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Remote Sensing
Special Issues
Recent Trends and Applications for Imaging Spectroscopy
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Recent Trends and Applications for Imaging Spectroscopy

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (29 February 2020) | Viewed by 17155

Special Issue Editors

Prof. Dr. Jose Moreno

E-Mail Website
Guest Editor
Laboratory for Earth Observation, Image Processing Laboratory, Department of Earth Physics and Thermodynamics, Faculty of Physics, University of Valencia, Scientific Park, 46980 Valencia, Spain
Interests: optical remote sensing; imaging spectroscopy; vegetation fluorescence; vegetation biophysical parameters; land surface applications; optical reflectance/fluorescence models; retrieval methods; design of future earth observation missions; dynamical vegetation models; calibration/validation field campaigns
Special Issues, Collections and Topics in MDPI journals
Dr. Robert Green

E-Mail Website
Guest Editor
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA
Interests: science questions posed in the context of the interaction of light with matter pursued with imaging spectroscopy in the optical portion of the spectrum
Dr. Cindy Ong

E-Mail Website
Guest Editor
CSIRO Energy, Commonwealth Scientific and Industrial Research Organisation (CSIRO), 26 Dick Perry Avenue, Kensington, WA 6151, Australia
Interests: methane monitoring; fugitive emisions; application of remote sensing for non renewable resource environmental monitoring and agricultural crops; calibration and vailidation of optical sensors; imaging spectroscopy; remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Uta Heiden

E-Mail Website
Guest Editor
German Aerospace Center (DLR), Remote Sensing Technology Institute, Photogrammetry and Image Analysis, Oberpfaffenhofen, 82234 Weßling, Germany
Interests: imaging spectroscopy with a focus on urban surface materials; spaceborne imaging spectroscopy missions; EnMAP; DESIS; earth observation for soil information; applied spectroscopy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Imaging spectroscopy has become a unique technique to quantify and map the chemical constituents of the Earth surface, the atmosphere, inland waters and oceans, contributing to a better understanding of the dynamics of land surface processes and surface-atmosphere interactions, and providing a wide range of opportunities for operational applications. The advancement in modeling and understanding of the signal, the development of advanced retrieval techniques, and the availability of data with improved spectral, spatial and radiometric resolutions, have contribute to make imaging spectroscopy an advanced and mature technique for remote sensing science and applications.

The recent and near-future launch of several new imaging spectroscopy missions provides an excellent opportunity to review the state of the art in such field, and this is the objective of the Special Issue on Recent Trends and Applications for Imaging Spectroscopy.

This special issue will cover recent results from field / airborne campaigns in preparation of future spaceborne missions, and early results from recently launched space systems, recent advances in retrieval methods and data exploitation tools, and updates on the science and applications of imaging spectroscopy data, with emphasis on new emerging applications. Data calibration and validation aspects, through automated measurements at field sites or dedicated validation campaigns, are also encouraged, including quantification of error sources and estimation of uncertainties in the final derived products. Future plans about new airborne facilities and dedicated new space missions for imaging spectroscopy, and combinations with other data sources for advanced applications, are also encouraged.

Prof. Dr. Jose Moreno
Dr. Robert Green
Dr. Cindy Ong
Dr. Uta Heiden
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • New imaging spectroscopy systems, including field, UAVs, airborne and satellite sensors and platforms
  • Recent airborne campaigns and dedicated field experiments in preparation of future missions
  • Early results from recently launched space systems
  • Advances in applications in land, atmosphere and oceans
  • New emerging applications
  • New techniques for the retrieval of geological and biophysical information
  • Modeling of the signal and model-inversion approaches
  • Advanced retrieval methods
  • Synergistic usage of imaging spectroscopy data with other remote sensing data
  • Calibration / validation of imaging spectroscopy data

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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17 pages, 8410 KiB  
Article
Approximating Empirical Surface Reflectance Data through Emulation: Opportunities for Synthetic Scene Generation
by Jochem Verrelst, Juan Pablo Rivera Caicedo, Jorge Vicent, Pablo Morcillo Pallarés and José Moreno
Remote Sens. 2019, 11(2), 157; https://doi.org/10.3390/rs11020157 - 16 Jan 2019
Cited by 10 | Viewed by 3868
Abstract
Collection of spectroradiometric measurements with associated biophysical variables is an essential part of the development and validation of optical remote sensing vegetation products. However, their quality can only be assessed in the subsequent analysis, and often there is a need for collecting extra [...] Read more.
Collection of spectroradiometric measurements with associated biophysical variables is an essential part of the development and validation of optical remote sensing vegetation products. However, their quality can only be assessed in the subsequent analysis, and often there is a need for collecting extra data, e.g., to fill in gaps. To generate empirical-like surface reflectance data of vegetated surfaces, we propose to exploit emulation, i.e., reconstruction of spectral measurements through statistical learning. We evaluated emulation against classical interpolation methods using an empirical field dataset with associated hyperspectral spaceborne CHRIS and airborne HyMap reflectance spectra, to produce synthetic CHRIS and HyMap reflectance spectra for any combination of input biophysical variables. Results indicate that: (1) emulation produces surface reflectance data more accurately than interpolation when validating against a separate part of the field dataset; and (2) emulation produces the spectra multiple times (tens to hundreds) faster than interpolation. This technique opens various data processing opportunities, e.g., emulators not only allow rapidly producing large synthetic spectral datasets, but they can also speed up computationally intensive processing routines such as synthetic scene generation. To demonstrate this, emulators were run to simulate hyperspectral imagery based on input maps of a few biophysical variables coming from CHRIS, HyMap and Sentinel-2 (S2). The emulators produced spaceborne CHRIS-like and airborne HyMap-like surface reflectance imagery in the order of seconds, thereby approximating the spectra of vegetated surfaces sufficiently similar to the reference images. Similarly, it took a few minutes to produce a hyperspectral data cube with a spatial texture of S2 and a spectral resolution of HyMap. Full article
(This article belongs to the Special Issue Recent Trends and Applications for Imaging Spectroscopy)
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21 pages, 4196 KiB  
Article
The Potential of Reflectance and Laser Induced Luminescence Spectroscopy for Near-Field Rare Earth Element Detection in Mineral Exploration
by Sandra Lorenz, Jan Beyer, Margret Fuchs, Peter Seidel, David Turner, Johannes Heitmann and Richard Gloaguen
Remote Sens. 2019, 11(1), 21; https://doi.org/10.3390/rs11010021 - 23 Dec 2018
Cited by 18 | Viewed by 6612
Abstract
New energy, transport, computer and telecommunication technologies require an increasing supply of rare earth elements (REEs). As a consequence, adequate and robust detection methods become essential for the exploration and discovery of new deposits, the improved characterization of existing deposits and the future [...] Read more.
New energy, transport, computer and telecommunication technologies require an increasing supply of rare earth elements (REEs). As a consequence, adequate and robust detection methods become essential for the exploration and discovery of new deposits, the improved characterization of existing deposits and the future recycling of today’s high-tech products. Within this paper, we investigate the potential of combining passive reflectance (imaging and point sampling) with laser stimulated luminescence (point sampling) spectroscopic measurements across the visible, near and shortwave infrared for REE detection in non-invasive near-field mineral exploration. We analyse natural REE-bearing mineral samples from main REE-deposits around the world and focus on challenges such as the discrimination of overlapping spectroscopic features and the influence of the mineral type on detectability, feature position and mineral matrix luminescence. We demonstrate that the cross-validation of results from both methods increases the robustness and sensitivity, provides the potential for semi-quantification and enables the time- and cost-efficient detection of economically important REE, including Ce, Pr, Nd, Sm, Eu, Dy, Er, Yb and potentially also Ho and Tm. Full article
(This article belongs to the Special Issue Recent Trends and Applications for Imaging Spectroscopy)
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23 pages, 21203 KiB  
Article
Retrieval of Sediment Fill Factor by Inversion of a Modified Hapke Model Applied to Sampled HCRF from Airborne and Satellite Imagery
by Rehman S. Eon, Charles M. Bachmann and Aaron D. Gerace
Remote Sens. 2018, 10(11), 1758; https://doi.org/10.3390/rs10111758 - 7 Nov 2018
Cited by 13 | Viewed by 5018
Abstract
The physical properties of a medium such as density, grain size and surface roughness all influence the angular dependence of spectral signatures. Radiative transfer models, such as the one developed by Hapke, can relate the angular dependence of the reflectance to these geophysical [...] Read more.
The physical properties of a medium such as density, grain size and surface roughness all influence the angular dependence of spectral signatures. Radiative transfer models, such as the one developed by Hapke, can relate the angular dependence of the reflectance to these geophysical variables. This paper focuses on extracting geophysical parameters, fill factor (decreasing porosity) and the single scattering albedo (SSA), through the inversion of a modified version of the Hapke model of airborne and space-borne imagery. The inversion methodology was validated through controlled experiments within a laboratory setting, where a good correlation (R 2 = 0.72) between the retrieved fill factor and the measured density was obtained. Using the same approach, we also retrieved the sediment fill factor and SSA from airborne data collected by the NASA G-LiHT system, and space-borne data observed by the NOAA GOES imager. The results from these studies provide a mechanism to understand geophysical characteristics of the terrain and may potentially be used for long-term monitoring of the dynamic dunes system. Full article
(This article belongs to the Special Issue Recent Trends and Applications for Imaging Spectroscopy)
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