

Abstract

There are only two species of native vascular plants found on the Antarctic Peninsula and the surrounding islands, Deschampsia Antarctica, and Colobanthus quitensis. Poa annua, a successful invasive species, poses a threat to D. antarctica and C. quitensis. This region may experience extreme changes in biodiversity due to climate change over the next 100 years. This study explores the relationship between vascular vegetation and changing temperature on the Antarctic Peninsula and uses a systems modelling approach to account for three climate change scenarios over a 100-year period. The results of this study indicate that (1) D. antarctica, C. quitensis, and P. annua will likely be impacted by temperature increases, and greater temperature increases will facilitate more rapid species expansion, (2) in all scenarios D. antarctica species occurrences increase to higher values compared to C. quitensis and P. annua, suggesting that D. antarctica populations may be more successful at expanding into newly forming ice-free areas, (3) C. quitensis may be more vulnerable to the spread of P. annua than D. antarctica if less extreme warming occurs, and (4) C. quitensis relative growth rate is capable of reaching higher values than D. antarctica and P. annua, but only under extreme warming conditions. Full article

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Open AccessArticle

Classification of Multispectral Airborne LiDAR Data Using Geometric and Radiometric Information

Salem Morsy

Ahmed Shaker

and

Ahmed El-Rabbany

Geomatics 2022, 2(3), 370-389; https://doi.org/10.3390/geomatics2030021 - 09 Sep 2022

Abstract

Classification of airborne light detection and ranging (LiDAR) point cloud is still challenging due to the irregular point cloud distribution, relatively low point density, and the complex urban scenes being observed. The availability of multispectral LiDAR systems allows for acquiring data at different wavelengths with a variety of spectral information from land objects. In this research, a rule-based point classification method of three levels for multispectral airborne LiDAR data covering urban areas is presented. The first level includes ground filtering, which attempts to distinguish aboveground from ground points. The second level aims to divide the aboveground and ground points into buildings, trees, roads, or grass using three spectral indices, namely normalized difference feature indices (NDFIs). A multivariate Gaussian decomposition is then used to divide the NDFIs’ histograms into the aforementioned four classes. The third level aims to label more classes based on their spectral information such as power lines, types of trees, and swimming pools. Two data subsets were tested, which represent different complexity of urban scenes in Oshawa, Ontario, Canada. It is shown that the proposed method achieved an overall accuracy up to 93%, which is increased to over 98% by considering the spatial coherence of the point cloud. Full article

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Open AccessArticle

Feasibility of Using Green Laser in Monitoring Local Scour around Bridge Pier

and

Geomatics 2022, 2(3), 355-369; https://doi.org/10.3390/geomatics2030020 - 04 Sep 2022

Abstract

Scour around bridge piers is considered as one of the major factors which causes failure of bridges in the United States. An undetected scour can affect the stability of the bridge, eventually leading to the collapse of the bridge. The experimental investigation of scour around a pier using a non-contact measuring method is carried out in this research. A green laser-based non-contact ranging technique is performed on a prefabricated scour hole to study the factors influencing the ability to reconstruct the shape of a scour hole. The experiment was conducted in a 10 ft diameter pool and Leica scan station II was used for the scanning of the scour hole. The turbidity of the water was changed by adding Kaolinite powder to the water. The turbidity was varied from 1.2 NTU to 20.8 NTU by adding Kaolinite. The lab experiments involved changing the turbidity of water to simulate real world conditions. The results from the experimental study show that the turbidity of the water has a direct dependence on the efficiency of the green laser to map the underwater scour profile. The ability of the green laser to capture the fabricated scour hole and pool bed topography were decreased as the turbidity was increased even when the water depth of the pool was reduced. The results from the study show that the green laser is effective in underwater scanning and can be also used for bathymetry profiling and the detection of underwater objects. The method of underwater scanning using a green laser for detecting scour around bridge pier is safe, efficient, and economical. Full article

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Open AccessArticle

Effective Automated Procedures for Hydrographic Data Review

and

Geomatics 2022, 2(3), 338-354; https://doi.org/10.3390/geomatics2030019 - 25 Aug 2022

Cited by 1

Abstract

Reviewing hydrographic data for nautical charting is still a predominately manual process, performed by experienced analysts and based on directives developed over the years by the hydrographic office of interest. With the primary intent to increase the effectiveness of the review process, a set of automated procedures has been developed over the past few years, translating a significant portion of the NOAA Office of Coast Survey’s specifications for hydrographic data review into code (i.e., the HydrOffice applications called QC Tools and CA Tools). When applied to a large number of hydrographic surveys, it has been confirmed that such procedures improve both the quality and timeliness of the review process. Increased confidence in the reviewed data, especially by personnel in training, has also been observed. As such, the combined effect of applying these procedures is a novel holistic approach to hydrographic data review. Given the similarities of review procedures among hydrographic offices, the described approach has generated interest in the ocean mapping community. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Open AccessArticle

Land Cover Classification Based on Double Scatterer Model and Neural Networks

Konstantinos Karachristos

and

Vassilis Anastassopoulos

Geomatics 2022, 2(3), 323-337; https://doi.org/10.3390/geomatics2030018 - 24 Aug 2022

Abstract

In this paper, a supervised land cover classification is presented based on the extracted information from polarimetric synthetic aperture radar (PolSAR) images. The analysis of the polarimetric scattering matrix is accomplished according to the Double Scatterer Model which interprets each PolSAR cell by a pair of elementary scattering mechanisms. Subsequently, by utilizing the contribution rate of the two fundamental scatterers, a novel data representation is accomplished, providing great informational content. The main component of the research is to highlight the robust new feature-tool and afterwards to present a classification scheme exploiting a fully connected artificial neural network (ANN). The PolSAR images used to verify the proposed method were acquired by RADARSAT-2 and the experimental results confirm the effectiveness of the presented methodology with an overall classification accuracy of 93%, which is considered satisfactory since only four feature-vectors are used. Full article

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Open AccessArticle

Geospatial Intelligence and Machine Learning Technique for Urban Mapping in Coastal Regions of South Aegean Volcanic Arc Islands

Pavlos Krassakis

Andreas Karavias

Paraskevi Nomikou

Konstantinos Karantzalos

Nikolaos Koukouzas

Stavroula Kazana

and

Issaak Parcharidis

Geomatics 2022, 2(3), 297-322; https://doi.org/10.3390/geomatics2030017 - 19 Aug 2022

Abstract

Coastal environments are globally recognized for their spectacular morphological characteristics as well as economic opportunities, such as fisheries and tourism industries. However, climate change, growth in tourism, and constant coastal urban sprawl in some places result in ever-increasing risk in the islands of the South Aegean Volcanic Arc (SAVA), necessitating thoughtful planning and decision making. GEOspatial INTelligence (GEOINT) can play a crucial role in the depiction and analysis of the natural and human surroundings, offering valuable information regarding the identification of vulnerable areas and the forecasting of urbanization rates. This work focuses on the delineation of the coastal zone boundaries, semi-automatization of Satellite-Derived Bathymetry (SDB), and urban mapping using a machine learning algorithm. The developed methodology has been implemented on the islands of Thira (Santorini island complex) and Milos. This study attempts to identify inaccuracies in existing open-source datasets, such as the European Settlement Map (ESM), as a result of the unique combination of the architectural style and bare-soil characteristics of the study areas. During the period 2016–2021, the average accuracy of the developed methodology for urban mapping in terms of the kappa index was 80.15% on Thira and 88.35% on Milos. The results showed that the average urbanization expansion on specified settlements was greater than 22% for both case studies. Ultimately, the findings of this study could contribute to the effective and holistic management of similar coastal regions in the context of climate change adaptation, mitigation strategies, and multi-hazard assessment. Full article

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Open AccessArticle

Two Decades Mangroves Loss Monitoring Using Random Forest and Landsat Data in East Luwu, Indonesia (2000–2020)

Ilham Jamaluddin

Ying-Nong Chen

Syafiq Muhammad Ridha

Panji Mahyatar

and

Amalia Gita Ayudyanti

Geomatics 2022, 2(3), 282-296; https://doi.org/10.3390/geomatics2030016 - 22 Jul 2022

Abstract

Mangroves grow in the tidal zone and have many benefits for the ecosystem and human life. Mangrove loss monitoring is important information to know the condition and status of mangrove forests. Along with the development of computer technology, machine learning and satellite imagery has widely used for mangrove mapping. The goal of this study is to monitor two decades (2000–2020) of mangrove loss using a random forest (RF) algorithm with Landsat-7 and Landsat-8 data in East Luwu, Indonesia. East Luwu has a high mangrove deforestation rate based on the previous study. More detailed mangrove loss monitoring in this area is needed to know the annual mangrove deforestation rate in this area. This study used an RF model to produce mangrove maps in the whole study area from 2000 to 2020. According to the large computing and storage capabilities of time-series satellite data, this study used Google Earth Engine (GEE) platform as the cloud computing process. A total of 2500 independent testing points were collected to calculate the evaluation assessment of produced mangrove maps. Based on the evaluation assessment, the average overall score of produced mangrove map is 0.966, while the average UA score of mangrove class is 0.936. In general, this study revealed the total area of mangroves in East Luwu from 2000 to 2020 has a decreased trend. The highest annual rate of mangrove loss happened from 2000 to 2005 with a loss rate of −14.11% (2477.39 Ha). The main factor of mangrove loss in this area is caused by the aquaculture ponds. In addition, we found an increase in mangrove areas from 2016 to 2020 by +1.04% (87.96 ha). Full article

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Open AccessFeature PaperArticle

Quality Assessment of DJI Zenmuse L1 and P1 LiDAR and Photogrammetric Systems: Metric and Statistics Analysis with the Integration of Trimble SX10 Data

Filippo Diara

and

Marco Roggero

Geomatics 2022, 2(3), 254-281; https://doi.org/10.3390/geomatics2030015 - 14 Jul 2022

Abstract

This manuscript focuses on a quality assessment of DJI’s new sensors: the Zenmuse L1 and P1, which are LiDAR and photographic payload sensors, respectively, for UAVs/UASs. In particular, metric and statistical analyses aim to evaluate the data obtained from different 3D survey instruments. Furthermore, we compared these sensors with TLS data derived from a Trimble SX10 scanning station. The integration of LiDAR and photogrammetric data was then performed and tested inside a complex architectural context, the medieval Frinco Castle (AT-Italy). Point clouds obtained from aerial and terrestrial instruments were analysed and compared using specific tools to calculate variance/distance between points and cloud alignment (via the ICP algorithm), as well as to perform qualitative estimations (especially roughness analysis). The medieval castle proved crucial for the purpose of analysing different metric data of an extremely complex architecture and achieving more accurate results. The collected dataset and performed analyses are now essential information for the consolidation and restoration programme. Full article

(This article belongs to the Special Issue Advanced Geomatic Techniques for the Built Heritage: Data Processing, Interpretation and Knowledge Management)

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Open AccessFeature PaperArticle

Multigrid/Multiresolution Interpolation: Reducing Oversmoothing and Other Sampling Effects

Daniel Rodriguez-Perez

and

Noela Sanchez-Carnero

Geomatics 2022, 2(3), 236-253; https://doi.org/10.3390/geomatics2030014 - 22 Jun 2022

Abstract

Traditional interpolation methods, such as IDW, kriging, radial basis functions, and regularized splines, are commonly used to generate digital elevation models (DEM). All of these methods have strong statistical and analytical foundations (such as the assumption of randomly distributed data points from a gaussian correlated stochastic surface); however, when data are acquired non-homogeneously (e.g., along transects) all of them show over/under-smoothing of the interpolated surface depending on local point density. As a result, actual information is lost in high point density areas (caused by over-smoothing) or artifacts appear around uneven density areas (“pimple” or “transect” effects). In this paper, we introduce a simple but robust multigrid/multiresolution interpolation (MMI) method which adapts to the spatial resolution available, being an exact interpolator where data exist and a smoothing generalizer where data are missing, but always fulfilling the statistical requirement that surface height mathematical expectation at the proper working resolution equals the mean height of the data at that same scale. The MMI is efficient enough to use K-fold cross-validation to estimate local errors. We also introduce a fractal extrapolation that simulates the elevation in data-depleted areas (rendering a visually realistic surface and also realistic error estimations). In this work, MMI is applied to reconstruct a real DEM, thus testing its accuracy and local error estimation capabilities under different sampling strategies (random points and transects). It is also applied to compute the bathymetry of Gulf of San Jorge (Argentina) from multisource data of different origins and sampling qualities. The results show visually realistic surfaces with estimated local validation errors that are within the bounds of direct DEM comparison, in the case of the simulation, and within the

10 %

of the bathymetric surface typical deviation in the real calculation. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Open AccessArticle

Automated Modeling of Road Networks for High-Definition Maps in OpenDRIVE Format Using Mobile Mapping Measurements

and

Geomatics 2022, 2(2), 221-235; https://doi.org/10.3390/geomatics2020013 - 01 Jun 2022

Abstract

With growing attention being devoted to autonomous vehicle (AV) safety, people have recently attached importance to high-definition (HD) maps. HD maps are not limited by environmental factors and can limit AVs driving in certain lanes. HD maps provide accurate auxiliary information on factors such as road geometry, traffic sign placement, and traffic topology. Nowadays, most HD maps are made from point clouds data, and this data contains accurate 3D position information. However, the production costs associated with HD maps are substantial. This article proposes an algorithm that reduces a great amount of time and human resource. The algorithm is divided into three phases, lane lines’ extraction from point clouds, modelling lane lines with attributes, and building OpenDRIVE file. The algorithm extracts lane lines resting on intensity value within the range of roads. Next, it models lane lines by cubic spline interpolation with the result of first phase, and build the OpenDRIVE file following the announcement of OpenDRIVE. The final result is compared with the verified HD map from the mapping company to analyze the accuracy. The root mean square (RMSE) obtained were 0.069 and 0.079 m for 2D and 3D maps, respectively. Full article

(This article belongs to the Special Issue High Definition Maps for Intelligent Transportation Applications)

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Open AccessFeature PaperReview

Introducing Smart Marine Ecosystem-Based Planning (SMEP)—How SMEP Can Drive Marine Spatial Planning Strategy and Its Implementation in Greece

Stilianos Contarinis

Byron Nakos

and

Athanasios Pallikaris

Geomatics 2022, 2(2), 197-220; https://doi.org/10.3390/geomatics2020012 - 13 May 2022

Abstract

This paper introduces smart marine ecosystem-based planning (SMEP), a marine spatial planning (MSP) strategy for more participatory and responsive marine governance by leveraging “smart” digital services. SMEP denotes an iterative MSP process with planning cycles that incorporate continuous data gathering of spatial–temporal natural phenomena and human activities in coastal and marine areas, with ongoing data mining to locate key patterns and trends, to strive for periodic refinement of the MSP output. SMEP aims to adopt an ecosystem-based approach, taking into account both living and nonliving aspects of the marine environment, and making use of all available spatial data at various resolutions. In pursuit of SMEP implementation, the paper examines the current state of the MSP process in Greece and relates its long-term success with the establishment of a marine spatial data infrastructure (MSDI), employing contemporary nautical cartography standards along with hydrospatial data services. Full article

(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)

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Open AccessArticle

A Practical Algorithm for the Viewpoint Planning of Terrestrial Laser Scanners

Fengman Jia

and

Derek D. Lichti

Geomatics 2022, 2(2), 181-196; https://doi.org/10.3390/geomatics2020011 - 22 Apr 2022

Cited by 1

Abstract

Applications using terrestrial laser scanners (TLS) have been skyrocketing in the past two decades. In a scanning project, the configuration of scans is a critical issue as it has significant effects on the project cost and the quality of the product. In this paper, a practical strategy is proposed to resolve the problem of the optimal placement of the terrestrial laser scanner. The method attempts to reduce the number of viewpoints under the premise that the scenes are fully covered. In addition, the approach is designed in a way that the solutions can be efficiently explored. The method has been tested on 540 polygons simulated with different sizes and complexities. The results have also been compared with a benchmark strategy in terms of the optimality of the solutions and runtime. It is concluded that our proposed algorithm ties or reduces the number of viewpoints in the benchmark paper in 85.6% of the 540 tests. For complex environments, the method can potentially reduce the project cost by 10%. Although with relatively lower efficiency, our method can still reach the solution within a few minutes for a polygon with up to 500 vertices. Full article

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Open AccessArticle

A Dispersion Index for the Analysis of the Distribution of Activities in the Tunisian Coastal City of Nabeul

Narjiss Bakhtyari

Asma Rejeb Bouzgarrou

Christophe Claramunt

and

Hichem Rejeb

Geomatics 2022, 2(2), 161-180; https://doi.org/10.3390/geomatics2020010 - 21 Apr 2022

Abstract

This research investigates the duality of the spatial organization and urban activities generated by the coastalization processes of the city of Nabeul. The first part of the study analyzes the city’s fragmentations of the urban landscape using a novel generic index of directional dispersion and a set of space syntax metrics. These structural and functional properties are studied by the concentration and/or dispersion of urban functions of the evolution and development patterns. Among the emerging features, we observe a dispersion of urban activities beyond a central radius all along the western periphery of the city, confirming the phenomenon of urban sprawl that many Tunisian cities are experiencing. These spaces generate urban fragmentations of “new polarity zones” under the influence of the coastline attraction. Finally, this study introduces a novel approach for identifying urban structural polarity and activities, as well as new perspectives for coastal land management and planning. Full article

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Open AccessArticle

Detection of Snow Cover from Historical and Recent AVHHR Data—A Thematic TIMELINE Processor

Sebastian Rößler

and

Andreas J. Dietz

Geomatics 2022, 2(1), 144-160; https://doi.org/10.3390/geomatics2010009 - 18 Mar 2022

Cited by 1

Abstract

Global snow cover forms the largest and most transient part of the cryosphere in terms of area. On the local and regional scale, small changes can have drastic effects such as floods and droughts, and on the global scale is the planetary albedo. Daily imagery of snow cover forms the basis of long-term observation and analysis, and only optical sensors offer the necessary spatial and temporal resolution to address decadal developments and the impact of climate change on snow availability. The MODIS sensors have been providing this daily information since 2000; before that, only the Advanced Very High-Resolution Radiometer (AVHRR) from the National Oceanographic and Atmospheric Administration (NOAA) was suitable. In the TIMELINE project of the German Aerospace Center, the historic AVHRR archive in HRPT (High Resolution Picture Transmission) format is processed for the European area and, among other processors, one output is the thematic product ‘snow cover’ that will be made available in 1 km resolution since 1981. The snow detection is based on the Normalized Difference Snow Index (NDSI), which enables a direct comparison with the MODIS snow product. In addition to the NDSI, ERA5 re-analysis data on the skin temperature and other level 2 TIMELINE products are included in the generation of the binary snow mask. The AVHRR orbit segments are projected from the swath projection into LAEA Europe, aggregated into daily coverages, and from this, the 10-day and monthly snow covers are finally calculated. In this publication, the snow cover algorithm is presented, as well as the results of the first validations and possible applications of the final product. Full article

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