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Special Issue "Remote Sensing to Detect and Diagnose Organismal Responses"
Deadline for manuscript submissions: 31 March 2020.
There is a wealth of studies describing applications of a wide range of remote sensing technologies to detect and diagnose abiotic and biotic responses by plants to single stressors. In this Special Issue, we intend to go beyond this range of remote sensing applications and focus on “organismal responses” more broadly. We are also hoping that authors can go beyond the detection of an optical reflectance response and tie a thorough analysis of remote sensing data to other types of data (physiological, molecular, genetic, biochemical). In other words, we are embracing a phenomics approach, in which we hope to, at least partially, explain why and how organisms exhibit an optical reflectance response to stressors and/or treatments. We are seeking articles describing exciting applications of remote sensing technologies to detect and diagnose differences and/or stress across all kingdoms. For instance, regarding animals, we would very much welcome articles describing applications of remote sensing technologies in studies of:
- Breeding of animals (i.e., fish, livestock, and insects)
- Disease and stress monitoring of animals (livestock as well as non-agricultural animals)
- Organismal adaptations to climate change and other anthropogenic factors
- Animals with/without pathogenic vectors (i.e., insects vectoring plant pathogenic diseases)
- Regarding plants, we would welcome articles describing studies of how remote sensing technologies can be used to characterize:
- Physiological/genetic traits of seeds (i.e., resistance to herbicides or environmental adaptations)
- Different plant responses to multiple biotic stressors (i.e., pests)
- Plant communities and/or individual plants and their adaptations to climate change and other anthropogenic factors.
The above-mentioned suggestions are by no means more than just suggestions. Feel free to contact the guest editor directly if you wish to discuss a possible topic. We are not limited to certain types of remote sensing technologies, nor do we impose restrictions regarding the spatial resolution (scale) of the data sets being examined.
With this Special Issue, we wish to showcase innovative and exciting examples of phenomics and the powerful nature of optical classifications—how remote sensing technologies, similar to molecular research tools, are becoming “household” equipment in almost all aspects of life sciences.
Very much looking forward to hearing from you about your interest in contributing to this Special Issue!
Dr. Christian Nansen
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 papers will be 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 1800 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.
- Stress detection
- Optical classification
- Modern life science research
- Organismal biology