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Geomatics, Volume 2, Issue 1 (March 2022) – 9 articles

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17 pages, 9876 KiB  
Article
Detection of Snow Cover from Historical and Recent AVHHR Data—A Thematic TIMELINE Processor
by Sebastian Rößler and Andreas J. Dietz
Geomatics 2022, 2(1), 144-160; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010009 - 18 Mar 2022
Cited by 3 | Viewed by 2546
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. [...] Read more.
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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19 pages, 9494 KiB  
Article
Determination of Satellite-Derived PM2.5 for Kampala District, Uganda
by Christine Atuhaire, Anthony Gidudu, Engineer Bainomugisha and Allan Mazimwe
Geomatics 2022, 2(1), 125-143; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010008 - 10 Mar 2022
Cited by 7 | Viewed by 3690
Abstract
Ground monitoring stations are widely used to monitor particulate matter (PM2.5). However, they are expensive to maintain and provide information localized to the stations, and hence are limited for large-scale use. Analysis of in situ PM2.5 shows that it varies [...] Read more.
Ground monitoring stations are widely used to monitor particulate matter (PM2.5). However, they are expensive to maintain and provide information localized to the stations, and hence are limited for large-scale use. Analysis of in situ PM2.5 shows that it varies spatially and temporally with distinct seasonal differences. This study, therefore, explored the use of satellite images (Sentinel-2 and Landsat-8) for determining the spatial and temporal variations in PM2.5 for Kampala District in Uganda. Firstly, satellite-derived aerosol optical depth (AOD) was computed using the Code for High Resolution Satellite mapping of optical Thickness and aNgstrom Exponent algorithm (CHRISTINE code). The derived AOD was then characterised with reference to meteorological factors and then correlated with in situ PM2.5 to determine satellite-derived PM2.5 using geographically weighted regression. In the results, correlating in situ PM2.5 and AOD revealed that the relationship is highly variable over time and thus needs to be modelled for each satellite’s overpass time, rather than having a generic model fitting, say, a season. The satellite-derived PM2.5 showed good model performance with coefficient of correlation (R2) values from 0.69 to 0.89. Furthermore, Sentinel-2 data produced better predictions, signifying that increasing the spatial resolution can improve satellite-derived PM2.5 estimations. Full article
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18 pages, 2441 KiB  
Article
Effects of Training Parameter Concept and Sample Size in Possibilistic c-Means Classifier for Pigeon Pea Specific Crop Mapping
by Priyadarsini Sivaraj, Anil Kumar, Shiva Reddy Koti and Parth Naik
Geomatics 2022, 2(1), 107-124; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010007 - 22 Feb 2022
Cited by 4 | Viewed by 2521
Abstract
This research work aims to study the effect of training parameter concept and sample size in the process of classification by using a fuzzy Possibilistic c-Means (PCM) approach for Pigeon Pea specific crop mapping. For specific class extraction, the “mean” of the [...] Read more.
This research work aims to study the effect of training parameter concept and sample size in the process of classification by using a fuzzy Possibilistic c-Means (PCM) approach for Pigeon Pea specific crop mapping. For specific class extraction, the “mean” of the training data is considered as a training parameter of the classification algorithm. In this study, we proposed an “Individual Sample as Mean” (ISM) approach where the individual training sample is accounted as a mean parameter for the fuzzy PCM classifier. In order to avoid the spectral overlap of target Pigeon pea crop with other crops in the study area, a temporal indices database was generated from Sentinel 2A/2B satellite images acquired during the 2019–2020 Pigeon Pea crop cycle. The spectral dimensionality of temporal data was reduced to extract the required bands to achieve maximum enhancement of the target crop class in the temporal data. Further, the training sample size was increased to study the heterogeneity within the class in the classified output. The proposed ISM approach delivered a higher mean membership difference (MMD) between the Pigeon Pea crop and the co-cultivated Cotton crop as compared to the conventional mean method. This indicated that a better separation was achieved between the target crop and the spectrally similar crop grown, that were cultivated in the same study area. When the sample size was gradually increased from 5 to 60, the MMD values within the Pigeon Pea test fields remained in the range 0.013–0.02, thereby implying that the proposed algorithm works better even with a small number of training samples. The heterogeneity was better handled using the proposed ISM approach since the variance obtained within Pigeon Pea field was only 0.008, as compared to that of 0.02 achieved using the conventional mean approach. Full article
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31 pages, 821 KiB  
Article
PBeL—A Novel Problem-Based (e-)Learning for Geomatics Students
by Guenther Retscher, Jelena Gabela and Vassilis Gikas
Geomatics 2022, 2(1), 76-106; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010006 - 22 Feb 2022
Viewed by 2798
Abstract
Due to the COVID-19 pandemic, distance learning had to be increasingly implemented at universities, and more e-learning formats had to be applied. The LBS2ITS project carried out under the lead of the Department of Geodesy and Geoinformation at TU Wien (TUW), Austria, came [...] Read more.
Due to the COVID-19 pandemic, distance learning had to be increasingly implemented at universities, and more e-learning formats had to be applied. The LBS2ITS project carried out under the lead of the Department of Geodesy and Geoinformation at TU Wien (TUW), Austria, came at the right time for these tasks. Education in Location-Based Services (LBS) is put to a new level including interactive e-learning and Problem-Based Learning (PBL) pedagogy. In the courses modernization, special attention is paid to the development and/or update of the courses to be implemented with these two pedagogic forms. Thus, teaching with an emphasis on learning outcomes is a central theme in the LBS2ITS project. To achieve this goal, the active verbs used in updated Bloom’s taxonomy for teaching on learning outcomes, i.e., remembering, understanding, applying, analyzing, evaluating, and creating, are applied to achieve the six levels of thinking and the active nature of learning. LBS2ITS will build a fully immersive and integrated LBS teaching and learning experience with the LBS application of Intelligent Transportation Systems (ITS) in mind. The outcome will be an innovative digital learning environment supporting synthetic and real-world PBL learning experiences. In the course of the project, a workshop for introduction of these new developments was held. This paper provides an insight into the results and experiences from this workshop. As e-learning and PBL must be combined and integrated nowadays, the new term PBeL (Problem-Based e-Learning) is proposed and introduced in this paper. The development of this approach and background information on the theory and the LBS2ITS project are presented. Full article
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23 pages, 4236 KiB  
Article
Multi-Objective Optimization Using Evolutionary Cuckoo Search Algorithm for Evacuation Planning
by Tomé Sicuaio, Olive Niyomubyeyi, Andrey Shyndyapin, Petter Pilesjö and Ali Mansourian
Geomatics 2022, 2(1), 53-75; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010005 - 22 Feb 2022
Cited by 3 | Viewed by 2449
Abstract
Proper emergency evacuation planning is a key to ensuring the safety and efficiency of resources allocation in disaster events. An efficient evacuation plan can save human lives and avoid other effects of disasters. To develop effective evacuation plans, this study proposed a multi-objective [...] Read more.
Proper emergency evacuation planning is a key to ensuring the safety and efficiency of resources allocation in disaster events. An efficient evacuation plan can save human lives and avoid other effects of disasters. To develop effective evacuation plans, this study proposed a multi-objective optimization model that assigns individuals to emergency shelters through safe evacuation routes during the available periods. The main objective of the proposed model is to minimize the total travel distance of individuals leaving evacuation zones to shelters, minimize the risk on evacuation routes and minimize the overload of shelters. The experimental results show that the Discrete Multi-Objective Cuckoo Search (DMOCS) has better and consistent performance as compared to the standard Multi-Objective Cuckoo Search (MOCS) in most cases in terms of execution time; however, the performance of MOCS is still within acceptable ranges. Metrics and measures such as hypervolume indicator, convergence evaluation and parameter tuning have been applied to evaluate the quality of Pareto front and the performance of the proposed algorithm. The results showed that the DMOCS has better performance than the standard MOCS. Full article
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1 pages, 146 KiB  
Editorial
Acknowledgment to Reviewers of Geomatics in 2021
by Geomatics Editorial Office
Geomatics 2022, 2(1), 52; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010004 - 28 Jan 2022
Viewed by 1617
Abstract
Rigorous peer-reviews are the basis of high-quality academic publishing [...] Full article
16 pages, 2993 KiB  
Article
Evaluating Scaling Frameworks for Multiscale Geomorphometric Analysis
by Daniel R. Newman, Jaclyn M. H. Cockburn, Lucian Drǎguţ and John B. Lindsay
Geomatics 2022, 2(1), 36-51; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010003 - 02 Jan 2022
Cited by 5 | Viewed by 2700
Abstract
Multiscale methods have become progressively valuable in geomorphometric analysis as data have become increasingly detailed. This paper evaluates the theoretical and empirical properties of several common scaling approaches in geomorphometry. Direct interpolation (DI), cubic convolution resampling (RES), mean aggregation (MA), local quadratic regression [...] Read more.
Multiscale methods have become progressively valuable in geomorphometric analysis as data have become increasingly detailed. This paper evaluates the theoretical and empirical properties of several common scaling approaches in geomorphometry. Direct interpolation (DI), cubic convolution resampling (RES), mean aggregation (MA), local quadratic regression (LQR), and an efficiency optimized Gaussian scale-space implementation (fGSS) method were tested. The results showed that when manipulating resolution, the choice of interpolator had a negligible impact relative to the effects of manipulating scale. The LQR method was not ideal for rigorous multiscale analyses due to the inherently non-linear processing time of the algorithm and an increasingly poor fit with the surface. The fGSS method combined several desirable properties and was identified as an optimal scaling method for geomorphometric analysis. The results support the efficacy of Gaussian scale-space as a general scaling framework for geomorphometric analyses. Full article
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19 pages, 9041 KiB  
Article
Vibration Analyses of a Gantry Structure by Mobile Phone Digital Image Correlation and Interferometric Radar
by Francesco Mugnai, Antonio Cosentino, Paolo Mazzanti and Grazia Tucci
Geomatics 2022, 2(1), 17-35; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010002 - 27 Dec 2021
Cited by 2 | Viewed by 2785
Abstract
The study presents results from applying the Real Aperture Radar interferometry technique and Digital Image Correlation through a mobile phone camera to identify static and dynamic deformations of a gantry during surveying operations on the Michelangelo’s David at the Galleria dell’Accademia di Firenze [...] Read more.
The study presents results from applying the Real Aperture Radar interferometry technique and Digital Image Correlation through a mobile phone camera to identify static and dynamic deformations of a gantry during surveying operations on the Michelangelo’s David at the Galleria dell’Accademia di Firenze Museum in Florence. The statue has considerable size and reaches an elevation of more than seven meters on its pedestal. An ad-hoc gantry was designed and deployed, given the cramped operating area around the statue. The scanner had a stability control system that forbid surveying in instrument movements. However, considering the unicity of the survey and its rare occurrence, the previous survey had been carried out in the year 2000; verifying stability and recording deformations is a crucial task, and necessary for validation. As the gantry does not have an on-board stability sensor, and considering the hi-survey accuracy requested, a redundant, contactless, remote monitoring system of the gantry and the statue stability was chosen to guarantee the maximum freedom of movement around the David to avoid any interference during scanning operations. Thanks to the TInRAR technique, the gantry and the statue were monitored with an accuracy of 0.01 mm. At the same time, a Digital Image Correlation analysis was performed on the gantry, which can be considered a Multi-Degree-Of-Freedom (MDOF) system, to accurately calculate the vibration frequency and amplitude. A comparison between TInRAR and DIC results reported substantial accordance in detecting gantry’s oscillating frequencies; a predominant oscillation frequency of 1.33 Hz was identified on the gantry structure by TinSAR and DIC analysis. Full article
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16 pages, 4480 KiB  
Review
Image Assisted Total Stations for Structural Health Monitoring—A Review
by Kira Zschiesche
Geomatics 2022, 2(1), 1-16; https://0-doi-org.brum.beds.ac.uk/10.3390/geomatics2010001 - 23 Dec 2021
Cited by 9 | Viewed by 4173
Abstract
Measuring structures and its documentation is one of the tasks of engineering geodesy. Structural health monitoring (SHM) is defined as a periodic or continuous method to provide information about the condition of the construction through the determination of measurement data and their analysis. [...] Read more.
Measuring structures and its documentation is one of the tasks of engineering geodesy. Structural health monitoring (SHM) is defined as a periodic or continuous method to provide information about the condition of the construction through the determination of measurement data and their analysis. In SHM, wide varieties of sensors are used for data acquisition. In the following, the focus is on the application of image assisted total stations (IATS). The combination of tacheometry and photogrammetric measurement offers high flexibility and precision. Different approaches of automated detecting and matching whose applications have been tested in practice are briefly explained. A distinction is made between built-in cameras (commercial) and external camera systems (prototypes). Various successful applications of IATS in the field of SHM are presented and explained. Full article
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