Topic Editors
2. Department of Soil and Crop Sciences, Texas A&M University, TAMU 2124, College Station, TX 77843, USA
Advances in Smart Agriculture with Remote Sensing as the Core and Its Applications in Crops Field
Topic Information
Dear Colleagues,
In recent years, smart agriculture with remote sensing and modeling technologies has brought significant benefits in crop fields and has also altered our understanding and management of crops. Remote sensing allows for crop growth monitoring on different scales such as “ground–low altitude–satellite”, while crop modeling provides predictive insights into crop growth and yield based on a diverse set of environmental parameters. Remote sensing and modeling are fully integrated into applications of crop growth, nutrition demands, irrigation management, and pest control in smart agriculture to optimize agricultural practices, enhance resource efficiency, and make substantial contributions to sustainable agricultural development. This research topic aims to seamlessly integrate remote sensing and modeling, essential components in smart agriculture, to address urgent challenges such as optimizing resource utilization and sustainable agricultural development with enhanced crop production.
The scope of this research topic encompasses a broad range of subjects including but not limited to:
- Integrating remote sensing data with plant traits into crop models to enhance prediction accuracy and decision support.
- Applying machine learning and AI algorithms in crop modeling for increased accuracy and adaptability.
- Utilizing the Internet of Things, sensors, and drones for real-time data collection and monitoring in smart agriculture.
We invite authors to contribute original research articles, perspectives, and reviews, providing valuable insights into the ”Advances in Smart Agriculture with Remote Sensing as the Core and Its Applications in Crops Field”.
Dr. Syed Tahir Ata-Ul-Karim
Dr. Wenxuan Guo
Dr. Yang Liu
Dr. Lei Zhang
Dr. Ben Zhao
Topic Editors
Keywords
- crop
- remote sensing
- crop modeling
- smart agriculture
- machine learning
Participating Journals
| Journal Name | Impact Factor | CiteScore | Launched Year | First Decision (median) | APC | |
|---|---|---|---|---|---|---|
Remote Sensing
|
5.0 | 7.9 | 2009 | 23 Days | CHF 2700 | Submit |
Agronomy
|
3.7 | 5.2 | 2011 | 15.8 Days | CHF 2600 | Submit |
Agriculture
|
3.6 | 3.6 | 2011 | 17.7 Days | CHF 2600 | Submit |
Crops
|
- | - | 2021 | 30.5 Days | CHF 1000 | Submit |
Plants
|
4.5 | 5.4 | 2012 | 15.3 Days | CHF 2700 | Submit |
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