Remote Sensing and Monitoring Data for Boosting Crop Yields and Mitigating Air Pollution

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Pollution Control".

Deadline for manuscript submissions: 10 May 2024 | Viewed by 169

Special Issue Editors

School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: source apportionment; persistent organic pollutants; road dust; sediment; atmospheric transport
Special Issues, Collections and Topics in MDPI journals
School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: remote sensing; ecological assessment; feature classification; geological analysis; mathematical geology; mineral evaluation

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Guest Editor
School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: natural organic matter; nanoparticles; environmental process; remediation; emerging pollutant
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce the call for papers for a Special Issue on "Remote Sensing and Monitoring Data for Boosting Crop Yields and Mitigating Air Pollution" in Atmosphere. This Special Issue aims to highlight the contributions of remote sensing and monitoring technologies to enhance crop yields while addressing the critical issue of air pollution.

The use of remote sensing and monitoring data has emerged as a powerful tool in agriculture and environmental science. This Special Issue intends to explore the applications of these technologies in optimizing crop yields and mitigating the adverse effects of air pollution. We welcome submissions that focus on remote sensing techniques for environmental quality and yield prediction, monitoring systems for sustainable development, and the impact of environmental changes on agriculture and crop productivity.

Researchers are also encouraged to present reliable methodologies utilizing remote sensing data, such as satellite imagery and ground-based sensors, to monitor ecological and environmental changes, estimate yield potential, and predict air quality. Contributions from monitoring programs, field experiments, new technologies of remote sensing, and associated laboratory/modeling studies are all welcome. By participating in this Special Issue, researchers will have the opportunity to share their latest advancements, exchange ideas, and foster collaborations in the fields of remote sensing, agricultural monitoring, and air pollution control.

Dr. Jun Li
Dr. Zhen Chen
Dr. Zhixiong 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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Atmosphere 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 2400 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.

Keywords

  • air pollution
  • PM2.5
  • crop yield
  • carbon sinks
  • control strategy
  • econometric model
  • persistent organic pollutants
  • econometric model
  • big data
  • machine learning

Published Papers

This special issue is now open for submission.
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