Forestry and Arboriculture Applications Using High-Resolution Imagery from Unmanned Aerial Vehicles (UAV)

Forests cover over one-third of the planet and provide unmeasurable benefits to the ecosystem. Forest managers have collected and processed countless amounts of data for use in studying, planning, and management of these forests. Data collection has evolved from completely manual operations to the incorporation of technology that has increased the efficiency of data collection and decreased overall costs. Many technological advances have been made that can be incorporated into natural resources disciplines. Laser measuring devices, handheld data collectors and more recently, unmanned aerial vehicles, are just a few items that are playing a major role in the way data is managed and collected. Field hardware has also been aided with new and improved mobile and computer software. Over the course of this study, field technology along with computer advancements have been utilized to aid in forestry and arboricultural applications. Three-dimensional point cloud data that represent tree shape and height were extracted and examined for accuracy. Traditional fieldwork collection (tree height, tree diameter and canopy metrics) was derived from remotely sensed data by using new modeling techniques which will result in time and cost savings. Using high resolution aerial photography, individual tree species are classified to support tree inventory development. Point clouds were used to create digital elevation models (DEM) which can further be used in hydrology analysis, slope, aspect, and hillshades. Digital terrain models (DTM) are in geographic information system (GIS), and along with DEMs, used to create canopy height models (CHM). The results of this study can enhance how the data are utilized and prompt further research and new initiatives that will improve and garner new insight for the use of remotely sensed data in forest management

Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

Aerial ad-hoc networks have the potential to enable smart services while maintaining communication between the ground system and unmanned aerial vehicles (UAV). Previous research has focused on enabling aerial data-centric smart services while integrating the benefits of aerial objects such as UAVs in hostile and non-hostile environments. Quality of service (QoS) provisioning in UAV-assisted communication is a challenging research theme in aerial ad-hoc networks environments. Literature on aerial ad hoc networks lacks cooperative service-oriented modeling for distributed network environments, relying on costly static base station-oriented centralized network environments. Towards this end, this paper proposes a quality of service provisioning framework for a UAV-assisted aerial ad hoc network environment (QSPU) focusing on reliable aerial communication. The UAV’s aerial mobility and service parameters are modelled considering highly dynamic aerial ad-hoc environments. UAV-centric mobility models are utilized to develop a complete aerial routing framework. A comparative performance evaluation demonstrates the benefits of the proposed aerial communication framework. It is evident that QSPU outperforms the state-of-the-art techniques in terms of a number of service-oriented performance metrics in a UAV-assisted aerial ad-hoc network environment

Applications of unmanned aerial vehicles in cryosphere : Latest advances and prospects

Peer reviewedPublisher PD

USE OF UNMANNED AERIAL VEHICLES (UAV) FOR URBAN TREE INVENTORIES

In contrast to standard aerial imagery, unmanned aerial systems (UAS) utilize recent technological advances to provide an affordable alternative for imagery acquisition. Increased value can be realized through clarity and detail providing higher resolution (2-5 cm) over traditional products. Many natural resource disciplines such as urban forestry will benefit from UAS. Tree inventories for risk assessment, biodiversity, planning, and design can be efficiently achieved with the UAS. Recent advances in photogrammetric processing have proved automated methods for three dimensional rendering of aerial imagery. Point clouds can be generated from images providing additional benefits. Association of spatial locational information within the point cloud can be used to produce elevation models i.e. digital elevation, digital terrain and digital surface. Taking advantage of this point cloud data, additional information such as tree heights can be obtained. Several software applications have been developed for LiDAR data which can be adapted to utilize UAS point clouds. This study examines solutions to provide tree inventory and heights from UAS imagery. Imagery taken with a micro-UAS was processed to produce a seamless orthorectified image. This image provided an accurate way to obtain a tree inventory within the study boundary. Utilizing several methods, tree height models were developed with variations in spatial accuracy. Model parameters were modified to offset spatial inconsistencies providing statistical equality of means. Statistical results (p = 0.756) with a level of significance (α = 0.01) between measured and modeled tree height means resulted with 82% of tree species obtaining accurate tree heights. Within this study, the UAS has proven to be an efficient tool for urban forestry providing a cost effective and reliable system to obtain remotely sensed data

INFACT technology watch report

This research has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement nº 776487. Furthermore, some of the authors (B.J. and V.H.-S.) were supported by the Spanish Ministry of Science Innovation and Universities under the framework of the R&D project RTI2018-098966-B-I00.Summary: This report presents a bibliometric study on patents and scientific publications related to the following technologies involved in INFACT: airborne electromagnetic methods, airborne gravity gradiometry, airborne magnetometry and drone-borne hyperspectral imaging. A statistical analysis of the documents reveals the main players, technology trends and collaboration patterns via bibliometric techniques