FYI on behalf of Ittai Herrmann and Katja Berger.
Best wishes, Jakub.
---
Hello all,
I hope you are all well.
In case the topic of the special issue is in your scope and you consider paper submission, please let us know.
Link to the special issue ----https://www.mdpi.com/journal/remotesensing/special_issues/Remote_Proximal
Just to make it clear, this is an open access journal and therefore there is a publication fee - check the details on line- https://www.mdpi.com/journal/remotesensing/apc
The scope of the special issue:
********************************************
Dear Colleagues,
Plants are optically sensed by a variety of sensors and at different scales to answer diverse research questions and to meet practical challenges. Research in quantitative remote sensing starts at
the organ scale moving to the entire plant, population, field, or biotope, up to data obtained from entire continents to explore global phenomena. The use of digital information has been abundantly exploited for more efficient cultivation of large areas and
has become part of agricultural practices worldwide for irrigation and fertilization based on management zones. In addition, breeders are using high-throughput phenotyping in selection experiments for biotic and abiotic stresses as well as yield quantity and
quality. Ecologists are using remotely sensed information to assess carbon footprint. Analyzing high-quality remote sensing observations is also challenging in view of upcoming hyperspectral spaceborne missions and their associated large data streams. Therefore,
the development and adaptation of fast, effective, accurate, and generic retrieval algorithms for biophysical and biochemical traits is required. Methods should be provided on appropriate platforms and evaluated by plant physiologists, agronomists, and ecologists.
This Special Issue strongly encourages contributions aimed at estimating the morpho-physiological and biochemical plant traits (e.g., plant height, LAI, biomass, nutrient contents, water status, pigment
concentration, photosynthetic activity, disease resistance, yield prediction, pollutants detection) from Earth Observation data in agricultural and ecological contexts to support food security and sustainability. This Special Issue aims to cover a vast range
of spatial resolutions (from continent to sub-leaf or root) and spectral resolutions (RGB, multi- and hyperspectral imagery, as well as point data). Besides diverse empirical and physically based retrieval approaches, “hybrid approaches” combining the generic
properties of radiative transfer models with the flexibility and efficiency of nonlinear nonparametric methods (machine learning) are welcome. Moreover, time-series analysis related to plant traits assessment can be exploited. This Special Issue is expected
to demonstrate recent progress and to discuss future perspectives in plant traits sensing.
Dr. Ittai Herrmann
Dr. Katja Berger
Guest Editors
*************************************************
Stay healthy and happy,
Cheers,
Ittai
--
Ittai Herrmann, PhD
The Plant Sensing Laboratory
The Robert H. Smith Institute for Plant Sciences and Genetics in Agriculture
The Robert H. Smith Faculty of Agriculture, Food and Environment
The Hebrew University of Jerusalem
P.O. Box 12, Rehovot 7610001, ISRAEL
Tel: +972-8-9489757
Mobile: +972-52-3947255
Fax: +972-8-9489918
Lab: +972-8-9489958
Email: ittai.herrmann@mail.huji.ac.il
Skype: ittaih
ORCID ID: https://orcid.org/0000-0003-1136-1883
https://www.researchgate.net/profile/Ittai_Herrmann
http://departments.agri.huji.ac.il/plantscience/people/Ittai_Herrmann