scholarly journals Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art

2020 ◽  
Vol 12 (10) ◽  
pp. 1624 ◽  
Author(s):  
Juan Quirós Vargas ◽  
Juliane Bendig ◽  
Alasdair Mac Arthur ◽  
Andreas Burkart ◽  
Tommaso Julitta ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Atmospheric Correction ◽  
Physiological Status ◽  
Unmanned Aerial Systems ◽  
Open Research ◽  
Calibration Methods ◽  
Research Questions ◽  
Spatio Temporal ◽  
Aerial Systems

Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest scientific contributions, some of which are being developed within the frame of the Training on Remote Sensing for Ecosystem Modelling (TRuStEE) program. Investigations from the Universities of Edinburgh (School of Geosciences) and Tasmania (School of Technology, Environments and Design) are first presented, both sharing the principle of the spectroradiometer optical path bifurcation throughout, the so called ‘Piccolo-Doppio’ and ‘AirSIF’ systems, respectively. Furthermore, JB Hyperspectral Devices’ ongoing investigations towards the closest possible characterization of the atmospheric interference suffered by orbital platforms are outlined. The latest approach focuses on the observation of one single ground point across a multiple-kilometer atmosphere vertical column using the high altitude UAS named as AirFloX, mounted on a specifically designed and manufactured fixed wing platform: ‘FloXPlane’. We present technical details and preliminary results obtained from each instrument, a summary of their main characteristics, and finally the remaining challenges and open research questions are addressed. On the basis of the presented findings, the consensus is that SIF can be retrieved from low altitude spectroscopy. However, the UAS-based methods for SIF retrieval still present uncertainties associated with the current sensor characteristics and the spatio-temporal mismatching between aerial and ground measurements, which complicate robust validations. Complementary studies regarding the standardization of calibration methods and the characterization of spectroradiometers and data processing workflows are also required. Moreover, other open research questions such as those related to the implementation of atmospheric correction, bidirectional reflectance distribution function (BRDF) correction, and accurate surface elevation models remain to be addressed.

scholarly journals FESSTVaL: Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg – the campaign 2021 an its predecessors

2021 ◽  
Author(s):  
Cathy Hohenegger ◽  
Felix Ament ◽  
Frank Beyrich ◽  
Ivan Bastak Duran ◽  
Ulrich Löhnert ◽  
...  
Keyword(s):  
Field Experiment ◽  
Temporal Variability ◽  
Low Cost ◽  
Unmanned Aerial Systems ◽  
Near Surface ◽  
Cold Pools ◽  
Measurement Strategy ◽  
Meteorological Observatory ◽  
Spatio Temporal ◽  
Aerial Systems

<p>Measuring submesoscale variability is the core task of the field campaign FESSTVaL (Field Experiment on Sub-Mesoscale Spatio-Temporal Variability in Lindenberg).  FESSTVaL focuses on three sources of submesoscale variability: cold pools, wind gusts and boundary layer pattern. It took place in the summer months of 2021 at the Meteorological Observatory Lindenberg – Richard-Aßmann-Observatory (MOL-RAO) of the German Weather Service (DWD) near Berlin and was initiated by the Hans-Ertel-Center for Weather Research (HErZ).</p><p>In order to capture phenomena at the submesoscale (500 m – 5 km), generally not captured by conventional measurement network, a hierarchical measurement strategy is adopted. This includes wind profiling stations with a coordinated scanning strategy of several Doppler Lidars, two mobile profilers to measure thermodynamic properties and precipitation, more than 100 stations with near-surface measurements of air temperature, pressure and soil moisture, more than 20 automatic weather stations, an X-Band radar, and a number of energy balance stations. This equipment is augmented by the extensive ground-based remote sensing array at the MOL-RAO, operated by DWD and by flights operated by Unmanned Aerial Systems. Complementing to this, the benefit of a citizen-science measurement network is investigated during the campaign with “Internet-of-things” based technology and low-cost sensors built and maintained by citizens. The measurements are supplemented by high-resolution large-eddy simulations (ICON-LES).</p><p>Originally planned for the summer 2020, FESSTVaL had to be postponed to 2021 and replaced by three local individual campaigns, conducted in Bayern, Lindenberg and Hamburg in 2020. Those three test campaigns demonstrated the ability of the envisionned measurement strategy and planned instruments to capture submesoscale variability and submesoscale weather phenomean. This talk will give a brief overview on the results of these three campaigns, as a foretaste to FESSTVaL, together with some of the very first measurements taken during FESSTVaL. </p>

scholarly journals Spatio-temporal evaluation of plant height in corn via unmanned aerial systems

2017 ◽  
Vol 11 (03) ◽  
pp. 1 ◽  
Author(s):  
Sebastian Varela ◽  
Yared Assefa ◽  
P. V. Vara Prasad ◽  
Nahuel R. Peralta ◽  
Terry W. Griffin ◽  
...  
Keyword(s):  
Plant Height ◽  
Unmanned Aerial Systems ◽  
Spatio Temporal ◽  
Aerial Systems

Characterization of Small-Scale Turbochargers for Unmanned Aerial Systems

2016 ◽  
Author(s):  
Mark R. Mataczynski ◽  
Paul Litke ◽  
Benjamin Naguy ◽  
Jacob Baranski
Keyword(s):  
Small Scale ◽  
Unmanned Aerial Systems ◽  
Aerial Systems

scholarly journals Advances in Unmanned Aerial System Remote Sensing for Precision Viticulture

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 956
Author(s):  
Alberto Sassu ◽  
Filippo Gambella ◽  
Luca Ghiani ◽  
Luca Mercenaro ◽  
Maria Caria ◽  
...  
Keyword(s):  
Remote Sensing ◽  
New Technologies ◽  
Unmanned Aerial Systems ◽  
Monitoring And Control ◽  
Detection Techniques ◽  
Precision Viticulture ◽  
Spatio Temporal ◽  
And Control ◽  
Aerial Systems ◽  
Area And Volume

New technologies for management, monitoring, and control of spatio-temporal crop variability in precision viticulture scenarios are numerous. Remote sensing relies on sensors able to provide useful data for the improvement of management efficiency and the optimization of inputs. unmanned aerial systems (UASs) are the newest and most versatile tools, characterized by high precision and accuracy, flexibility, and low operating costs. The work aims at providing a complete overview of the application of UASs in precision viticulture, focusing on the different application purposes, the applied equipment, the potential of technologies combined with UASs for identifying vineyards’ variability. The review discusses the potential of UASs in viticulture by distinguishing five areas of application: rows segmentation and crop features detection techniques; vineyard variability monitoring; estimation of row area and volume; disease detection; vigor and prescription maps creation. Technological innovation and low purchase costs make UASs the core tools for decision support in the customary use by winegrowers. The ability of the systems to respond to the current demands for the acquisition of digital technologies in agricultural fields makes UASs a candidate to play an increasingly important role in future scenarios of viticulture application.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

Beach and dune impacts due to Hurricane Florence in Dare County, North Carolina

Shore & Beach ◽  
2019 ◽  
pp. 44-49 ◽  
Author(s):  
Elizabeth Sciaudone ◽  
Liliana Velasquez-Montoya
Keyword(s):  
North Carolina ◽  
Prior Knowledge ◽  
Unmanned Aerial Systems ◽  
State University ◽  
National Wildlife Refuge ◽  
Sediment Samples ◽  
Wildlife Refuge ◽  
Full Report ◽  
Aerial Systems

Less than two weeks after Hurricane Florence made landfall in North Carolina (NC), a team of researchers from NC State University traveled to Dare County to investigate the storm’s effects on beaches and dunes. Using available post-storm imagery and prior knowledge of vulnerabilities in the system, the team identified several locations to visit in the towns of Kitty Hawk, Nags Head, Rodanthe, Buxton, and Hatteras, as well as a number of locations within the Pea Island National Wildlife Refuge (Figure 1). Data collected included topographic profiles, still imagery and video from unmanned aerial systems, sediment samples, and geo-located photography. This Coastal Observations piece presents some of the data and photos collected; the full report is available online (Sciaudone et al. 2019), and data collected will be made available to interested researchers upon request.

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