Applications of Remote Sensing in Agricultural Soil and Crop Mapping

Dear Colleagues,

This Special Issue will explore the multifaceted applications of remote sensing technologies for agricultural soil and crop mapping. Remote sensing has emerged as a powerful tool, offering unprecedented capabilities for monitoring, assessing, and managing agricultural landscapes. This Special Issue studies the latest advancements, methodologies, and case studies that showcase the diverse applications of remote sensing for enhancing precision agriculture and sustainable farming practices. Example topics addressed in this issue include, but are not limited to, advances in these fields:   

• Advanced remote sensing techniques: we will explore cutting-edge methodologies and technologies employed in remote sensing, such as satellite imagery, unmanned aerial vehicles (UAVs), and hyperspectral imaging, as well as their roles in improving the accuracy and efficiency of agricultural mapping.
• Integration with geospatial technologies: we will examine the synergies between remote sensing and geospatial technologies, such as geographic information systems (GIS) and global positioning systems (GPS), to provide comprehensive solutions for precise soil and crop mapping.
• Crop mapping and health monitoring: We will investigate the use of remote sensing for early in-season crop type mapping, real-time monitoring of crop health, disease detection, and stress assessment. We will also highlight innovative approaches that contribute to the early identification and mitigation of potential crop productivity threats.
• Soil quality assessment: We will address the application of remote sensing for assessing soil properties, nutrient levels, and moisture contents. We will also explore how these insights can be utilized for precision farming, optimizing resource allocation, and promoting sustainable soil management practices.
• Data fusion and machine learning: We will explore the integration of remote sensing data with machine learning algorithms for data fusion and analysis. We will also showcase successful applications of artificial intelligence for extracting meaningful insights from large datasets to improve decision-making in agriculture.
• Case studies and practical applications: We will present real-world case studies and success stories that demonstrate the practical implementation of remote sensing in agricultural settings. We will also highlight their impacts on yield optimization, resource efficiency, and overall sustainability.

For this Special Issue, we request contributions from researchers, scientists, and practitioners in the field to foster a deeper understanding of the role of remote sensing in transforming agricultural practices. By bringing together diverse perspectives and innovative approaches, we seek to contribute to the ongoing discourse on how to best leverage technology for the advancement of sustainable agriculture.

Dr. Haoteng Zhao
Dr. Chen Zhang
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

• remote sensing
• soil moisture
• soil properties
• crop mapping
• crop health monitoring
• yield prediction
• crop phenology
• machine learning
• data fusion