Next Article in Journal
Two New Ways of Documenting Miniature Incisions Using a Combination of Image-Based Modelling and Reflectance Transformation Imaging
Previous Article in Journal
Evaluating Elevation Change Thresholds between Structure-from-Motion DEMs Derived from Historical Aerial Photos and 3DEP LiDAR Data
Previous Article in Special Issue
CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity
Open AccessArticle

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

1
Institute of Biogeosciences, IBG2: Plant Sciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
2
School of Technology, Environments and Design, University of Tasmania, Hobart, TAS 7001, Australia
3
School of Geosciences, University of Edinburgh, Edinburgh EH9 3FF, UK
4
Laboratory for Earth Observation, Image Processing Laboratory, University of Valencia, 46980 Valencia, Spain
5
JB Hyperspectral Devices UG, Am Botanischen Garten 33, Düsseldorf 40225, Germany
6
School of Environment, Earth & Ecosystem Sciences, The Open University, Milton Keynes MK7 6AA, UK
7
Birmingham Institute of Forest Research (BIFoR), University of Birmingham, Birmingham B15 2TT, UK
8
Big Sky Science Ltd., Sutton Coldfield B72 1SY, UK
9
Remote Sensing of Environmental Dynamics Laboratory, Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza1, 20126 Milano, Italy
10
ESA-ESTEC, 2201 AZ Noordwijk, The Netherlands
11
Field Lab Campus Klein-Altendorf, University of Bonn, 53359 Rheinbach, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(10), 1624; https://doi.org/10.3390/rs12101624
Received: 14 April 2020 / Revised: 8 May 2020 / Accepted: 13 May 2020 / Published: 19 May 2020
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. View Full-Text
Keywords: hyperspectral remote sensing; light weight spectroradiometer; telluric bands; ESA-FLEX; VNIR; SIF; UAS hyperspectral remote sensing; light weight spectroradiometer; telluric bands; ESA-FLEX; VNIR; SIF; UAS
Show Figures

Figure 1

MDPI and ACS Style

Vargas, J.Q.; Bendig, J.; Mac Arthur, A.; Burkart, A.; Julitta, T.; Maseyk, K.; Thomas, R.; Siegmann, B.; Rossini, M.; Celesti, M.; Schüttemeyer, D.; Kraska, T.; Muller, O.; Rascher, U. Unmanned Aerial Systems (UAS)-Based Methods for Solar Induced Chlorophyll Fluorescence (SIF) Retrieval with Non-Imaging Spectrometers: State of the Art. Remote Sens. 2020, 12, 1624.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop