Dear Colleagues,

Vegetation is a collective term for various plant types that grow on the surface of the Earth and play an important role in the Earth's system. Vegetation is an important regenerative resource within the Earth's surface. Vegetation is the most active and valuable influencing and indicating factor in global change. It simultaneously affects the energy balance of the Earth’s atmosphere system and plays an important role in climate, hydrological, and biochemical cycles.

The combination of remote sensing technology and machine learning technology has brought new solutions to vegetation monitoring. The data obtained through remote sensing technology are automatically analyzed and processed through machine learning algorithms to achieve the efficient and high-precision monitoring of vegetation coverage, biomass, and pests and diseases. This is of great significance for environmental protection and ecological construction. This Special Issue will offer a comprehensive review of the research on the simulation and monitoring of vegetation biomass, vegetation coverage, vegetation phenology, vegetation diseases and pests, and vegetation ecological hydrology using machine learning or remote sensing technology. We kindly invite authors to submit review articles, original research articles, or short communications on topics related to the spatiotemporal change monitoring and driving mechanisms of grasslands, forests, and crops in the context of the application of machine learning or remote sensing technology. As Guest Editors, we look forward to reviewing your relevant contributions to this Special Issue. The specific topics of this Special Issue will include (but are not limited to) the following:

• Vegetation remote sensing monitoring;
• Vegetation biomass simulation;
• Crop disease monitoring;
• Crop yield prediction;
• Analysis of vegetation driving mechanism;
• Vegetation ecological hydrology.

Dr. Yangyang Liu
Dr. Wei Zhang
Guest Editors

Manuscript Submission Information

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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. Agronomy 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 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.

• machine learning
• application of remote sensing
• crop disease
• vegetation monitoring
• ecological hydrology