Map** Essential Elements of Agricultural Land Using 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 November 2024 | Viewed by 1050
Special Issue Editors
Interests: crop system; crop map**; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: plant ecology remote sensing; vegetation phenology; remote sensing big data
Interests: integrated application of satellite-space-earth remote sensing technology; multi-scale remote sensing inversion of ecological parameters at global and regional scales; carbon and water cycle of vegetation; uav remote sensing monitoring of vegetation phenotype; machine learning and application development of big data
Special Issues, Collections and Topics in MDPI journals
Interests: land use/cover change; land use monitoring and simulation; agricultural remote sensing; agricultural land use; rural human–earth system
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; multi-source remote sensing fusion; crop dynamic monitoring
Special Issue Information
Dear Colleagues,
Agricultural remote sensing technology plays a crucial role in modern agriculture, especially in identifying and monitoring key elements of agricultural land including farmland, grassland and etc.. By utilizing remote sensing data, we can effectively classify, monitor, and manage agricultural land to enhance its yield and quality. Map** and analyzing the essential elements of agricultural land is an important task, including soil types, vegetation cover, water resource distribution, climate variance, etc. By conducting remote sensing monitoring and map** of agricultural land, precision agricultural management can be achieved, enhancing land utilization efficiency while reducing resource waste and environmental pollution. Moreover, it can provide scientific basis for agricultural decision-making, assisting farmers in formulating more rational planting plans to improve agricultural production stability and sustainability. In summary, excavate immense potential and promising prospects in map** key elements of farmland.
Therefore, to better excavate immense potential and promising prospects in key elements of agricultural land by leveraging remote sensing technology, this Special Issue aims to invite original and innovative research on applications of multi-source remote sensing for map** essential elements of agricultural land using mathematical statistics, machine learning, and deep learning methods, or other state-of-the-art approaches.
The research areas may include (but are not limited to) the following:
- Agricultural land thematic information map**;
- Multi-sensor imagery fusion;
- Near real-time remote sensing monitoring of plant growth
- Water-food-energy-environment tradeoff and synergies in agricultural land supported by remote sensing;
- Agricultural soil health diagnosis;
- Machine learning or deep learning for near-real-time monitoring of plant growth.
Dr. Luo Liu
Dr. Jilin Yang
Prof. Dr. Fei Li
Dr. Yaqun Liu
Dr. Wenzhi Zhao
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at mdpi.longhoe.net 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
- agricultural land map**
- agricultural land parameter retrieval
- yield estimation or forecasts
- biomass in agricultural land
- water use efficiency in agricultural land
- plant biodiversity in agricultural land
- plant growth model
- deep learning
