Earth Observations and Crop Models for Sustainable Agricultural Management

Dear Colleagues,

Modern agricultural management strongly requires intensive and extensive information from earth observation and spatially explicit models (SEMs). Thanks to the rapid development of earth observation systems and data processing technologies, the quantity and quality of the available information for agriculture have improved substantially in the past decade. On the other hand, crop models have contributed greatly to agricultural management and research. Both process-based and statistical crop models often require wide-spectrum data input, and inadequate data input will limit the performance and thus the applications of crop models. Many innovative research works have been committed to incorporating earth observations into crop models to facilitate agricultural management, but there are still gaps to be met for sustainable and profitable agricultural management.

To better understand the challenges and opportunities to integrate earth observation with crop modelling technologies, this Special Issue invites contributions on: (i) innovative EO methods to derive crop parameters; (ii) novel spatially-explicit crop models towards a better understanding of agricultural production system and ecosystems; and (iii) remote sensing data assimilation with crop models. Submissions are encouraged to cover a broad range of topics that may include, but are not limited to, the following:

• EO quantitative inversion of crop and relevant environmental parameters
• Calibration and verification of various of EO datasets including Sentinel and Gaofen imagery
• Multi-sensor and multi-system EO data fusion
• EO for monitoring crop growth, health and yield
• EO for pests and diseases
• Spatially-explicit crop model development, implementation, and validation
• Data assimilation algorithms, system and uncertainty

Prof. Zhongxin Chen
Dr Jianxi Huang
Prof. Guijun Yang
Prof. Shibo Fang
Prof. Zhenhong Li
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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.