SFM-MVS photogrammetry for rockfall analysis and hazard assessment along the ancient roman via Flaminia road at the Furlo gorge (Italy)

Rockfall events represent significant hazards for areas characterized by high and steep slopes and therefore effective mitigation controls are essential to control their effect. There are a lot of examples all over the world of anthropic areas at risk because of their proximity to a rock slope. A rockfall runout analysis is a typical 3D problem, but for many years, because of the lack of specific software, powerful computers, and economic reasons, a 2D approach was normally adopted. However, in recent years the use of 3D software has become quite widespread and different runout working approaches have been developed. The contribution and potential use of photogrammetry in this context is undoubtedly great. This paper describes the application of a 3D hybrid working approach, which considers the integrated use of traditional geological methods, Terrestrial Laser Scanning, and drone based Digital Photogrammetry. Such approach was undertaken in order to perform the study of rockfall runout and geological hazard in a natural slope in Italy in correspondence of an archaeological area. Results show the rockfall hazard in the study area and highlights the importance of using photogrammetry for the correct and complete geometrical reconstruction of slope, joints, and block geometries, which is essential for the analysis and design of proper remediation measures

Underpass clearance checking in highway widening projects using digital twins

Main road widening can reduce the clearance of the low-level underpass road, restricting the passage of vehicles and leading to collisions with structures. Therefore, checking the clearance of the underpass road effectively should be considered at the design stage. This paper describes a digital twin approach for checking the clearance of underpass roads in highway widening projects using online map data. The underpass road digital twin and BIM model of the newly widened road based on the existing main road digital twin are created to assist the clearance check and redesign. The proposed method presented a cost-effective clearance check for underpass roads in road widening design without field surveys and was successfully implemented in an underpass road in the UK. In future research, more digital twin methods for overpasses, bridges, tunnels, and traffic safety facilities should be employed comprehensively to assist more road widening applications

Towards quantifying the effects of resource extraction on land cover and topography through remote sensing analysis: Confronting issues of scale and data scarcity

This dissertation focuses on the mapping and monitoring of mineral mining activity using remotely sensed data. More specifically, it explores the challenges and issues associated with remote sensing-based analysis of land use land cover (LULC) and topographic changes in the landscape associated with artisanal and industrial-scale mining. It explores broad themes of image analysis, including evaluation of error in digital elevation models (DEMs), integration of multiple scales and data sources, quantification of change, and remote sensing classification in data-scarce environments. The dissertation comprises three case studies.;The first case study examines the LULC change associated with two scales of mining activity (industrial and artisanal) near Tortiya, Cote d\u27Ivoire. Industrial mining activity was successfully mapped in a regional LULC classification using Landsat multispectral imagery and support vector machines (SVMs). However, mapping artisanal mining required high-resolution imagery to discriminate the small, complex patterns of associated disturbance.;The second case study is an investigation of the potential for quantifying topographic change associated with mountain top removal mining and the associated valley-fill operations for a region in West Virginia, USA, using publicly available DEMs. A 1:24,000 topographic map data, the shuttle radar topography mission (SRTM) DEM, a state-wide photogrammetric DEM, and the Advanced Spaceborne Thermal Emission Radiometer (ASTER) Global DEM (GDEM) were compared to a lidar bare-earth reference DEM. The observed mean error in both the SRTM and GDEM was statistically different than zero and modeled a surface well above the reference DEM surface. Mean error in the other DEMs was lower, and not significantly different than zero. The magnitude of the root mean square error (RMSE) suggests that only topographic change associated with the largest topographic disturbances would be separable from background noise using global DEMS such as the SRTM. Nevertheless, regionally available DEMs from photogrammetric sources allow mapping of mining change and quantification of the total volume of earth removal.;Monitoring topographic change associated with mining is challenging in regions where publicly available DEMs are limited or not available. This challenge is particularly acute for artisanal mining, where the topographic disturbance, though locally important, is unlikely to be detected in global elevation data sets. Therefore, the third and final case study explored the potential for creating fine-spatial resolution bare-earth DEMs from digital surface models (DSMs) using high spatial resolution commercial satellite imagery and subsequent filtering of elevation artifacts using commercial lidar software and other spatial filtering techniques. Leaf-on and leaf-off DSMs were compared to highlight the effect of vegetation on derived bare-earth DEM accuracy. The raw leaf-off DSM was found to have very low error overall, with notably higher error in areas of evergreen vegetation. The raw leaf-on DSM was found to have a RMSE error much higher than the leaf-off data, and similar to that of the SRTM in dense deciduous forest. However, filtering using the commercial techniques developed for lidar notably reduced the error present in the raw DSMs, suggesting that such approaches could help overcome data scarcity in regions where regional or national elevation data sets are not available.;Collectively this research addressed data issues and methodological challenges in the analysis of 3D changes caused by resource extraction. Elevation and optical imagery are key data sets for mapping the disturbance associated with mining. The particular combination required regarding data spatial scale, and for elevation, accuracy, is a function of the type and scale of the mining

Accelerating Spatial Data Processing with MapReduce

Abstract—MapReduce is a key-value based programming model and an associated implementation for processing large data sets. It has been adopted in various scenarios and seems promising. However, when spatial computation is expressed straightforward by this key-value based model, difficulties arise due to unfit features and performance degradation. In this paper, we present methods as follows: 1) a splitting method for balancing workload, 2) pending file structure and redundant data partition dealing with relation between spatial objects, 3) a strip-based two-direction plane sweep-ing algorithm for computation accelerating. Based on these methods, ANN(All nearest neighbors) query and astronomical cross-certification are developed. Performance evaluation shows that the MapReduce-based spatial applications outperform the traditional one on DBMS

Monitoring the dune-beach system of Guardamar del Segura (Spain) using UAV, SfM and GIS techniques

Dune ecosystems play a key role in coastal dynamics, so it is essential to measure their movements with high precision and monitor their changes over time. It is crucial to have a system that allows us to know the natural and anthropic impacts affecting these ecosystems. The aim of this study is to ascertain the historical evolution of the dune system of Guardamar del Segura (Spain) and its relationship with coastal erosion. Likewise, it is also intended to assess the state of the foredune restoration works carried out in 2011. To this end, a comparison of existing cartographic data has been undertaken by using geospatial analysis techniques through Geographic Information Systems (GIS). As a novelty, a low takeoff weight UAV (Unmanned Aerial Vehicle) has been used to produce a high-precision 3D model from two-dimensional images using photogrammetric techniques, such as Structure from Motion (SfM). This technique made it possible to obtain a digital terrain model of high density and precision (30 pt/m2 and RMSE Z of 0.173 m). The results show a constant erosion of both the beach and the foredune, with an overall loss of 143,561 m3 of material in the period analyzed (2001–2017). The anthropogenic restoration actions executed within this period have not been effective. In fact, erosion has increased in the period 2016–2017, with a significant reduction in the beach width and sea waves directly affecting the foredune. The main conclusion is that the combined use of UAV and SfM techniques is an excellent procedure to periodically supervise dune ecosystems with high precision and significant time and cost savings

Modeling spatial uncertainties in geospatial data fusion and mining

Geospatial data analysis relies on Spatial Data Fusion and Mining (SDFM), which heavily depend on topology and geometry of spatial objects. Capturing and representing geometric characteristics such as orientation, shape, proximity, similarity, and their measurement are of the highest interest in SDFM. Representation of uncertain and dynamically changing topological structure of spatial objects including social and communication networks, roads and waterways under the influence of noise, obstacles, temporary loss of communication, and other factors. is another challenge. Spatial distribution of the dynamic network is a complex and dynamic mixture of its topology and geometry. Historically, separation of topology and geometry in mathematics was motivated by the need to separate the invariant part of the spatial distribution (topology) from the less invariant part (geometry). The geometric characteristics such as orientation, shape, and proximity are not invariant. This separation between geometry and topology was done under the assumption that the topological structure is certain and does not change over time. New challenges to deal with the dynamic and uncertain topological structure require a reexamination of this fundamental assumption. In the previous work we proposed a dynamic logic methodology for capturing, representing, and recording uncertain and dynamic topology and geometry jointly for spatial data fusion and mining. This work presents a further elaboration and formalization of this methodology as well as its application for modeling vector-to-vector and raster-to-vector conflation/registration problems and automated feature extraction from the imagery