Estimation of Crop Coefficients and Evapotranspiration through Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 10351
Special Issue Editors
Interests: remote sensing; data assimilation; artificial intelligence; hydrology
Special Issues, Collections and Topics in MDPI journals
Interests: satellite data processing; land surface product algorithm; remote sensing classification with machine learning;agrometeorology; agrometeorological disater monitoring with remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: scale transformation; remote sensing product validation; uncertainty quantification; machine learning
Special Issue Information
Dear Colleagues,
The accurate estimation of agro-meteorological variables such as crop coefficient, soil moisture, evapotranspiration, transpiration, irrigation water, crop yield, and gross primary productivity is very improtant for agricultural water management, irrigation scheduling, water use efficiency, and global food security. This Special Issue will focus on the estimation of agro-meteorological variables (e.g., crop coefficient, evapotranspiration, soil moisture, leaf area index, and land surface temperature) over crop lands using remote sensing data and hydrological models. We welcome original research articles and reviews in this Special Issue. Research areas may include (but are not limited to) the estimation of crop coefficient and evapotranspiration, soil moisture, irrigation water, crop yield, gross primary productivity, land surface temperature, water use efficiency, and leaf area index by incorporating remote sensing data into physical hydrologic, machine learning, data assimilation, and hybrid approaches.
We look forward to receiving your contributions.
Prof. Dr. Tongren Xu
Dr. Sayed M. Bateni
Dr. Xiang Li
Dr. Xinlei He
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
- crop coefficient
- evapotranspiration
- gross primary productivity
- irrigation water
- soil moisture
- leaf area index
- machine learning
- data assimilation