Remote Sensing for Land Surface Applications

Dear Colleagues,

Climate change, global warming, and resource depletion have been rising issues recently due to their strong link to the global insufficient food supply and, hence, to world food security. Such issues have led, essentially, to (1) damaged crops and reduced yields, (2) increased CO₂ emissions, (3) rising wildfire risks, and (4) an increased rate of climate change impacts. In addition, covering vast areas has becoming challenging and costly for multiple reasons, requiring personnel, budgets, as well as tough political decisions.

For this matter, several remote sensing data with revolutionary characteristics in term of spatial resolution, revisit time, and frequency are easily accessible, so they represent a unique land-monitoring tool. Nevertheless, developed models and algorithms are highly needed to process, analyze, and interpret such spatial data for the sake of generating biophysical indicators relevant to the consequences listed above. The operationality of these methods and algorithms (i.e., using mainly remote sensing data as inputs) is highly demanded to achieve an efficient and powerful earth surface monitoring tool. Forest and crop biomass, evapotranspiration rate, water content, as well vegetation cover would assure continuous monitoring.

In this context, research papers and studies aiming at methodology development and/or applications utilizing remote sensing products (e.g., SAR, LiDAR, optical satellites) across different regions and climates are welcome.

Potential topics relevant to this Special Issue include, but are not limited to, the following:

• Remote sensing to feed crop models for precise biophysical estimations;
• Machine and deep learning for forest and/or crop monitoring;
• Crop ET estimates using remote sensing (e.g., LST, NDVI, etc.);
• Water accounting/water productivity;
• Basin monitoring;
• Phenology and LAI estimations using remote sensing (e.g., SAR and Sentinel-2);
• Data fusion (optical and radar data);
• Forest height and biomass estimation (e.g., LiDAR)

Dr. Marcel M. El Hajj
Dr. Ali Nasrallah
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 250 words) can be sent to the Editorial Office for assessment.

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.