A Low Cost UWB Based Solution for Direct Georeferencing UAV Photogrammetry

Thanks to their flexibility and availability at reduced costs, Unmanned Aerial Vehicles (UAVs) have been recently used on a wide range of applications and conditions. Among these, they can play an important role in monitoring critical events (e.g., disaster monitoring) when the presence of humans close to the scene shall be avoided for safety reasons, in precision farming and surveying. Despite the very large number of possible applications, their usage is mainly limited by the availability of the Global Navigation Satellite System (GNSS) in the considered environment: indeed, GNSS is of fundamental importance in order to reduce positioning error derived by the drift of (low-cost) Micro-Electro-Mechanical Systems (MEMS) internal sensors. In order to make the usage of UAVs possible even in critical environments (when GNSS is not available or not reliable, e.g., close to mountains or in city centers, close to high buildings), this paper considers the use of a low cost Ultra Wide-Band (UWB) system as the positioning method. Furthermore, assuming the use of a calibrated camera, UWB positioning is exploited to achieve metric reconstruction on a local coordinate system. Once the georeferenced position of at least three points (e.g., positions of three UWB devices) is known, then georeferencing can be obtained, as well. The proposed approach is validated on a specific case study, the reconstruction of the façade of a university building. Average error on 90 check points distributed over the building façade, obtained by georeferencing by means of the georeferenced positions of four UWB devices at fixed positions, is 0.29 m. For comparison, the average error obtained by using four ground control points is 0.18 m

A Comparative Analysis of Phytovolume Estimation Methods Based on UAV-Photogrammetry and Multispectral Imagery in a Mediterranean Forest

Management and control operations are crucial for preventing forest fires, especially in Mediterranean forest areas with dry climatic periods. One of them is prescribed fires, in which the biomass fuel present in the controlled plot area must be accurately estimated. The most used methods for estimating biomass are time-consuming and demand too much manpower. Unmanned aerial vehicles (UAVs) carrying multispectral sensors can be used to carry out accurate indirect measurements of terrain and vegetation morphology and their radiometric characteristics. Based on the UAV-photogrammetric project products, four estimators of phytovolume were compared in a Mediterranean forest area, all obtained using the difference between a digital surface model (DSM) and a digital terrain model (DTM). The DSM was derived from a UAV-photogrammetric project based on the structure from a motion algorithm. Four different methods for obtaining a DTM were used based on an unclassified dense point cloud produced through a UAV-photogrammetric project (FFU), an unsupervised classified dense point cloud (FFC), a multispectral vegetation index (FMI), and a cloth simulation filter (FCS). Qualitative and quantitative comparisons determined the ability of the phytovolume estimators for vegetation detection and occupied volume. The results show that there are no significant differences in surface vegetation detection between all the pairwise possible comparisons of the four estimators at a 95% confidence level, but FMI presented the best kappa value (0.678) in an error matrix analysis with reference data obtained from photointerpretation and supervised classification. Concerning the accuracy of phytovolume estimation, only FFU and FFC presented differences higher than two standard deviations in a pairwise comparison, and FMI presented the best RMSE (12.3 m) when the estimators were compared to 768 observed data points grouped in four 500 m2 sample plots. The FMI was the best phytovolume estimator of the four compared for low vegetation height in a Mediterranean forest. The use of FMI based on UAV data provides accurate phytovolume estimations that can be applied on several environment management activities, including wildfire prevention. Multitemporal phytovolume estimations based on FMI could help to model the forest resources evolution in a very realistic way

High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques

The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of "linking genotype and phenotype," considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders

Using Unmanned Aerial Systems for Deriving Forest Stand Characteristics in Mixed Hardwoods of West Virginia

Forest inventory information is a principle driver for forest management decisions. Information gathered through these inventories provides a summary of the condition of forested stands. The method by which remote sensing aids land managers is changing rapidly. Imagery produced from unmanned aerial systems (UAS) offer high temporal and spatial resolutions to small-scale forest management. UAS imagery is less expensive and easier to coordinate to meet project needs compared to traditional manned aerial imagery. This study focused on producing an efficient and approachable work flow for producing forest stand board volume estimates from UAS imagery in mixed hardwood stands of West Virginia. A supplementary aim of this project was to evaluate which season was best to collect imagery for forest inventory. True color imagery was collected with a DJI Phantom 3 Professional UAS and was processed in Agisoft Photoscan Professional. Automated tree crown segmentation was performed with Trimble eCognition Developer’s multi-resolution segmentation function with manual optimization of parameters through an iterative process. Individual tree volume metrics were derived from field data relationships and volume estimates were processed in EZ CRUZ forest inventory software. The software, at best, correctly segmented 43% of the individual tree crowns. No correlation between season of imagery acquisition and quality of segmentation was shown. Volume and other stand characteristics were not accurately estimated and were faulted by poor segmentation. However, the imagery was able to capture gaps consistently and provide a visualization of forest health. Difficulties, successes and time required for these procedures were thoroughly noted

COMPARISON OF LOW COST PHOTOGRAMMETRIC SURVEY WITH TLS AND LEICA PEGASUS BACKPACK 3D MODELS

This paper considers Leica backpack and photogrammetric surveys of a mediaeval bastion in Padua, Italy. Furhtermore, terrestrial laser scanning (TLS) survey is considered in order to provide a state of the art reconstruction of the bastion. Despite control points are typically used to avoid deformations in photogrammetric surveys and ensure correct scaling of the reconstruction, in this paper a different approach is considered: this work is part of a project aiming at the development of a system exploiting ultra-wide band (UWB) devices to provide correct scaling of the reconstruction. In particular, low cost Pozyx UWB devices are used to estimate camera positions during image acquisitions. Then, in order to obtain a metric reconstruction, scale factor in the photogrammetric survey is estimated by comparing camera positions obtained from UWB measurements with those obtained from photogrammetric reconstruction. Compared with the TLS survey, the considered photogrammetric model of the bastion results in a RMSE of 21.9cm, average error 13.4cm, and standard deviation 13.5cm. Excluding the final part of the bastion left wing, where the presence of several poles make reconstruction more difficult, (RMSE) fitting error is 17.3cm, average error 11.5cm, and standard deviation 9.5cm. Instead, comparison of Leica backpack and TLS surveys leads to an average error of 4.7cm and standard deviation 0.6cm (4.2 cm and 0.3 cm, respectively, by excluding the final part of the left wing)

Multi-Temporal Image Co-Registration Of Uav Blocks: A Comparison Of Different Approaches

Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

MULTI-TEMPORAL IMAGE CO-REGISTRATION OF UAV BLOCKS: A COMPARISON OF DIFFERENT APPROACHES

Abstract. Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

NOVI PRISTUP PRAĆENJA POMAKA KLIZIŠTA POMOĆU BESPILOTNIH FOTOGRAMETRIJSKIH SUSTAVA

Landslides represent great dangers that can cause fatalities and huge property damage. To prevent or reduce all possible consequences that landslides cause, it is necessary to know the kinematics of the surface and undersurface sliding masses. Geodetic surveying techniques can be used for landslide monitoring and creating a kinematic model of the landslide. One of the most used surveying techniques for landslide monitoring is the photogrammetric survey by Unmanned Aerial System. The results of the photogrammetric survey are dense point clouds, digital terrain models, and digital orthomosaic maps, where landslide displacements can be determined by comparing these results in two measurement epochs. This paper presents a new data processing method with a novel approach for calculating landslide displacements based on Unmanned Aerial System photogrammetric survey data. The main advantage of the new method is that it does not require the production of dense point clouds, digital terrain models, or digital orthomosaic maps to determine displacements. The applicability and accuracy of the new method were tested in a test field with simulated displacements of known values within the range of 20-40 cm in various directions. The new method successfully determined these displacements with a 3D accuracy of ±1.3 cm.Klizišta predstavljaju velike opasnosti koje mogu uzrokovati katastrofalne ljudske žrtve te nanijeti veliku materijalnu štetu. Da bi se spriječile ili umanjile sve moguće posljedice koje klizišta prouzročuju, važno je poznavati kinematiku kretanja površinskih i podzemnih kliznih masa klizišta. Geodetske tehnike izmjere mogu se koristiti za potrebe praćenja te za izradu kinematičkoga modela klizišta. U današnje vrijeme jedna od najčešće korištenih geodetskih tehnika za potrebe praćenja klizišta jest fotogrametrijsko snimanje pomoću bespilotnih zrakoplovnih sustava. Rezultati su takvih snimanja gusti oblaci točaka, digitalni modeli terena te digitalne ortomozaik karte, a na temelju usporedbe tih rezultata u dvjema mjernim epohama mogu se odrediti pomaci klizišta. Ovaj rad predstavlja novu metodu obrade podataka s novim pristupom za određivanje pomaka klizišta na temelju podataka fotogrametrijskoga snimanja bespilotnim zrakoplovnim sustavima. Glavna je prednost nove metode u tome što ne zahtijeva izradu gustih oblaka točaka, digitalnih modela terena ili digitalnih ortomozaik karata za određivanje pomaka. Primjenjivost i točnost nove metode ispitane su na testnome polju sa simuliranim pomacima poznatih vrijednosti čiji su se iznosi kretali u rasponu od 20 do 40 cm u različitim smjerovima. Nova metoda uspješno je odredila te pomake s 3D točnošću od ±1,3 cm