Aerial Surveys Research Articles

Experience in assessing the abundance and spatial distribution of geese on the Taimyr Peninsula using the aerial survey method

The Taimyr Peninsula is a key region for reproduction of waterfowl of European and Asian wintering populations. The uniqueness of Taimyr is that birds migrate there from both the west and the east, following five out of eight global flyways: East Atlantic, Black Sea/Mediterranean, West Asian/East African, Central Asian, and East Asian/Australasian. The study develops the topic of conservation ornithology and sustainable use of biological resources raised at the First All-Russian Ornithological Congress by Dr. Evgeny Syroechkovsky. Russia lacks the system of state monitoring and assessment of waterfowl populations, in particular with the use of aerial survey methods. In 2019, counts of geese in the tundra zone of the Taimyr Peninsula were carried out from the board of an ultralight aircraft specially designed for aerial surveys. New data on the abundance and spatial distribution of geese were obtained. We substantiated the methodology for the survey flight routing with no transects and the use of GIS, remote sensing, and generalized additive models (GAM) for interpreting the results and extrapolating estimates of goose abundance. A database of the results of aerial surveys was compiled (http://rggsurveys.ru). According to our estimate, for the first time made by statistical modeling for the tundra zone of the Taimyr Peninsula, more than 1.5 million White-fronted geese, about 450000 Bean geese, 78400 Red-breasted geese, and 43000 Lesser White-fronted geese nest and moult on Taimyr. Comparison of these figures with modern estimates of the world populations of these species demonstrates the key role of the Taimyr Peninsula in maintaining populations of rare and economically important Anseriformes.

Tritium Autrigonum (Monasterio de Rodilla, BURGOS): an urban approach to a Hispano-Roman agglomeration based on recent aerial surveys

The ancient town located at Alto de Rodilla (Monasterio de Rodilla, Burgos, Spain), identified as Tritium Autrigonum, has never been the subject of an archeological excavation, although the site has been known for a long time. However, the aerial survey campaigns conducted between 2001 and 2015 made it possible to take a large number of photographs that expose the urban form of the city. They reveal, on an unprecedented scale, a significant portion of the buried structures throughout the agglomeration. After a brief presentation of the site and the extent of our current knowledge, this work details the exploitation of the rectified and georeferenced aerial views, making it possible to obtain an unedited planimetry of the remains. It also provides an exceptionally detailed description of the site. This expanding documentary base was used in 2016 to study the remains identified as monuments. Since then, the analysis of the analysis of the aerial photographs has made it possible to obtain a general plan of the city, the various facets of its urbanism in its various aspects and to situate the city within the urban spaces of the northern Hispanic area.

Оценка трещиноватости отрабатываемого горного массива на основе аэрофотосъемки и методов машинного зрения

The task to assess rock mass jointing are currently usually solved in manual mode, which requires high qualification of the specialists and considerable time expenditures. Automation of such tasks is important in terms of reducing the time of image processing and obtaining additional information on the geomechanical state of the rock mass. The article discusses the possibilities of using computer vision and artificial intelligence technologies to assess jointing of the rock mass. For this purpose, aerial photography data obtained using unmanned aerial vehicles are used. The images are processed with the software developed by the authors, which performs tracing of the joints based on a neural network of a dedicated architecture. The results of processing aerial photography data are presented using the cases of coal strip mines in Kuzbass and open-pit mines of the Kola Peninsula. The use of neural network in processing of the aerial survey data of the rock masses has shown the promising potential of the method. After processing the data of tracing the jointing fields, it becomes possible to monitor the behavior of the rock mass by using the visualization tools for additional fields of characteristics, which allow to assess the nature of changes occurring under anthropogenic loads. The developed algorithms make it possible to significantly accelerate the processes of aerial survey data processing to assess the structural disturbance of the rock mass.

The Detection of Tree of Heaven (Ailanthus altissima) Using Drones and Optical Sensors: Implications for the Management of Invasive Plants and Insects

Tree of heaven (Ailanthus altissima) is a highly invasive tree species in the USA and the preferred host of an invasive insect, the spotted lanternfly (Lycorma delicatula). Currently, pest managers rely solely on ground surveys for detecting both A. altissima and spotted lanternflies. This study aimed to develop efficient tools for A. altissima detection using drones equipped with optical sensors. Aerial surveys were conducted to determine the optimal season, sensor type, and flight altitudes for A. altissima detection. The results revealed that A. altissima can be detected during different seasons and at specific flight heights. Male inflorescences were identifiable using an RGB sensor in the spring at <40 m, seed clusters were identifiable in summer and fall at <25 m using an RGB sensor, and remnant seed clusters were identifiable in the winter at <20 m using RGB and thermal sensors. Combining all seasonal data allowed for the identification of both male and female A. altissima. This study suggests that employing drones with optical sensors can provide a near real-time and efficient method for A. altissima detection. Such a tool has the potential to aid in the development of effective strategies for monitoring spotted lanternflies and managing A. altissima.

Quantifying the Impact of Hurricane Harvey on Beach−Dune Systems of the Central Texas Coast and Monitoring Their Changes Using UAV Photogrammetry

Historically, the Texas Gulf Coast has been affected by many tropical storms and hurricanes. The most recent severe impact was caused by Hurricane Harvey, which made landfall in August 2017 on the central Texas coast. We evaluated the impact of Hurricane Harvey on the barrier islands of the central Texas coast, including San Jose Island, Mustang Island, and North Padre Island. We used public data sets, including 1 m resolution bare-earth digital elevation models (DEMs), derived from airborne lidar acquisitions before (2016) and after (2018) Hurricane Harvey, and sub-meter scale aerial imagery pre- and post-Harvey to evaluate changes at a regional scale. Shoreline proxies were extracted to quantify shoreline retreat and/or advance, and DEM differencing was performed to quantify net sediment erosion and accretion or deposition. Unmanned aerial vehicle surveys were conducted at each island to produce high-resolution (cm scale) imagery and topographic data used for morphological and change analyses of beaches and dunes at the local scale. The results show that Hurricane Harvey caused drastic local shoreline retreat, reaching 59 m, and significant erosion levels of beach−dune elements immediately after its landfall. Erosion and recovery processes and their levels were influenced by the local geomorphology of the beach−foredune complexes. It is also observed that local depositional events contributed to their post-storm rebuilding. This study aims to enhance the understanding of major storm impacts on coastal areas and help in future protection planning of the Texas coast. It also has broader implications for coastlines on Earth affected by major storms.

Six Decades of Changes in Pool Characteristics on a Concentric-Patterned Raised Bog

AbstractRaised bogs are wetland ecosystems which, under the right climatic conditions, feature patterns of pool hollows and hummock ridges. The relative cover and the spatial arrangement of pool and ridge microforms are thought to be influential on peatland atmosphere carbon gas fluxes and plant biodiversity. The mechanisms responsible for the formation and maintenance of pools, and the stability of these features in response to warming climates, remain topics of ongoing research. We employed historical aerial imagery, combined with a contemporary uncrewed aerial vehicle survey, to study 61 years of changes in pools at a patterned raised bog in central Sweden. We used a pool inheritance method to track individual pools between image acquisition dates throughout the time series. These data show a rapid loss of open-water pool area during the study period, primarily due to overgrowth of open-water pools by Sphagnum. We postulate that these changes are driven by ongoing climate warming that is accelerating Sphagnum colonisation. Open-water pool area declined by 26.8% during the study period, equivalent to a loss of 1001 m2 y−1 across the 150-hectare site. This is contradictory to an existing theory that states pools are highly stable, once formed, and can only convert to a terrestrial state through catastrophic drainage. The pool inheritance analysis shows that smaller pools are liable to become completely terrestrialised and expire. Our findings form part of a growing body of evidence for the loss of open-water habitats in peatlands across the boreal and elsewhere.

Investigation of fractured rock beneath a uranium-tailing storage dam through UAV digital photogrammetry and seismic refraction tomography

Failure events in dams can be associated with processes in the dam body and in the foundation of the structure. If they are properly identified in early stages, corrective actions can take place, leading to a reduction in the risk of collapse and/or rupture of the dam. Most studies on dams are carried out on the body of the dam; however, problems associated with the foundation of the structure can also lead to loss of stability and subsequent ruptures. This study presents an analysis of the advantages and limitations of the use of seismic refraction in hydrogeological studies of fractured aquifers under pressure from large loads, specifically a dam in this case. Seismic refraction data were collected on an outcrop of fractured rock near a uranium storage dam foundation in southeastern Brazil. The results and interpretations were supported by a structural analysis performed through manual strike measurements collected with a Clark compass and an uncrewed aerial vehicle digital photogrammetry survey in an outcrop. The digital photogrammetric survey mapped the spatial distribution and orientation of the geological structures of the rock mass. Although the structural measurements performed through digital photogrammetry presented greater variability than the measurements collected from the compass, the maximum density of the fracture measurements obtained from both methods were similar and were corroborated by the regional and local fracture patterning. The integration of seismic refraction data with geotechnical and geological investigations allowed us to identify the positioning of structural lineaments in the rock mass and zones with a higher degree of rock alteration. The identification of highly fractured zones in the rock mass from such non-invasive investigations could be used to assist in decision making for structural reinforcements in the foundation of the dam to avoid the loss of stability at the foot of the dam from possible leaks or water flows from the reservoir.

Accuracy comparison of mobile mapping system for road inventory

Mobile Mapping Systems (MMSs) stand out as the preferred solution for achieving highly precise 3D environmental models, particularly in urban planning, highway mapping, asset inventory, corridor mapping, traffic safety evaluation, autonomous vehicle, digital twin, and emergency response mapping where traditional aerial or satellite surveys often fall short in providing precise data. Understanding the intricate factors that impact the accuracy of mobile mapping is pivotal to harnessing the full potential of this advanced measurement technique. This study analyzes the spatial accuracy of geographical data produced by the mobile mapping method, considering factors such as the speed of the mobile mapping tool, measurement time difference, camera shooting distance of the produced data, and differences in picture shooting distances. The acquired results were examined for their applicability in the production of inventory along the highway route, revealing their practical usability through analysis and findings. This investigation delves into the proficiency and precision benchmarks of mobile mapping systems, specifically in the context of creating road inventory and supporting decision-making for road systems. The study discusses the usability and accuracy criteria of mobile mapping systems for creating transportation inventory and decision support systems.

Review of discrete fracture network characterization for geothermal energy extraction

Geothermal reservoirs are highly anisotropic and heterogeneous, and thus require a variety of structural geology, geomechanical, remote sensing, geophysical and hydraulic techniques to inform Discrete Fracture Network flow models. Following the Paris Agreement on reduction of carbon emissions, such reservoirs have received more attention and new techniques that support Discrete Fracture Network models were developed. A comprehensive review is therefore needed to merge innovative and traditional technical approaches into a coherent framework to enhance the extraction of geothermal energy from the deep subsurface. Traditionally, statistics extracted from structural scanlines and unmanned aerial vehicle surveys on analogues represent optimum ways to constrain the length of joints, bedding planes, and faults, thereby generating a model of the network of fractures. Combining borehole images with seismic attributes has also proven to be an excellent approach that supports the stochastic generation of Discrete Fracture Network models by detecting the orientation, density, and dominant trends of the fractures in the reservoirs. However, to move forward to flow modelling, computation of transmissivities from pumping tests, and the determination of hydraulically active fractures allow the computation of the hydraulic aperture in permeable sedimentary rocks. The latter parameter is fundamental to simulating flow in a network of discrete fractures. The mechanical aperture can also be estimated based on the characterization of geomechanical parameters (Poisson’s ratio, and Young’s modulus) in Hot Dry Rocks of igneous-metamorphic origin. Compared with previous review studies, this paper will be the first to describe all the geological and hydro-geophysical techniques that inform Discrete Fracture Network development in geothermal frameworks. We therefore envisage that this paper represents a useful and holistic guide for future projects on preparing DFN models.

ASSESSING THE ACCURACY OF UAV SURVEYS WITH DIFFERENT CONFIGURATIONS

Abstract. Recently, developments in airborne sensors and easy-to-fly, reliable, low-cost commercial UAVs have opened a new era for precise aerial mapping. The restricted payload capacity of low-cost UAVs imposes constraints on the quality of their navigation systems and the sensors they can carry. Therefore, the quality of photogrammetric products generated from UAV surveys needs to be assessed. In this study, photogrammetric mapping principles are employed in collecting, processing, and analyzing optical images collected using two UAV surveying systems. The first system was a 3DR Iris+ drone flying at 25 meters above the ground. The second system was a homemade drone similar to Tuffwing flying at about 70 meters above the ground. Both systems carried a Canon PowerShot S100 using a fixed 5.2 focal length. About 30 ground points were surveyed with a TS02 total station and served as the ground truth for data evaluation. After the flights, data was proceeded and geospatial products including DEMs and orthophotos produced were evaluated. Different ground control configurations were examined and ground check-points were used to evaluate the final accuracy of the geospatial products. The comparison of the derived 3D information from captured data with ground measurements showed a high correlation between the accuracy of the 3D products and the sensor specification, flying altitude, as well as image layout. This was supported by comparisons between actual errors and theoretical positional precision based on flying height, photo scale and air base was conducted.

High‐resolution model reconstruction and bridge damage detection based on data fusion of unmanned aerial vehicles light detection and ranging data imagery

AbstractDamage detection is essential for the maintenance of transportation infrastructure that experiences high daily traffic levels in potentially extreme environments and changes in use patterns. However, traditional physical inspection is always labor‐intensive, subjective, and biased, lacking the objective perspective required for a comprehensive and reliable assessment. Recently, unmanned aerial vehicles (UAVs) combined with emerging high‐performance sensor(s) have been intensively researched. Here, we present an aerial bridge surface survey method that can be used to assess damage. Existing damage detection methods focus on single types of damage and are limited in locating global damage, whereas our method detects two types of damage on the surface and marks them in a panoramic image. The workflow involves three steps: data acquisition using a meticulous UAV flight strategy that covers the entire surface, data processing using image‐based and point‐cloud models after polynomial rectification, and data output (i.e., damage detected by the combined models). To verify the method, a field test detected damage to two real bridges. A UAV equipped with a camera and light detection and ranging (LiDAR) equipment was employed. Experiments demonstrate the effectiveness of the proposed method, which is capable of producing accurate outputs and detecting damage with an average position error of 13.37 mm and a relative size error of 25.25%. Owing to the data fusion model taking advantage of two‐dimensional (2D) images and 3D LiDAR data, it outputs a high‐resolution 3D model and avoids environmental disturbances. After decision‐making‐level damage fusion, all position and size properties of damage information are computed into a panoramic damage image. This panoramic image showing all detecting damage helps technicians perform maintenance; the image can be zoomed to focus on any issue individually.

Недеструктивно археологическо проучване в местността „Долната чатма“ при село Велино, Шуменско

In the late autumn of 2022, a non-destructive archaeological survey was carried out in the territory of Velino village, Shumen municipality. The survey went through several stages: 1) collection of preliminary information on the names of localities and toponyms in the area of the survey; 2) conducting a field survey during which accumulations of large unprocessed stones and a relatively large concentration of fragmented Old Bulgarian household ceramics were registered; 3) aerial photogrammetric survey of the terrain, as a result of which a digital elevation model and an ortho-photo plan of the area designated for study were produced. The contours of linear structures of artificial origin were clearly visible; 4) geophysical survey in four zones, which confirmed the proposals for the presence of anomalous zones; 5) vertical electric sounding with the aim of studying the stratigraphy of the object during which it was established that the structures probably develop at a depth of 0.80-1.00 m from the contemporary terrain. The results of the non-destructive archaeological survey in Dolnata Chatma locality, near the village of Velino, Shumen region show that linear stone structures develop on the flat terrace east of the village, probably part of a presumed archaeological object. At this stage, its scope, chronology and character are not clarified, and this remains a task for the team in future exploratory and subsequently regular archaeological surveys.

Efficacy evaluation of apple sunburn mitigation techniques in WA 38 cultivar using crop physiology sensing system

This study evaluated the efficacy of two heat stress mitigation techniques, i.e., modified evaporative cooling (EC), and drape/shade net (SN) against untreated control (UC) in terms of fruit surface temperature (FST) suppression and internal fruit quality for cv. WA 38. The EC treatment used foggers (flow rate: 4.1 L s−1 ha−1) spaced at 3.3 m along the row to create mist within the canopy. The experiment was conducted in a 0.2 acre block planted on two randomly distributed rootstocks [Geneva 41 (G41) and Malling 9-Nic 29 (M9)], trained in a bi-axis vertical wall architecture. Treatments were divided into three sub-blocks. Alternate wet and dry zones were observed in the sub-block treated with fogger-based EC and was therefore subdivided into EC-Wet and EC-Dry treatments. The proximal thermal-RGB imaging and in-field weather sensing integrated crop physiology sensing system (CPS2.0) was upgraded with edge computing capability to monitor real-time apple FST, an indicator of heat stress. Deployed nodes monitored imagery and weather data based FST in each treatment at an interval of 5-min throughout the growing season (i.e., during fruit maturation). Aerial imagery-based canopy temperature mapping with ground sampling distance of 4 cm/pixel was also utilized to monitor the canopy heat stress at key growth stages. CPS2.0 imagery derived apple FST was effectively reduced by EC-Wet (G41: 27.1 ± 0.4 and M9: 28.8 ± 0.4 °C) (mean ± std. error) and SN (G41: 29.8 ± 0.2 and M9: 30.5 ± 0.1 °C) treatments compared to the UC (G41: 33.1 ± 0.2 and M9: 31.4 ± 0.4 °C) throughout the production season. However, convective cooling from EC-Dry (G41: 33.1 ± 0.2 and M9: 32.5 ± 0.2 °C) treatment failed to mitigate heat stress. Results suggest that fogger spacing, and orientation need adjustments along tree-rows for effective sunburn management. Overall, canopy temperature quantified by aerial imagery was significantly lower under modified EC (30.3 ± 1.3 °C) than UC (34.2 ± 1.3 °C) treatment. Compared to UC, EC-Wet and SN protection enhanced fruit quality with higher or similar crop load, fruit firmness, and quality.

Application of Airborne Radar Variable Altitude Aerial Survey in High Precision Mapping of Mountainous Areas

This paper studies how to use UAV aerial survey equipment to carry laser radar and high-definition real-scene lenses to achieve high-precision mountain mapping. The study aims to solve the problems of complex terrain, difficulties in surveying, and controlling the accuracy of surveying and mapping in mountainous, canyon, and hilly areas. Firstly, the LK tea production area development project is selected as an example for example analysis. The aerial survey equipment and data acquisition equipment are selected according to the characteristics of the project. Secondly, aiming at the problem that the mountainous terrain undulates greatly and that the accuracy of ground object mapping is difficult to control, this paper puts forward the “variable height aerial survey” method. It collects aerial survey data according to the terrain characteristics. Finally, this paper proposes a “point cloud overlay” modeling method. It combines laser point cloud data with real 3D data to form a high-precision real 3D model point cloud reorganization and establish a high-precision real 3D model.

Modern Trends in Populations of the Siberian Crane (Grus leucogeranus) and the Sandhill Crane (Grus canadensis) (Gruidae, Gruiformes) on the Tundra of Yakutia and Chukotka Based on Aerial Surveys

Modern Trends in Populations of the Siberian Crane (Grus leucogeranus) and the Sandhill Crane (Grus canadensis) (Gruidae, Gruiformes) on the Tundra of Yakutia and Chukotka Based on Aerial Surveys

Spatial navigation performance differentiates Alzheimer´s disease biomarker positive and biomarker negative cognitively impaired older adults

AbstractBackgroundSpatial navigation deficits including egocentric (body‐centered) and allocentric (world‐centered) navigation impairment are present early in Alzheimer´s disease (AD). We evaluated a potential of a realistic‐looking spatial navigation task to differentiate older adults with amnestic mild cognitive impairment (aMCI) who have positive AD biomarkers (AD aMCI) from those with negative AD biomarkers (non‐AD aMCI).MethodParticipants with AD aMCI (n = 24), non‐AD aMCI (n = 25), mild AD dementia (n = 14) and cognitively normal (CN) older adults (n = 35) underwent spatial navigation assessment in the virtual Supermarket task. Participants passively travelled through the supermarket and followed different routes to reach specific locations. In the final location, the participants had to indicate their starting location (egocentric heading) and their current location and final heading orientation on an aerial spatial map of the supermarket (distance from the correct location and allocentric heading, respectively, both measures of allocentric navigation).ResultIn the egocentric heading, the AD aMCI and mild AD dementia groups indicated their original starting location less accurately than the CN group (p<0.001) and with similar accuracy as the non‐AD aMCI group (p> = 0.219). The non‐AD aMCI group did not significantly differ from the CN group (p = 0.055). In the first allocentric task (distance from the correct location), the AD aMCI group and mild AD dementia groups indicated their positions on a paper aerial map of the supermarket with greater distance errors compared to the non‐AD aMCI group (p< = 0.013) and CN (p<0.001) groups. The non‐AD aMCI group had comparable performance to the CN group (p = 0.172). In the second allocentric task (allocentric heading), both the AD aMCI and mild AD dementia groups made more errors indicating final heading orientation than the non‐AD aMCI (p< = 0.040) and the CN (p<0.001) groups. The non‐AD aMCI group had worse performance than the CN group (p = 0.004). The sensitivity and specificity for discriminating AD aMCI and non‐AD aMCI was 72% and 71%, respectively.ConclusionBoth, egocentric and allocentric spatial navigation tasks detected spatial navigation impairment in older adults with AD aMCI. However, only the allocentric tasks differentiated AD aMCI from non‐AD aMCI. The virtual Supermarket task has a potential to become a screening tool for early AD‐related spatial navigation deficits.

Flood Affected Building Footprints 3D Model from LiDAR and Aerial Photogrammetry (Case Study: Pandugo Street, Surabaya)

Frequent rainfall events in Surabaya occurred due to tall silt within the channel, which prevent water flow and at that point flooding onto the street. Information about the events, including the simulation and prediction are needing accurate visualization to be major consideration for infrastructure and public facilities decision-making. 3D modelling are accurate enough as flood disaster risk management for buildings, using LiDAR and aerial photogrammetry that can provide strong visual representations accurately. DSM and DTM derived from aerial photogrammetry survey are then used to get DSM LiDAR. DSM&DTM from LiDAR was taken in 2016 and DSM&DTM from aerial photogrammetry was taken in 2022. The only objects that are updated are buildings from DSM aerial photogrammetry then applied to DSM LiDAR. Buildings footprint, road network, nDSM, and flood inundation data are then processed to get the 3D Model of buildings and floods. The model are then evaluated by comparing the total of affected buildings with manual methods. Validation on buildings height also performed and results in 0.86233 RMSe that achieved the LOD2 standard. Potential further studies could focus on improving the LOD and considering other parameters such as rainfall data or gutter data.

농업용 저수지 조기경보시스템 현황 분석 및 개선방안

Of the 17,160 agricultural reservoirs nationwide, 96% are aged more than 30 years after construction. Aging reservoirs are at risk of deterioration and potential collapse. The torrential rains between July and August 2020 caused 26 collapse and loss filure across the country. Preemptive and comprehensive response plan is needed to prevent damage to life and property caused by such a reservoir collapse, and this study analyzes the early warning system of agricultural reservoirs as part of a preemptive and comprehensive countermeasure plan to diagnose the current situation and come up with improvement measures. Using bathymetric data, real-time water level change through water level-rainfall linkage analysis and early warning standard setting according to rainfall were proposed. Using bathymetric and aerial survey data, a three-dimensional reservoir collapse simulation was used to predict the arrival time and submerged range of the collapsed flow, suggesting early warning standards and positioning methods.

Climate Change-Driven Cumulative Mountain Pine Beetle-Caused Whitebark Pine Mortality in the Greater Yellowstone Ecosystem

An aerial survey method called the Landscape Assessment System (LAS) was used to assess mountain pine beetle (Dendroctonus ponderosae)-caused mortality of whitebark pine (Pinus albicaulis) across the Greater Yellowstone Ecosystem (59,000 km2; GYE). This consisted of 11,942 km of flightlines, along which 4434 geo-tagged, oblique aerial photos were captured and processed. A mortality rating of none to severe (0–4.0 recent attack or 5.0–5.4 old attack) was assigned to each photo based on the amount of red (recent attack) and gray (old attack) trees visible. The method produced a photo inventory of 74 percent of the GYE whitebark pine distribution. For the remaining 26 percent of the distribution, mortality levels were estimated based on an interpolated mortality surface. Catchment-level results combining the photo-inventoried and interpolated mortality indicated that 44 percent of the GYE whitebark pine distribution showed severe old attack mortality (5.3–5.4 rating), 37 percent showed moderate old attack mortality (5.2–5.29 rating), 19 percent showed low old attack mortality (5.1–5.19 rating) and less than 1 percent showed trace levels of old attack mortality (5.0–5.09). No catchments were classified as recent attacks indicating that the outbreak of the early 2000’s has ended. However, mortality continues to occur as chronic sub-outbreak-level mortality. Ground verification using field plots indicates that higher LAS mortality values are moderately correlated with a higher percentage of mortality on the ground.

Accuracy assessment of UAS photogrammetry and structure from motion in surveying and mapping

Rapid and accurate surveying has always attracted great interest in all scientific and industrial activities that require high-resolution topographic data. The latest automation and advancement in geomatics engineering are remote sensing solutions using Unmanned Aerial Systems (UAS) and Structure from Motion (SfM) with Multi-View Stereo (MVS) photogrammetry. This research aimed to find the influence of flight height, Ground Control Point (GCP), and software on the geometric accuracy of UAS-SfM-derived Digital Surface Models (DSMs) and orthoimages, as well as to analyze and evaluate the accuracy of UAS-SfM as a rapid and low-cost alternative to conventional survey methods. To achieve the aim of the study, aerial surveys using a fixed-wing UAS and field surveys using RTK GNSS and total station were conducted. A total of 16 photogrammetric projects were processed using different GCP configurations, and detailed statistical analysis was performed on the results. Moreover, the contribution of cross flight on bundle adjustment was investigated empirically by conducting a combined photogrammetric image processing. The analysis revealed that flight height, GCP number and distribution, and the processing software significantly affect products' quality and accuracy. Evaluation of the achieved accuracies was made based on the American Society for Photogrammetry and Remote Sensing (ASPRS) positional accuracy standard for digital geospatial data. The findings of this study revealed that using the optimal flight height and GCP configuration, 3D models, orthomosaics and DSMs can be rapidly reconstructed from 2D images with the quality and accuracy sufficient for most terrain analysis applications, including civil engineering projects.