Digital Recording of Historical Defensive Structures in Mountainous Areas Using Drones: Considerations and Comparisons

Barazzetti, Luigi; Previtali, Mattia; Cantini, Lorenzo; Oteri, Annunziata Maria

doi:10.3390/drones7080512

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…Krofcheck et al, 2019) and mavic 3 enterprise series (e.g. Barazzetti et al, 2023) becoming more accessible, the need for GCPs may become redundant (Tomaštík et al, 2019), opening the opportunity for more rapid data collection with fewer specialised equipment costs. However, in dense forest canopies, UAV-derived SfM data will suffer from lower penetration through the canopy due to a larger effective pixel size, meaning LiDAR data is likely to produce more accurate segmentation.…”

Section: F I G U R Ementioning

confidence: 99%

UAV‐derived greenness and within‐crown spatial patterning can detect ash dieback in individual trees

Flynn,

Grieve,

Henshaw

et al. 2024

Ecol Sol and Evidence

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Ash Dieback (ADB) has been present in the UK since 2012 and is expected to kill up to 80% of UK ash trees. Detecting and quantifying the extent of ADB in individual tree crowns (ITCs), which is crucial to understanding resilience and resistance, currently relies on visual assessments which are impractical over large scales or at high frequency. The improved imaging capabilities and declining cost of consumer UAVs, together with new remote sensing methods such as structure from motion photogrammetry (SfM) offers potential to quantify the fine‐scale structural and spectral metrics of ITCs that are indicative of ADB, rapidly, and at low‐cost. We extract high‐resolution 3D RGB point clouds derived from SfM of canopy ash trees taken monthly throughout the growing season at Marden Park, Surrey, UK, a woodland impacted by ADB. We segment ITCs, extract green chromatic coordinate (gcc), and test the relationship with visual assessments of crown health. Next, we quantify spatial patterning of dieback within ITCs by testing the relationship between internal variation of gcc and path length, a measure of the distance from foliage to trunk, for small clusters of foliage. We find gcc correlates with visual assessments of crown health throughout the growing season, but the strongest relationships are in measurements taken after peak greenness, when the effects of ADB on foliage are likely to be most prevalent. We also find a negative relationship between gcc and path length in infected trees, indicating foliage loss is more severe at crown extremities. We demonstrate a new method for identifying ADB at scale using a consumer‐grade 3D RGB UAV system and suggest this approach could be adopted for widespread rapid monitoring. We recommend the optimum time of year for data acquisition, which we find to be an important factor for detecting ADB. Although here applied to ADB, this framework is applicable to a multitude of drivers of crown dieback, presenting a method for identifying spectral‐structural relationships which may be characteristic of disturbance type.

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Section: F I G U R Ementioning

confidence: 99%

UAV‐derived greenness and within‐crown spatial patterning can detect ash dieback in individual trees

Flynn,

Grieve,

Henshaw

et al. 2024

Ecol Sol and Evidence

View full text Add to dashboard Cite

show abstract

“…Another example is related to the survey of an archaeological site, where the authors [41] used aerial photogrammetry (exploiting PPK technology) and TLS data, which were integrated employing the ICP algorithm. Lastly, the authors of [42] surveyed historical defensive structures in mountainous areas. They used traditional photogrammetric solutions and novel methods based on Neural Radiance Fields (NeRFs).…”

Section: Rtk and Ppk Technologies For Uavsmentioning

confidence: 99%

Drones and Real-Time Kinematic Base Station Integration for Documenting Inaccessible Ruins: A Case Study Approach

Treccani,

Adami,

Fregonese

2024

Drones

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Ruins, marked by decay and abandonment, present challenges for digital documentation due to their varied conditions and remote locations. Surveying inaccessible ruins demands innovative approaches for safety and accuracy. Drones with high-resolution cameras enable the detailed aerial inspection and imaging of these inaccessible areas. This study investigated how surveying technologies, particularly Unmanned Aerial Vehicles (UAVs), are used to document inaccessible ruins. Integration with Real-Time Kinematic (RTK) technologies allows direct georeferencing in photogrammetric processing. A case study of the Castle of Terracorpo in Italy was used to demonstrate UAV-only surveying feasibility in inaccessible environments, testing two different scenarios. The first scenario involved the use of a DJI Matrice 300 RTK coupled with the D-RTK2 base station to survey the Castle; both direct and indirect georeferencing were exploited and compared through the photogrammetric process. This first scenario confirmed that this approach can lead to a centimetre-level accuracy (about three times the GSD value for indirect georeferencing and seven times the GSD value for direct georeferencing exploting RTK). The second scenario testing the integration of data from drones at varying resolutions enabled the comprehensive coverage of ruinous structures. In this case, the photogrammetric survey performed with the dji Mavic 3 Cine drone (indirect georeferencing) was integrated with the photogrammetric survey performed with the dji Matrice 300 RTK drone (direct georeferencing). This scenario showed that GCPs extracted from a direct georeferencing photogrammetric survey could be successfully used to georeference and integrate other drone data. However, challenges persist in surveying underground or enclosed spaces that are inaccessible to UAVs. Future research will explore integrating robotic LiDAR survey systems and advanced data fusion techniques to enhance documentation.

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Near-Complete Sampling of Forest Structure from High-Density Drone Lidar Demonstrated by Ray Tracing

Zhang,

Král,

Krůček

et al. 2024

Remote Sensing

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Drone lidar has the potential to provide detailed measurements of vertical forest structure throughout large areas, but a systematic evaluation of unsampled forest structure in comparison to independent reference data has not been performed. Here, we used ray tracing on a high-resolution voxel grid to quantify sampling variation in a temperate mountain forest in the southwest Czech Republic. We decoupled the impact of pulse density and scan-angle range on the likelihood of generating a return using spatially and temporally coincident TLS data. We show three ways that a return can fail to be generated in the presence of vegetation: first, voxels could be searched without producing a return, even when vegetation is present; second, voxels could be shadowed (occluded) by other material in the beam path, preventing a pulse from searching a given voxel; and third, some voxels were unsearched because no pulse was fired in that direction. We found that all three types existed, and that the proportion of each of them varied with pulse density and scan-angle range throughout the canopy height profile. Across the entire data set, 98.1% of voxels known to contain vegetation from a combination of coincident drone lidar and TLS data were searched by high-density drone lidar, and 81.8% of voxels that were occupied by vegetation generated at least one return. By decoupling the impacts of pulse density and scan angle range, we found that sampling completeness was more sensitive to pulse density than to scan-angle range. There are important differences in the causes of sampling variation that change with pulse density, scan-angle range, and canopy height. Our findings demonstrate the value of ray tracing to quantifying sampling completeness in drone lidar.

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Digital Recording of Historical Defensive Structures in Mountainous Areas Using Drones: Considerations and Comparisons

Cited by 4 publications

References 30 publications

UAV‐derived greenness and within‐crown spatial patterning can detect ash dieback in individual trees

UAV‐derived greenness and within‐crown spatial patterning can detect ash dieback in individual trees

Drones and Real-Time Kinematic Base Station Integration for Documenting Inaccessible Ruins: A Case Study Approach

Near-Complete Sampling of Forest Structure from High-Density Drone Lidar Demonstrated by Ray Tracing

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