Classifying Forest Structure of Red-Cockaded Woodpecker Habitat Using Structure from Motion Elevation Data De-Rived from sUAS Imagery

Small unmanned aerial systems (sUAS) and relatively new photogrammetry software solutions are creating opportunities for forest managers to perform spatial analysis more efficiently and cost-effectively. This study aims to identify a method for leveraging these technologies to analyze vertical forest structure of red-cockaded woodpecker habitat in Montgomery County, Texas. Traditional sampling methods would require numerous hours of ground surveying and data collection using various measuring techniques. Structure from Motion (SfM), a photogrammetric method for creating 3-D structure from 2-D images, provides an alternative to relatively expensive LIDAR sensing technologies and can accurately model the high level of complexity found within our study area’s vertical structure. DroneDeploy, a photogrammetry processing app service, was used to post-process and create a point cloud, which was later further processed into a Canopy Height Model (CHM). Using supervised, object-based classification and comparing multiple classifier algorithms, classifications maps were generated with a best overall accuracy of 84.8% using Support Vector Machine in ArcGIS Pro software. Appropriately sized training sample datasets, correctly processed elevation data, and proper image segmentation were among the major factors impacting classification accuracy during the numerous classification iterations performed.

Demystifying the Differences between Structure-from-Motion Software Packages for Pre-Processing Drone Data

With the increased availability of low-cost, off-the-shelf drone platforms, drone data become easy to capture and are now a key component of environmental assessments and monitoring. Once the data are collected, there are many structure-from-motion (SfM) photogrammetry software options available to pre-process the data into digital elevation models (DEMs) and orthomosaics for further environmental analysis. However, not all software packages are created equal, nor are their outputs. Here, we evaluated the workflows and output products of four desktop SfM packages (AgiSoft Metashape, Correlator3D, Pix4Dmapper, WebODM), across five input datasets representing various ecosystems. We considered the processing times, output file characteristics, colour representation of orthomosaics, geographic shift, visual artefacts, and digital surface model (DSM) elevation values. No single software package was determined the “winner” across all metrics, but we hope our results help others demystify the differences between the options, allowing users to make an informed decision about which software and parameters to select for their specific application. Our comparisons highlight some of the challenges that may arise when comparing datasets that have been processed using different parameters and different software packages, thus demonstrating a need to provide metadata associated with processing workflows.

BALLCOURT REPRESENTATIONS IN QUIECHAPA, OAXACA, MEXICO: RITUAL OFFERING, FERTILITY, AND LIFE

During an archaeological survey in the municipality of San Pedro Mártir Quiechapa, Oaxaca, Mexico, archaeologists from the Proyecto Arqueológico de Quiechapa (PAQuie) encountered and documented a number of carved stone elements. Of particular interest are the 30 representations of ballcourts carved into natural rock outcrops at two sites in the region. This is the highest density in which this type of ballcourt representation occurs throughout Mesoamerica. After their initial discovery, members of PAQuie documented the carved stone ballcourts using structure-from-motion (SfM) photogrammetry, a quick and affordable technique to collect 3D spatial, quantitative, and visual data of stone carvings. In this article, I report on the carved stone ballcourt representations documented in the Quiechapa region and offer some preliminary interpretations. I first provide some description of the broader archaeological context in which the carvings were found. Then I describe the methods used to record the stone carvings, followed by a presentation of the data. Finally, in dialogue with extant literature, I explore some possibilities as to why these carved stone ballcourt representations were created, how they may have been used, and what they may symbolize.

Mapping Glacier Ablation With a UAV in the North Cascades: A Structure-from-Motion Approach

The glaciers of the North Cascades have experienced mass loss and terminus retreat due to climate change. The meltwater from these glaciers provides a flux of cold glacier meltwater into the river systems, which supports salmon spawning during the late summer dry season. The Nooksack Indian Tribe monitors the outlet flow of the Sholes Glacier within the North Cascades range with the goal of understanding the health of the glacier and the ability of the Tribe to continue to harvest sustainable populations of salmon. This study compares the UAV derived glacier ablation with the discharge data collected by the Tribe. We surveyed the Sholes Glacier twice throughout the 2020 melt season and, using Structure-from-Motion technology, generated high resolution multispectral orthomosaics and Digital Elevation Models (DEMs) of the glacier on each of the survey dates. The DEMs were differenced to reveal the surface height change of the glacier. The spectral data of the orthomosaics were used to conduct IsoData unsupervised classification. This process divided the survey area into Snow, Ice, and Rock classes that were then used to attribute the surface height changes of the DEMs to either snow or ice melt. The analysis revealed the glacier lost an average thickness of −0.132 m per day (m d−1) with snow and ice losing thickness at similar rates, −0.130 m d−1 and −0.132 m d−1 respectively. DEM differencing reveals that a total of −550,161 ± 45,206 m3 water equivalent (w.e.) was discharged into Wells Creek between the survey dates whereas the stream gauge station measured a total discharge of 350,023 m3. This study demonstrates the ability to spectrally classify the UAV data and derive discharge measurements while evaluating the small-scale spatial variability of glacier melt. Assessing ablation in small alpine glaciers is of great importance to downstream communities, like the Nooksack Indian Tribe who seek to understand the magnitude and timing of glacier melt in order to better protect their salmon populations. With this paper, we provide a baseline for future glacier monitoring and the potential to connect the snow surface properties with the rate of snow melt into a warming future.

Estimating herbaceous aboveground biomass in Sahelian rangelands using structure from motion data collected on the ground and by UAV

1.Herbaceous aboveground biomass (HAB) is a key indicator of grassland vegetation and indirect estimation tools, such as remote sensing imagery, increase the potential for covering larger areas in a timely and cost-efficient way. Structure from motion (SfM) is an image analysis process that can create a 3D model from a set of images. 2: Computed from UAV and ground camera measurements, the SfM potential to estimate the herbaceous aboveground biomass in Sahelian rangelands was tested in this study. Both UAV and ground camera recordings were used at three different scales: temporal, landscape and national (across Senegal). All images were processed using PIX4D software and were used to extract vegetation indices and heights. 3: A random forest algorithm was used to estimate the HAB and the average estimation errors were around 150 g.m-² for fresh mass (20% relative error) and 60 g.m-² for dry mass (around 25% error). A comparison between different datasets revealed that the estimates based on camera data were slightly more accurate than those from UAV data. 4:It was also found that combining datasets across scales for the same type of tool (UAV or camera) could be a useful option for monitoring HAB in Sahelian rangelands or in other grassy ecosystem.

The Feasibility of Using UAV Structure from Motion Photogrammetry to Extract HBIM of the Great Ziggurat of UR

Culture heritage reflects nation’s legacy and therefore should be protected from damage in order to pass it to future generations. Recently, such protection can be applied by 3D digitization techniques such as conservation, restoration, documentation, etc. The 3D digitalization of heritage assets has encountered numerous focus in the last two decades due to the development in data capturing techniques and technological advancement in 3D remote sensing (RS) approaches such as photogrammetry and laser scanning. However, the abundance of 3D information resources and spatial data modelling and analysis methods have urged stakeholders to adopt intelligent 3D data management system so called Building Information Modelling (BIM) to facilitate data approaching and management. Historic Building Information Model (HBIM) is a special case of the BIM system, however it reflects the possibility to apply the BIM technology to the historical and heritage buildings. In this research, Structure from motion (SfM) photogrammetric routine based on Unmanned Aerial Vehicles (UAVs) images was applied to build HBIM of the Great Ziggurat of Ur in the south of Iraq. Based on the 3D geometric and texturing information extracted through photogrammetry and the historical information provided, virtual reconstruction has been carried out using (HBIM) technology. This was achieved by applying realistic materials and texturing information in order to document the building, which is directed to investigate the feasibility of implementing image-based 3D modelling within HBIM environments. Restoring the missing parts of the Ziggurat temple was also a focus of this research by implementing reverse engineering methodologies based on available information considered within the extracted HBIM. This can successfully represent a complete virtual reality model and a management information system of the Ziggurat building to be passed to future generations. The work also includes data assessment and validation with the as-built model generated from reference measurements within Computer Aided Design (CAD) environment.

Experimental Study on 3D Measurement Accuracy Detection of Low Altitude UAV for Repeated Observation of an Invariant Surface

Low-altitude unmanned aerial vehicle (UAV) photogrammetry combined with structure-from-motion (SFM) algorithms is the latest technological approach to imaging 3D stereo constructions. At present, derivative products have been widely used in landslide monitoring, landscape evolution, glacier movement, volume measurement, and landscape change detection. However, there is still a lack of research into the accuracy of 3D data positioning based on the structure-from-motion of unmanned aerial vehicle (UAV-SFM) technology, itself, which can affect the measurable effectiveness of the results in further applications of this technological approach. In this paper, validation work was carried out for the DJI Phantom 4 RTK UAV, for earth observation data related to 3D positioning accuracy. First, a test plot with a relatively stable surface was selected for repeated flight imaging observations. Specifically, three repeated flights were performed on the test plot to obtain three sorties of images; the structure from motion and multi-view stereo (SFM-MVS) key technology was used to process and construct a 3D scene model, and based on this model the digital surface model (DSM) and digital orthophoto map (DOM) data of the same plot with repeated observations were obtained. In order to check the level of 3D measurement accuracy of the UAV technology itself, a window selection-based method was used to sample the point cloud set data from the three-sortie repeat observation 3D model. The DSM and DOM data obtained from three repeated flights over the surface invariant test plots were used to calculate the repeat observation 3D point errors, taking into account the general methodology of redundant observation error analysis for topographic surveys. At the same time, to further analyze the limits of the UAV measurement technique, possible under equivalent observation conditions with the same processing environment, a difference model (DOD) was constructed for the DSM data from three sorties, to deepen the overall characterization of the differences between the DSMs obtained from repeated observations. The results of the experimental study concluded that both the analysis of the 3D point set measurements based on window sampling and the accuracy evaluation using the difference model were generally able to achieve a centimeter level of planimetric accuracy and vertical accuracy. In addition, the accuracy of the surface-stabilized hardened ground was better, overall, than the accuracy of the non-hardened ground. The results of this paper not only probe the measurement limits of this type of UAV, but also provide a quantitative reference for the accurate control and setting of an acquisition scheme of the UAV-based SfM-MVS method for geomorphological data acquisition and 3D reconstruction.