Topic Editors

Department of Plant Science, the Pennsylvania State University, University Park, PA 16802, USA
1. Department of Plant & Soil Science, Texas Tech University, 2500 Broadway, Lubbock, TX 79409, USA
2. Department of Soil and Crop Sciences, Texas A&M University, TAMU 2124, College Station, TX 77843, USA
College of Agriculture, Shihezi University, Shihezi 832003, China
College of Agriculture, South China Agricultural University, Guangzhou 510642, China
Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, 380 Hongli Road, Xinxiang 453003, China

Advances in Smart Agriculture with Remote Sensing as the Core and Its Applications in Crops Field

Abstract submission deadline
31 August 2024
Manuscript submission deadline
31 December 2024
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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


  • 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
3.7 5.2 2011 15.8 Days CHF 2600 Submit
3.6 3.6 2011 17.7 Days CHF 2600 Submit
- - 2021 30.5 Days CHF 1000 Submit
4.5 5.4 2012 15.3 Days CHF 2700 Submit is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

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Published Papers

This Topic is now open for submission.
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