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An Approach to Improving GNSS Positioning Accuracy Using Several GNSS Devices (2021)

Jiménez-Martínez, María Jesús ; Farjas-Abadia, Mercedes ; Quesada-Olmo, Nieves

Molecular Diversity Preservation International

In: Remote Sensing. 2021; 13(6): 1149. Published 2021 Mar 17. doi: 10.3390/rs13061149.

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Publication Date: 2021-03-17

Description: Single point positioning (SPP) mode, related to pseudorange measurements, limits the level of accuracy to several meters in open sky and to several dozens of meters in urban canyons. This paper explores the effect of using a large number of SPP observations from low-cost global navigation system (GNSS) receivers, smartphones, and handheld GNSS units. Data segmentation and bootstrapping statistical methods were used to obtain the deviation, which can describe the accuracy of the large sample. The empirical test recording data showed that the error may achieve a sub-meter horizontal accuracy by the simple process of increasing the measurements of smartphones and handheld GNSS units. However, the drawback is the long period of time required. To reduce the satellite tracking time, a least squares solution network was applied over all the recorded data, assisted by the external geometric conditions. The final goal was to obtain the absolute positioning and associated deviations of one vertex from three or five GNSS receivers positioned on a network. The process was tested in three geodetic network examples. The results indicated that the enhanced SPP mode was able to improve its accuracy. Errors of several meters were reduced to values close to 50 cm in 25–37 min periods.

Electronic ISSN: 2072-4292

Topics: Architecture, Civil Engineering, Surveying , Geography

Published by Molecular Diversity Preservation International

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Influence of Soil Moisture vs. Climatic Factors in Pinus Halepensis Growth Variability in Spain: A Study with Remote Sensing and Modeled Data (2021)

González-Zamora, Ángel ; Almendra-Martín, Laura ; de Luis, Martín ; [et al.]

Molecular Diversity Preservation International

In: Remote Sensing. 2021; 13(4): 757. Published 2021 Feb 18. doi: 10.3390/rs13040757.

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Publication Date: 2021-02-18

Description: The influence of soil water content on Aleppo pine growth variability is analyzed against climatic variables, using satellite and modeled soil moisture databases. The study was made with a dendrochronological series of 22 forest sites in Spain with different environmental conditions. From the results of the correlation analysis, at both daily and monthly scales, it was observed that soil moisture was the variable that correlated the most with tree growth and the one that better identified the critical periods for this growth. The maximum correlation coefficients obtained with the rest of the variables were less than half of that obtained for soil moisture. Multiple linear regression analysis with all combinations of variables indicated that soil moisture was the most important variable, showing the lowest p-values in all cases. While identifying the role of soil moisture, it was noted that there was appreciable variability between the sites, and that this variability is mainly modulated by water availability, rather than thermal conditions. These results can contribute to new insights into the ecohydrological dynamics of Aleppo pine and a methodological approach to the study of many other species.

Electronic ISSN: 2072-4292

Topics: Architecture, Civil Engineering, Surveying , Geography

Published by Molecular Diversity Preservation International

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A Multi-Frequency SDR-Based GBSAR: System Overview and First Results (2021)

Amézaga, Adrià ; López-Martínez, Carlos ; Jové, Roger

Molecular Diversity Preservation International

In: Remote Sensing. 2021; 13(9): 1613. Published 2021 Apr 21. doi: 10.3390/rs13091613.

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Publication Date: 2021-04-21

Description: This work describes a system-level overview of a multi-frequency GBSAR built around a high performance software defined radio (SDR). The main goal of the instrument is to be employed as a demonstrator and experimental platform for multi-frequency GBSAR campaigns. The system is capable of operating in P, L, C and X-bands, and signal generation and digital signal processing are customizable and reconfigurable through software. An overview of the software and hardware and implementations of the system are presented. The operation of the system is demonstrated with two measuring campaigns showing focused amplitude images at different frequencies. It is shown how the usage of SDR for GBSAR systems is a viable design option.

Electronic ISSN: 2072-4292

Topics: Architecture, Civil Engineering, Surveying , Geography

Published by Molecular Diversity Preservation International

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An Integration of UAV-Based Photogrammetry and 3D Modelling for Rockfall Hazard Assessment: The Cárcavos Case in 2018 (Spain) (2021)

Gallo, Ilenia G. ; Martínez-Corbella, Mónica ; Sarro, Roberto ; [et al.]

Molecular Diversity Preservation International

In: Remote Sensing. 2021; 13(17): 3450. Published 2021 Aug 31. doi: 10.3390/rs13173450.

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Publication Date: 2021-08-31

Description: An example of the combined use of UAV photogrammetry and rockfall numerical simulation is described. A case of fragmental rockfall occurred on 17 November 2018 in Cárcavos, a site located in the Spanish municipality of Ayna (Albacete). The event caused a great social alarm as some infrastructure was affected. By using Unmanned Aerial Vehicle (UAV) photogrammetry, a high-resolution 3D model has been generated from point cloud data, and distribution and size of the fragmented rocks (more than 600 boulders) determined. The analysis has been performed through numerical simulations to: (1) reproduce the paths followed by the real blocks; and (2) estimate the speed and energy of the blocks, together with their heights, impacts and stopping points. Accordingly, source areas have been identified, including the potential source areas and unstable blocks on the slope. In addition, the exposed elements at risk (buildings, facilities, infrastructures, etc.) have been identified, and the effectiveness of mitigation measures against future events evaluated.

Electronic ISSN: 2072-4292

Topics: Architecture, Civil Engineering, Surveying , Geography

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Machine Learning Classification and Accuracy Assessment from High-Resolution Images of Coastal Wetlands (2021)

Martínez Prentice, Ricardo ; Villoslada Peciña, Miguel ; Ward, Raymond D. ; [et al.]

Molecular Diversity Preservation International

In: Remote Sensing. 2021; 13(18): 3669. Published 2021 Sep 14. doi: 10.3390/rs13183669.

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Publication Date: 2021-09-14

Description: High-resolution images obtained by multispectral cameras mounted on Unmanned Aerial Vehicles (UAVs) are helping to capture the heterogeneity of the environment in images that can be discretized in categories during a classification process. Currently, there is an increasing use of supervised machine learning (ML) classifiers to retrieve accurate results using scarce datasets with samples with non-linear relationships. We compared the accuracies of two ML classifiers using a pixel and object analysis approach in six coastal wetland sites. The results show that the Random Forest (RF) performs better than K-Nearest Neighbors (KNN) algorithm in the classification of pixels and objects and the classification based on pixel analysis is slightly better than the object-based analysis. The agreement between the classifications of objects and pixels is higher in Random Forest. This is likely due to the heterogeneity of the study areas, where pixel-based classifications are most appropriate. In addition, from an ecological perspective, as these wetlands are heterogeneous, the pixel-based classification reflects a more realistic interpretation of plant community distribution.

Electronic ISSN: 2072-4292

Topics: Architecture, Civil Engineering, Surveying , Geography

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