Advancing Cropland Management Through Hyperspectral Remote Sensing: Innovations and Applications

Dear Colleagues,

Hyperspectral remote sensing has emerged as a transformative tool in cropland management, enabling the precise monitoring of crop growth, development, and decision making to improve agricultural sustainability and productivity. The rich spectral information provided by hyperspectral data empowers researchers and practitioners to detect subtle variations in soil properties, crop biophysical characteristics, and, therefore, vegetation health. These capabilities make hyperspectral technologies invaluable for addressing the challenges of food security, resource management, and environmental sustainability.

This Special Issue invites contributions that explore innovative applications of hyperspectral remote sensing in cropland management, focusing on advancements in data acquisition, processing, and integration with other technologies. We aim to highlight cutting-edge research and practical solutions that drive sustainable agricultural practices.

Scope
The topics of interest include, but are not limited to, the following:

• Hyperspectral techniques for assessing and mapping soil and vegetation biophysical properties.
• Crop variety identification and classification using hyperspectral data.
• Assessing crop water productivity and water-use efficiency.
• Soil organic carbon estimation and soil fertility assessment.
• Detection of crop diseases, pests, and stress conditions using hyperspectral imagery.
• Temporal and spatial analysis of cropland dynamics using hyperspectral imaging.
• Water and/or nutrient stress detection by using hyperspectral data for crop growth and development.
• Precision agriculture applications, including yield prediction and irrigation management.
• Integration of hyperspectral data with other geospatial technologies (e.g., LiDAR, thermal imaging, and UAVs).
• Machine learning and AI-driven methods for hyperspectral data analysis.
• Advances in hyperspectral sensor technologies and calibration for agricultural use.
• Monitoring agricultural land use changes and their environmental impacts.
• Validation and benchmarking of hyperspectral applications in cropland studies.

We look forward to receiving your submission.

Prof. Dr. Jamal Ezzahar
Dr. Abdelghani Chehbouni
Prof. Dr. Salah Er-Raki
Prof. Dr. Saïd Khabba
Guest Editors

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 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 250 words) can be sent to the Editorial Office for assessment.

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. AgriEngineering is an international peer-reviewed open access monthly 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 1800 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.