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 is provided to authors approximately 18.6 days after submission; acceptance to publication is undertaken in 3.2 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
- Companion journal: Remote Sensing.
Latest Articles
Mapping and Geomorphic Characterization of the Vast Cold-Water Coral Mounds of the Blake Plateau
Geomatics 2024, 4(1), 17-47; https://doi.org/10.3390/geomatics4010002 - 12 Jan 2024
Abstract
►
Show Figures
A coordinated multi-year ocean exploration campaign on the Blake Plateau offshore of the southeastern U.S. has mapped what appears to be the most expansive cold-water coral (CWC) mound province thus far discovered. Nearly continuous CWC mound features span an area up to 500
[...] Read more.
A coordinated multi-year ocean exploration campaign on the Blake Plateau offshore of the southeastern U.S. has mapped what appears to be the most expansive cold-water coral (CWC) mound province thus far discovered. Nearly continuous CWC mound features span an area up to 500 km long and 110 km wide, with a core area of high-density mounds up to 254 km long by 42 km wide. This study synthesized bathymetric data from 31 multibeam sonar mapping surveys and generated a standardized geomorphic classification of the region in order to delineate and quantify CWC mound habitats and compare mound morphologies among subregions of the coral province. Based on the multibeam bathymetry, a total of 83,908 individual peak features were delineated, providing the first estimate of the overall number of potential CWC mounds mapped in the region to date. Five geomorphic landform classes were mapped and quantified: peaks (411 km2), valleys (3598 km2), ridges (3642 km2), slopes (23,082 km2), and flats (102,848 km2). The complex geomorphology of eight subregions was described qualitatively with geomorphic “fingerprints” (spatial patterns) and quantitatively by measurements of mound density and vertical relief. This study demonstrated the value of applying an objective automated terrain segmentation and classification approach to geomorphic characterization of a highly complex CWC mound province. Manual delineation of these features in a consistent repeatable way with a comparable level of detail would not have been possible.
Full article
Open AccessArticle
Evaluating Land Surface Temperature Trends and Explanatory Variables in the Miami Metropolitan Area from 2002–2021
by
and
Geomatics 2024, 4(1), 1-16; https://doi.org/10.3390/geomatics4010001 - 25 Dec 2023
Abstract
►▼
Show Figures
Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST
[...] Read more.
Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST trends in the Miami Statistical Area (MSA) between 2002 and 2021. This study evaluates the effect of dry and wet seasons as well as day and night data on LST. A multiscale investigation is used to examine LST trends at the MSA scale, the individual county level, and at the pixel level to provide a detailed local perspective. The multiscale results are needed to understand spatiotemporal LST distributions to plan mitigation measures such as planting trees or greenery to regulate temperature and reduce the impacts of surface urban heat islands. The results indicate that LST values are rising in the MSA with a positive trend throughout the 20-year study period. The rate of change (RoC) for the wet season is smaller than for the dry season. The pixel-level analysis suggests that the RoC is primarily in rural areas and less apparent in urban areas. New development in rural areas may trigger increased RoC. This RoC relates to LST in the MSA and is different from global or regional RoC using air temperature. Results also suggest that climatic explanatory variables have different impacts during the night than they do in the daytime. For instance, the Tree Canopy variable has a positive coefficient, while during the day, the Tree Canopy variable has a negative relationship with LST. The Distance to the Coast variable changes from day to night as well. The increased granularity achieved with the multiscale analysis provides critical information needed to improve the effectiveness of potential mitigation efforts.
Full article
Figure 1
Open AccessArticle
“How Far Is the Closest Bus Stop?” An Evaluation of Self-Reported versus GIS-Computed Distance to the Bus among Older People and Factors Influencing Their Perception of Distance
by
, , , , , and
Geomatics 2023, 3(4), 580-596; https://doi.org/10.3390/geomatics3040031 - 13 Dec 2023
Abstract
►▼
Show Figures
Previous research showed that living closer to bus stops could be a factor in promoting a healthy and active lifestyle. However, most of the studies relied on self-reported measures of distance, which might be affected by several confounders. In this study, self-reported distances
[...] Read more.
Previous research showed that living closer to bus stops could be a factor in promoting a healthy and active lifestyle. However, most of the studies relied on self-reported measures of distance, which might be affected by several confounders. In this study, self-reported distances among study participants were compared to actual ones, computed by the use of GIS (Geographic Information System) technology and routing algorithms. We tested whether distance to the bus stop is associated with health and socioeconomic conditions of the respondents, using data among 2398 older people (75–90 years) in three cities in Sweden. We found that several variables including older age, female gender, living alone, and worse health status are associated with an over-estimation of bus stop distance. People who use public transport daily or several times a week and are satisfied with the walking environment in the neighbourhood tend to underestimate bus stop distances. Evidence based on self-reported measures only should be treated cautiously. Considering the limitations still present in open-data-based routing algorithms, the best indication is to combine the subjective with the objective measure of distance. Having the possibility to combine the two measures appears as a sound strategy to overcome the limitations associated with each single measure.
Full article
Figure 1
Open AccessArticle
Use of Smartphone Lidar Technology for Low-Cost 3D Building Documentation with iPhone 13 Pro: A Comparative Analysis of Mobile Scanning Applications
by
and
Geomatics 2023, 3(4), 563-579; https://doi.org/10.3390/geomatics3040030 - 11 Dec 2023
Abstract
►▼
Show Figures
Laser scanning technology has long been the preferred method for capturing interior scenes in various industries. With a growing market, smaller and more affordable scanners have emerged, offering end products with sufficient accuracy. While not on par with professional scanners, Apple has made
[...] Read more.
Laser scanning technology has long been the preferred method for capturing interior scenes in various industries. With a growing market, smaller and more affordable scanners have emerged, offering end products with sufficient accuracy. While not on par with professional scanners, Apple has made laser scanning technology accessible to users with the introduction of the new iPhone Pro models, democratizing 3D scanning. Thus, this study aimed to assess the performance of the iPhone’s lidar technology as a low-cost solution for building documentation. Four scanning applications were evaluated to determine the accuracy, precision, and user experience of the generated point clouds compared with a terrestrial laser scanner. The results reveal varying performances on the same device, highlighting the influence of software. Notably, there is room for improvement, particularly in tracking the device’s position through software solutions. As it stands, the technology is well suited for applications such as indoor navigation and the generation of quick floor plans in the context of building documentation.
Full article
Figure 1
Open AccessArticle
Evaluating OSM Building Footprint Data Quality in Québec Province, Canada from 2018 to 2023: A Comparative Study
Geomatics 2023, 3(4), 541-562; https://doi.org/10.3390/geomatics3040029 - 09 Dec 2023
Abstract
►▼
Show Figures
OpenStreetMap (OSM) is among the most prominent Volunteered Geographic Information (VGI) initiatives, aiming to create a freely accessible world map. Despite its success, the data quality of OSM remains variable. This study begins by identifying the quality metrics proposed by earlier research to
[...] Read more.
OpenStreetMap (OSM) is among the most prominent Volunteered Geographic Information (VGI) initiatives, aiming to create a freely accessible world map. Despite its success, the data quality of OSM remains variable. This study begins by identifying the quality metrics proposed by earlier research to assess the quality of OSM building footprints. It then evaluates the quality of OSM building data from 2018 and 2023 for five cities within Québec, Canada. The analysis reveals a significant quality improvement over time. In 2018, the completeness of OSM building footprints in the examined cities averaged around 5%, while by 2023, it had increased to approximately 35%. However, this improvement was not evenly distributed. For example, Shawinigan saw its completeness surge from 2% to 99%. The study also finds that OSM contributors were more likely to digitize larger buildings before smaller ones. Positional accuracy saw enhancement, with the average error shrinking from 3.7 m in 2018 to 2.3 m in 2023. The average distance measure suggests a modest increase in shape accuracy over the same period. Overall, while the quality of OSM building footprints has indeed improved, this study shows that the extent of the improvement varied significantly across different cities. Shawinigan experienced a substantial increase in data quality compared to its counterparts.
Full article
Figure 1
Open AccessArticle
Beyond the Tide: A Comprehensive Guide to Sea-Level-Rise Inundation Mapping Using FOSS4G
Geomatics 2023, 3(4), 522-540; https://doi.org/10.3390/geomatics3040028 - 28 Nov 2023
Abstract
Sea-level rise (SLR) is a critical consequence of climate change, posing significant threats to coastal regions worldwide. Accurate and efficient assessment of potential inundation areas is crucial for effective coastal planning and adaptation strategies. This study aimed to explore the utility of free
[...] Read more.
Sea-level rise (SLR) is a critical consequence of climate change, posing significant threats to coastal regions worldwide. Accurate and efficient assessment of potential inundation areas is crucial for effective coastal planning and adaptation strategies. This study aimed to explore the utility of free and open-source software for geospatial (FOSS4G) tools for mapping SLR inundation, providing cost-effective solutions that are accessible to researchers and policymakers. We employed a combination of geospatial data, including high-resolution elevation models, tidal data, and projected SLR scenarios. Utilizing widely available FOSS4G tools, like QGIS, GDAL/OGR, and GRASS GIS, we developed an integrated workflow to map inundation extents, using a passive bathtub approach for various SLR scenarios. We demonstrate the approach through a case study in Virginia Key, Florida, however, the methodology can be replicated in any area where the input datasets are available. This paper demonstrates that FOSS4G tools offer a reliable and accessible means to map SLR inundation, empowering stakeholders to assess coastal vulnerabilities and to devise sustainable adaptation measures. The open-source approach facilitates collaboration and reproducibility, fostering a comprehensive understanding of the potential impacts of SLR on coastal ecosystems and communities.
Full article
(This article belongs to the Special Issue GIS Open Source Software Applied to Geosciences)
►▼
Show Figures
Figure 1
Open AccessArticle
Comparative Analysis of Algorithms to Cleanse Soil Micro-Relief Point Clouds
by
, , , and
Geomatics 2023, 3(4), 501-521; https://doi.org/10.3390/geomatics3040027 - 26 Nov 2023
Abstract
Detecting changes in soil micro-relief in farmland helps to understand degradation processes like sheet erosion. Using the high-resolution technique of terrestrial laser scanning (TLS), we generated point clouds of three 2 × 3 m plots on a weekly basis from May to mid-June
[...] Read more.
Detecting changes in soil micro-relief in farmland helps to understand degradation processes like sheet erosion. Using the high-resolution technique of terrestrial laser scanning (TLS), we generated point clouds of three 2 × 3 m plots on a weekly basis from May to mid-June in 2022 on cultivated farmland in Germany. Three well-known applications for eliminating vegetation points in the generated point cloud were tested: Cloth Simulation Filter (CSF) as a filtering method, three variants of CANUPO as a machine learning method, and ArcGIS PointCNN as a deep learning method, a sub-category of machine learning using deep neural networks. We assessed the methods with hard criteria such as F1 score, balanced accuracy, height differences, and their standard deviations to the reference surface, resulting in data gaps and robustness, and with soft criteria such as time-saving capacity, accessibility, and user knowledge. All algorithms showed a low performance at the initial measurement epoch, increasing with later epochs. While most of the results demonstrate a better performance of ArcGIS PointCNN, this algorithm revealed an exceptionally low performance in plot 1, which is describable by the generalization gap. Although CANUPO variants created the highest amount of data gaps, we recommend that CANUPO include colour values in combination with CSF.
Full article
(This article belongs to the Topic Remote Sensing and Geoinformatics in Agriculture and Environment Volume II)
►▼
Show Figures
Figure 1
Open AccessReview
Quantifying Aboveground Grass Biomass Using Space-Borne Sensors: A Meta-Analysis and Systematic Review
Geomatics 2023, 3(4), 478-500; https://doi.org/10.3390/geomatics3040026 - 18 Oct 2023
Abstract
Recently, the move from cost-tied to open-access data has led to the mushrooming of research in pursuit of algorithms for estimating the aboveground grass biomass (AGGB). Nevertheless, a comprehensive synthesis or direction on the milestones achieved or an overview of how these models
[...] Read more.
Recently, the move from cost-tied to open-access data has led to the mushrooming of research in pursuit of algorithms for estimating the aboveground grass biomass (AGGB). Nevertheless, a comprehensive synthesis or direction on the milestones achieved or an overview of how these models perform is lacking. This study synthesises the research from decades of experiments in order to point researchers in the direction of what was achieved, the challenges faced, as well as how the models perform. A pool of findings from 108 remote sensing-based AGGB studies published from 1972 to 2020 show that about 19% of the remote sensing-based algorithms were tested in the savannah grasslands. An uneven annual publication yield was observed with approximately 36% of the research output from Asia, whereas countries in the global south yielded few publications (<10%). Optical sensors, particularly MODIS, remain a major source of satellite data for AGGB studies, whilst studies in the global south rarely use active sensors such as Sentinel-1. Optical data tend to produce low regression accuracies that are highly inconsistent across the studies compared to radar. The vegetation indices, particularly the Normalised Difference Vegetation Index (NDVI), remain as the most frequently used predictor variable. The predictor variables such as the sward height, red edge position and backscatter coefficients produced consistent accuracies. Deciding on the optimal algorithm for estimating the AGGB is daunting due to the lack of overlap in the grassland type, location, sensor types, and predictor variables, signalling the need for standardised remote sensing techniques, including data collection methods to ensure the transferability of remote sensing-based AGGB models across multiple locations.
Full article
(This article belongs to the Topic Remote Sensing and Geoinformatics in Agriculture and Environment Volume II)
►▼
Show Figures
Figure 1
Open AccessArticle
Applying a Geographic Information System and Other Open-Source Software to Geological Mapping and Modeling: History and Case Studies
Geomatics 2023, 3(4), 465-477; https://doi.org/10.3390/geomatics3040025 - 13 Oct 2023
Abstract
Open-source software applications, especially those useful for GIS, have been used in the field of geology both in research and teaching at the University of Urbino for decades. The experiences described in this article range from land-surveying cases to cartographic processing and 3D
[...] Read more.
Open-source software applications, especially those useful for GIS, have been used in the field of geology both in research and teaching at the University of Urbino for decades. The experiences described in this article range from land-surveying cases to cartographic processing and 3D printing of geological models. History of their use and development is punctuated by trials, failures, and slowdowns, but the idea of using digital tools in areas where they are traditionally frowned upon, such as in soil geology, is now rooted in and validated by applications in projects of various types. Although the current situation is not definitive, given that the evolution of information technology provides increasingly faster tools that are performance-oriented and easier to use, this article aims to contribute to the development of methodologies through an exchange of information and experiences.
Full article
(This article belongs to the Special Issue GIS Open Source Software Applied to Geosciences)
►▼
Show Figures
Figure 1
Open AccessArticle
Land Use and Land Cover Changes in Kabul, Afghanistan Focusing on the Drivers Impacting Urban Dynamics during Five Decades 1973–2020
Geomatics 2023, 3(3), 447-464; https://doi.org/10.3390/geomatics3030024 - 09 Sep 2023
Abstract
This study delves into the patterns of urban expansion in Kabul, using Landsat and Sentinel satellite imagery as primary tools for analysis. We classified land use and land cover (LULC) into five distinct categories: water bodies, vegetation, barren land, barren rocky terrain, and
[...] Read more.
This study delves into the patterns of urban expansion in Kabul, using Landsat and Sentinel satellite imagery as primary tools for analysis. We classified land use and land cover (LULC) into five distinct categories: water bodies, vegetation, barren land, barren rocky terrain, and buildings. The necessary data processing and analysis was conducted using ERDAS Imagine v.2015 and ArcGIS 10.8 software. Our main objective was to scrutinize changes in LULC across five discrete decades. Additionally, we traced the long-term evolution of built-up areas in Kabul from 1973 to 2020. The classified satellite images revealed significant changes across all categories. For instance, the area of built-up land reduced from 29.91% in 2013 to 23.84% in 2020, while barren land saw a decrease from 33.3% to 28.4% over the same period. Conversely, the proportion of barren rocky terrain exhibited an increase from 22.89% in 2013 to 29.97% in 2020. Minor yet notable shifts were observed in the categories of water bodies and vegetated land use. The percentage of water bodies shrank from 2.51% in 2003 to 1.30% in 2013, and the extent of vegetated land use showed a decline from 13.61% in 2003 to 12.6% in 2013. Our study unveiled evolving land use patterns over time, with specific periods recording an increase in barren land and a slight rise in vegetated areas. These findings underscored the dynamic transformation of Kabul’s urban landscape over the years, with significant implications for urban planning and sustainability.
Full article
(This article belongs to the Topic Urban Land Use and Spatial Analysis)
►▼
Show Figures
Figure 1
Open AccessArticle
Temporal Autocorrelation of Sentinel-1 SAR Imagery for Detecting Settlement Expansion
by
and
Geomatics 2023, 3(3), 427-446; https://doi.org/10.3390/geomatics3030023 - 21 Aug 2023
Abstract
Urban areas are rapidly expanding globally. The detection of settlement expansion can, however, be challenging due to the rapid rate of expansion, especially for informal settlements. This paper presents a solution in the form of an unsupervised autocorrelation-based approach. Temporal autocorrelation function (ACF)
[...] Read more.
Urban areas are rapidly expanding globally. The detection of settlement expansion can, however, be challenging due to the rapid rate of expansion, especially for informal settlements. This paper presents a solution in the form of an unsupervised autocorrelation-based approach. Temporal autocorrelation function (ACF) values derived from hyper-temporal Sentinel-1 imagery were calculated for all time lags using VV backscatter values. Various thresholds were applied to these ACF values in order to create urban change maps. Two different orbital combinations were tested over four informal settlement areas in South Africa. Promising results were achieved in the two of the study areas with mean normalized Matthews Correlation Coefficients (MCCn) of 0.79 and 0.78. A lower performance was obtained in the remaining two areas (mean MCCn of 0.61 and 0.65) due to unfavorable building orientations and low building densities. The first results also indicate that the most stable and optimal ACF-based threshold of 95 was achieved when using images from both relative orbits, thereby incorporating more incidence angles. The results demonstrate the capacity of ACF-based methods for detecting settlement expansion. Practically, this ACF-based method could be used to reduce the time and labor costs of detecting and mapping newly built settlements in developing regions.
Full article
(This article belongs to the Special Issue Urban Morphology and Environment Monitoring)
►▼
Show Figures
Figure 1
Open AccessArticle
Seafloor and Ocean Crust Structure of the Kerguelen Plateau from Marine Geophysical and Satellite Altimetry Datasets
Geomatics 2023, 3(3), 393-426; https://doi.org/10.3390/geomatics3030022 - 10 Aug 2023
Abstract
The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the
[...] Read more.
The volcanic Kerguelen Islands are formed on one of the world’s largest submarine plateaus. Located in the remote segment of the southern Indian Ocean close to Antarctica, the Kerguelen Plateau is notable for a complex tectonic origin and geologic formation related to the Cretaceous history of the continents. This is reflected in the varying age of the oceanic crust adjacent to the plateau and the highly heterogeneous bathymetry of the Kerguelen Plateau, with seafloor structure differing for the southern and northern segments. Remote sensing data derived from marine gravity and satellite radar altimetry surveys serve as an important source of information for mapping complex seafloor features. This study incorporates geospatial information from NOAA, EMAG2, WDMAM, ETOPO1, and EGM96 datasets to refine the extent and distribution of the extracted seafloor features. The cartographic joint analysis of topography, magnetic anomalies, tectonic and gravity grids is based on the integrated mapping performed using the Generic Mapping Tools (GMT) programming suite. Mapping of the submerged features (Broken Ridge, Crozet Islands, seafloor fabric, orientation, and frequency of magnetic anomalies) enables analysis of their correspondence with free-air gravity and magnetic anomalies, geodynamic setting, and seabed structure in the southwest Indian Ocean. The results show that integrating the datasets using advanced cartographic scripting language improves identification and visualization of the seabed objects. The results include 11 new maps of the region covering the Kerguelen Plateau and southwest Indian Ocean. This study contributes to increasing the knowledge of the seafloor structure in the French Southern and Antarctic Lands.
Full article
(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)
►▼
Show Figures
Figure 1
Open AccessReview
Review of Remote Sensing Approaches and Soft Computing for Infrastructure Monitoring
Geomatics 2023, 3(3), 367-392; https://doi.org/10.3390/geomatics3030021 - 16 Jul 2023
Cited by 2
Abstract
►▼
Show Figures
During the past few decades, remote sensing has been established as an innovative, effective and cost-efficient option for the provision of high-quality information concerning infrastructure to governments or decision makers in order to update their plans and/or take actions towards the mitigation of
[...] Read more.
During the past few decades, remote sensing has been established as an innovative, effective and cost-efficient option for the provision of high-quality information concerning infrastructure to governments or decision makers in order to update their plans and/or take actions towards the mitigation of the infrastructure risk. Meanwhile, climate change has emerged as a serious global challenge and hence there is an urgent need to develop reliable and cost-efficient infrastructure monitoring solutions. In this framework, the current study conducts a comprehensive review concerning the use of different remote-sensing sensors for the monitoring of multiple types of infrastructure including roads and railways, dams, bridges, archaeological sites and buildings. The aim of this contribution is to identify the best practices and processing methodologies for the comprehensive monitoring of critical national infrastructure falling under the research project named “PROION”. In light of this, the review summarizes the wide variety of approaches that have been utilized for the monitoring of infrastructure and are based on the collection of remote-sensing data, acquired using the global navigation satellite system (GNSS), synthetic aperture radar (SAR), light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV) sensors. Moreover, great emphasis is given to the contribution of the state-of-the-art soft computing methods throughout infrastructure monitoring aiming to increase the automation of the procedure. The statistical analysis of the reviewing publications revealed that SARs and LiDARs are the prevalent remote-sensing sensors used in infrastructure monitoring concepts, while regarding the type of infrastructure, research is orientated onto transportation networks (road and railway) and bridges. Added to this, deep learning-, fuzzy logic- and expert-based approaches have gained ground in the field of infrastructure monitoring over the past few years.
Full article
Figure 1
Open AccessEditorial
Geomatics in the Era of Citizen Science
Geomatics 2023, 3(2), 364-366; https://doi.org/10.3390/geomatics3020020 - 20 Jun 2023
Cited by 1
Abstract
Geomatics has long been recognized as an information-technology-oriented discipline whose objective is to integrate and deliver multiple sources of geolocated data to a wide range of environmental and urban sciences [...]
Full article
Open AccessArticle
Advancing Erosion Control Analysis: A Comparative Study of Terrestrial Laser Scanning (TLS) and Robotic Total Station Techniques for Sediment Barrier Retention Measurement
Geomatics 2023, 3(2), 345-363; https://doi.org/10.3390/geomatics3020019 - 26 Apr 2023
Cited by 1
Abstract
Sediment Barriers (SBs) are crucial for effective erosion control, and understanding their capacities and limitations is essential for environmental protection. This study compares the accuracy and effectiveness of Terrestrial Laser Scanning (TLS) and Robotic Total Station (RTS) techniques for quantifying sediment retention in
[...] Read more.
Sediment Barriers (SBs) are crucial for effective erosion control, and understanding their capacities and limitations is essential for environmental protection. This study compares the accuracy and effectiveness of Terrestrial Laser Scanning (TLS) and Robotic Total Station (RTS) techniques for quantifying sediment retention in SBs. To achieve this, erosion tests were conducted in a full-scale testing apparatus with TLS and RTS methods to collect morphological data of sediment retention surfaces before and after each experiment. The acquired datasets were processed and integrated into a Building Information Modeling (BIM) platform to create Digital Elevation Models (DEMs). These were then used to calculate the volume of accumulated sediment upstream of the SB system. The results indicated that TLS and RTS techniques could effectively measure sediment retention in a full-scale testing environment. However, TLS proved to be more accurate, exhibiting a standard deviation of 0.41 ft3 in contrast to 1.94 ft3 for RTS and more efficient, requiring approximately 15% to 50% less time per test than RTS. The main conclusions of this study highlight the benefits of using TLS over RTS for sediment retention measurement and provide valuable insights for improving erosion control strategies and sediment barrier design.
Full article
(This article belongs to the Topic Slope Erosion Monitoring and Anti-erosion)
►▼
Show Figures
Figure 1
Open AccessArticle
Mapping Invasive Herbaceous Plant Species with Sentinel-2 Satellite Imagery: Echium plantagineum in a Mediterranean Shrubland as a Case Study
Geomatics 2023, 3(2), 328-344; https://doi.org/10.3390/geomatics3020018 - 18 Apr 2023
Cited by 1
Abstract
►▼
Show Figures
Invasive alien plants (IAPs) pose a serious threat to biodiversity, agriculture, health, and economies globally. Accurate mapping of IAPs is crucial for their management, to mitigate their impacts and prevent further spread where possible. Remote sensing has become a valuable tool in detecting
[...] Read more.
Invasive alien plants (IAPs) pose a serious threat to biodiversity, agriculture, health, and economies globally. Accurate mapping of IAPs is crucial for their management, to mitigate their impacts and prevent further spread where possible. Remote sensing has become a valuable tool in detecting IAPs, especially with freely available data such as Sentinel-2 satellite imagery. Yet, remote sensing methods to map herbaceous IAPs, which tend to be more difficult to detect, particularly in shrubland Mediterranean-type ecosystems, are still limited. There is a growing need to detect herbaceous IAPs at a large scale for monitoring and management; however, for countries or organizations with limited budgets, this is often not feasible. To address this, we aimed to develop a classification methodology based on optical satellite data to map herbaceous IAP’s using Echium plantagineum as a case study in the Fynbos Biome of South Africa. We investigate the use of freely available Sentinel-2 data, use the robust non-parametric classifier Random Forest, and identify the most important variables in the classification, all within the cloud-based platform, Google Earth Engine. Findings reveal the importance of the shortwave infrared and red-edge parts of the spectrum and the importance of including vegetation indices in the classification for discriminating E. plantagineum. Here, we demonstrate the potential of Sentinel-2 data, the Random Forest classifier, and Google Earth Engine for mapping herbaceous IAPs in Mediterranean ecosystems.
Full article
Figure 1
Open AccessArticle
High-Resolution Mapping of Seasonal Crop Pattern Using Sentinel Imagery in Mountainous Region of Nepal: A Semi-Automatic Approach
by
, , , , , and
Geomatics 2023, 3(2), 312-327; https://doi.org/10.3390/geomatics3020017 - 06 Apr 2023
Abstract
►▼
Show Figures
Sustainable agricultural management requires knowledge of where and when crops are grown, what they are, and for how long. However, such information is not yet available in Nepal. Remote sensing coupled with farmers’ knowledge offers a solution to fill this gap. In this
[...] Read more.
Sustainable agricultural management requires knowledge of where and when crops are grown, what they are, and for how long. However, such information is not yet available in Nepal. Remote sensing coupled with farmers’ knowledge offers a solution to fill this gap. In this study, we created a high-resolution (10 m) seasonal crop map and cropping pattern in a mountainous area of Nepal through a semi-automatic workflow using Sentinel-2 A/B time-series images coupled with farmer knowledge. We identified agricultural areas through iterative self-organizing data clustering of Sentinel imagery and topographic information using a digital elevation model automatically. This agricultural area was analyzed to develop crop calendars and to track seasonal crop dynamics using rule-based methods. Finally, we computed a pixel-level crop-intensity map. In the end our results were compared to ground-truth data collected in the field and published crop calendars, with an overall accuracy of 88% and kappa coefficient of 0.83. We found variations in crop intensity and seasonal crop extension across the study area, with higher intensity in plain areas with irrigation facilities and longer fallow cycles in dry and hilly regions. The semi-automatic workflow was successfully implemented in the heterogeneous topography and is applicable to the diverse topography of the entire country, providing crucial information for mapping and monitoring crops that is very useful for the formulation of strategic agricultural plans and food security in Nepal.
Full article
Figure 1
Open AccessProject Report
A Wide-Area Deep Ocean Floor Mapping System: Design and Sea Tests
by
, , , , , , and
Geomatics 2023, 3(1), 290-311; https://doi.org/10.3390/geomatics3010016 - 22 Mar 2023
Cited by 2
Abstract
Mapping the seafloor in the deep ocean is currently performed using sonar systems on surface vessels (low-resolution maps) or undersea vessels (high-resolution maps). Surface-based mapping can cover a much wider search area and is not burdened by the complex logistics required for deploying
[...] Read more.
Mapping the seafloor in the deep ocean is currently performed using sonar systems on surface vessels (low-resolution maps) or undersea vessels (high-resolution maps). Surface-based mapping can cover a much wider search area and is not burdened by the complex logistics required for deploying undersea vessels. However, practical size constraints for a towbody or hull-mounted sonar array result in limits in beamforming and imaging resolution. For cost-effective high-resolution mapping of the deep ocean floor from the surface, a mobile wide-aperture sparse array with subarrays distributed across multiple autonomous surface vessels (ASVs) has been designed. Such a system could enable a surface-based sensor to cover a wide area while achieving high-resolution bathymetry, with resolution cells on the order of 1 m2 at a 6 km depth. For coherent 3D imaging, such a system must dynamically track the precise relative position of each boat’s sonar subarray through ocean-induced motions, estimate water column and bottom reflection properties, and mitigate interference from the array sidelobes. Sea testing of this core sparse acoustic array technology has been conducted, and planning is underway for relative navigation testing with ASVs capable of hosting an acoustic subarray.
Full article
(This article belongs to the Special Issue Advances in Ocean Mapping and Nautical Cartography)
►▼
Show Figures
Figure 1
Open AccessArticle
Curvature Weighted Decimation: A Novel, Curvature-Based Approach to Improved Lidar Point Decimation of Terrain Surfaces
by
, , , , and
Geomatics 2023, 3(1), 266-289; https://doi.org/10.3390/geomatics3010015 - 19 Mar 2023
Cited by 1
Abstract
►▼
Show Figures
Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often including large quantities of redundant points. Because of these large memory requirements, practitioners often use decimation to reduce the number of points used to create models. This paper introduces a
[...] Read more.
Increased availability of QL1/QL2 Lidar terrain data has resulted in large datasets, often including large quantities of redundant points. Because of these large memory requirements, practitioners often use decimation to reduce the number of points used to create models. This paper introduces a novel approach to improve decimation, thereby reducing the total count of ground points in a Lidar dataset while retaining more accuracy than Random Decimation. This reduction improves efficiency of downstream processes while maintaining output quality nearer to the undecimated dataset. Points are selected for retention based on their discrete curvature values computed from the mesh geometry of the TIN model of the points. Points with higher curvature values are preferred for retention in the resulting point cloud. We call this technique Curvature Weighted Decimation (CWD). We implement CWD in a new free, open-source software tool, CogoDN, which is also introduced in this paper. We evaluate the effectiveness of CWD against Random Decimation by comparing the resulting introduced error values for the two kinds of decimation over multiple decimation percentages, multiple statistical types, and multiple terrain types. The results show that CWD reduces introduced error values over Random Decimation when 15 to 50% of the points are retained.
Full article
Figure 1
Open AccessArticle
Feature Extraction and Classification of Canopy Gaps Using GLCM- and MLBP-Based Rotation-Invariant Feature Descriptors Derived from WorldView-3 Imagery
Geomatics 2023, 3(1), 250-265; https://doi.org/10.3390/geomatics3010014 - 16 Mar 2023
Abstract
►▼
Show Figures
Accurate mapping of selective logging (SL) serves as the foundation for additional research on forest restoration and regeneration, species diversification and distribution, and ecosystem dynamics, among other applications. This study aimed to model canopy gaps created by illegal logging of Ocotea usambarensis in
[...] Read more.
Accurate mapping of selective logging (SL) serves as the foundation for additional research on forest restoration and regeneration, species diversification and distribution, and ecosystem dynamics, among other applications. This study aimed to model canopy gaps created by illegal logging of Ocotea usambarensis in Mt. Kenya Forest Reserve (MKFR). A texture-spectral analysis approach was applied to exploit the potential of WorldView-3 (WV-3) multispectral imagery. First, texture properties were explored in the sub-band images using fused grey-level co-occurrence matrix (GLCM)- and local binary pattern (LBP)-based texture feature extraction. Second, the texture features were fused with colour using the multivariate local binary pattern (MLBP) model. The G-statistic and Euclidean distance similarity measures were applied to increase accuracy. The random forest (RF) and support vector machine (SVM) were used to identify and classify distinctive features in the texture and spectral domains of the WV-3 dataset. The variable importance measurement in RF ranked the relative influence of sets of variables in the classification models. Overall accuracy (OA) scores for the respective MLBP models were in the range of 80–95.1%. The respective user’s accuracy (UA) and producer’s accuracy (PA) for the univariate LBP and MLBP models were in the range of 67–75% and 77–100%, respectively.
Full article
Figure 1
Highly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Geomatics, Land, Remote Sensing, Urban Science, Water
Urban Land Use and Spatial Analysis
Topic Editors: Elahi Ehsan, Guo WeiDeadline: 2 February 2024
Topic in
Remote Sensing, Sensors, Smart Cities, Vehicles, Geomatics
Information Sensing Technology for Intelligent/Driverless Vehicle, 2nd Volume
Topic Editors: Yan Huang, Yi Ren, Penghui Huang, Jun Wan, Zhanye Chen, Shiyang TangDeadline: 31 May 2024
Topic in
Forests, Geomatics, Remote Sensing, Sensors
Information Fusion for Vegetation Characterization
Topic Editors: Baoxin Hu, Linhai JingDeadline: 30 June 2024
Topic in
Geomatics, IJGI
Geospatial Knowledge Graph
Topic Editors: Guohui Xiao, Yu Feng, Linfang Ding, Younes HamdaniDeadline: 1 August 2024
Conferences
Special Issues
Special Issue in
Geomatics
Advanced Geomatic Techniques for the Built Heritage: Data Processing, Interpretation and Knowledge Management
Guest Editors: Roberto Pierdicca, Francesco Di Stefano, Francesca MatroneDeadline: 29 February 2024
Special Issue in
Geomatics
Uncovering Earth System Processes through Satellite Remote Sensing and GIS
Guest Editors: Salvatore Stramondo, Roberto Battiston, Fawzi DoumazDeadline: 30 April 2024