Special Issue "Methodological Advancements in Remote Sensing of Biophysical Parameters in Inland and Coastal Waters"
Deadline for manuscript submissions: 30 April 2022.
Interests: inland and coastal waters; ocean color; bathymetry; water quality; rivers; lakes; fluvial remote sensing; environmental remote sensing; machine learning
Interests: radiative transfer modeling in water and the atmosphere; algorithm development for optically complex waters; inverse modeling; calibration of field spectrometers and hyperspectral sensors
2. Remote Sensing and Geoinformatics, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Interests: inland water remote sensing; lake color; water quality; proximity sensing; optical sensors; light pollution; night-time lights; environmental monitoring
Special Issues and Collections in MDPI journals
Special Issue in Remote Sensing: Light Pollution Monitoring Using Remote Sensing Data II
The biophysical attributes of inland and coastal waters, including the concentration of constituents (e.g., chlorophyll-a and suspended matters), bathymetry, and benthic habitats are closely linked to a variety of aquatic ecosystem services. Timely and accurate information on the aquatic biophysical parameters is crucial to enable sustainable management of natural waters, urban and agricultural water supply, navigation, fisheries, tourism, recreational activities, and so on. Furthermore, reliable quantification of the aforementioned parameters both in space and time can enhance our understanding of processes such as eutrophication and harmful algal blooms, carbon cycle, as well as climate change impacts. In this context, optical remote sensing provides an efficient means of characterizing these parameters across large spatial and temporal scales.
This Special Issue aims to disseminate the latest research findings concerned with the development of novel methodological approaches, for example, advanced machine learning and physics-based methods for the remote sensing of biophysical parameters such as water quality, bathymetry, and substrate properties. We welcome the submission of original manuscripts concerned with all aspects of developing and assessing methods for estimation of the parameters from multispectral and hyperspectral data. Welcome topics include but are not limited to the following:
- Novel machine/deep learning methods for the estimation of biophysical parameters;
- Advanced physics-based inversion methods;
- Method comparison and review studies;
- Synergic use and fusion of machine learning and physics-based approaches;
- Multitemporal analysis;
- Cross-sensor fusion of spectral or other data;
- Spectrally based in situ measurement approaches.
Dr. Milad Niroumand-Jadidi
Dr. Peter Gege
Dr. Andreas Jechow
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 2400 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.
- remote sensing methods
- physics-based inversion
- machine learning
- inland and coastal waters
- biophysical parameters
- water quality
- substrate types and compositions