Special Issue "Remote Sensing of Agricultural Monitoring"
A special issue of Agronomy (ISSN 2073-4395).
Deadline for manuscript submissions: closed (30 April 2020).
Interests: remote sensing; biophysical parameters of vegetation (chlorophyll content, leaf area index, water content); agroecosystems; inland water quality
Interests: thermal remote sensing; land surface temperature/emissivity retrieval; temperature trends over tropical forests
Special Issues and Collections in MDPI journals
Special Issue in Sensors: Advances in Remote Sensors for Earth Observation and Modeling of Earth Processes
In recent decades, remote sensing has become an important tool to improve agricultural management. As a consequence of important technological development and the launch of new Earth Observation missions, e.g., ESA’s Copernicus program, open-access high spectral and temporal resolution images are now available which allow obtaining detailed crop maps and agronomic products, such as the crops’ chlorophyll content, leaf area index (LAI), evapotranspiration or soil surface moisture (SSM). Furthermore, in 2022, the Fluorescence Explorer (FLEX) mission will be launched in tandem with Copernicus Sentinel-3, allowing the simultaneous measurements of sun-induced fluorescence (SIF) along with spectrally resolved visible near-infrared (VIS-NIR), and thermal–infrared reflectance. These and other products make it possible to improve our knowledge of crop dynamics and agricultural practices, which are useful for farmers, stakeholders, and policy makers, allowing the early detection of pests/diseases, improving farmers’ nutrients/water management, and consequently increasing the final crop yield.
This Special Issue invites original research to improve our knowledge of agro-ecosystems dynamics using remote sensing techniques. Topics may cover but are not limited to:
- Algorithms for the early detection of nutrients/water deficits as well as pests/diseases;
- Development of novel algorithms to improve LAI, Chlorophyll, and other biophysical parameters;
- Remote sensing studies that use ground, airborne, or satellite approaches to monitor plant dynamics;
- Remote sensing studies focuses on image fusion combining radar, optical, and thermal images, such as image classification, indices or statistical methods, such as machine learning, temporal analysis or image fusion with radar, optical, and thermal images;
- Water quality for irrigation by remote sensing.
We invite both theoretical and application-oriented studies to be submitted, mainly those based on operational satellites such as Sentinel-1, 2 and 3 or other current or future hyperspectral missions.
Prof. Dr. Jesús Delegido Gómez
Prof. Dr. Juan Carlos Jiménez-Muñoz
Dr. Mª Pilar Cendrero-Mateo
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. Agronomy is an international peer-reviewed open access monthly 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.
- Biophysical parameters (Chlorophyll content, LAI, water content, fluorescence, evapotranspiration, etc.)
- Crop classification maps
- Yield forecasting
- Multitemporal image analysis
- Empirical or physics-based methods
- Vegetation stress detection
- Sun induced fluorescence