Special Issue "Near Real-Time (NRT) Agriculture Monitoring"
Deadline for manuscript submissions: 1 May 2022.
Interests: multi-satellite data fusion; agriculture monitoring; yield prediction; evapotranspiration
Interests: crop phenology; yield mapping; crop monitoring; data fusion; land surface modeling; land cover and land use change
Special Issues, Collections and Topics in MDPI journals
Interests: smart agriculture; agricultural system; crop mapping; climate change
Near-real-time (NRT) agriculture monitoring can provide immediate crop information, which is vital for agriculture management and decision support. Capturing signal of crop stress at early stages will help the farmers and decision makers to mitigate agricultural loss. An increasing availability of data acquired from satellites, unmanned aerial vehicles, and proximal sensors in the farmland has given us great opportunities to accomplish agricultural monitoring in near real-time. However, the requirements of NRT monitoring vary with application and with scale, from continental and regional scale to farm and field scale. In addition, a cloudy cover can limit the frequency of clear sky observations during the critical growing period, thus adding latency to the imagery used in NRT monitoring. Due to the diverse and complex set agricultural remote sensing monitoring indicators available, and coupled with rapid changes during the crop growth season, there are great demands for the effective use of remote sensing satellite observations, advanced multi-source data processing methods, and convenient joint data inversion. Recent advancements in remotely sensed data collection enable and inspire us to develop new algorithms for agricultural applications using data mining and machine learning techniques. This Special Issue focuses on novel methods and applications for agricultural monitoring in near real-time (within the season) using remote sensing. The contributions may include (1) crop type early mapping; (2) crop growing condition and crop phenology detection; (3) crop stress (water, nutrient, etc.) identification; (4) crop yield prediction; (5) soil water, fertility monitoring; and (6) data processing methods to achieve timely and high-quality monitoring within the season.
Dr. Liang Sun
Dr. Feng Gao
Dr. Wenbin Wu
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.
- near real-time (NRT)
- early crop mapping
- crop stress
- crop phenology
- yield prediction
- soil monitoring
- data fusion
- time-series analysis