Special Issue "Advanced Remote Sensing Imaging for Environmental Sciences"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: 31 October 2023 | Viewed by 168

Special Issue Editors

1. Graduate School, Northern Arizona University, Flagstaff, AZ 86011, USA
2. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
Interests: neural networks; forecast modeling; deep learning
Special Issues, Collections and Topics in MDPI journals
School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China
Interests: time-series prediction; pattern recognition; deep learning; blockchain traceability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Remote sensing imaging is an active source of spatial information which has been proven to be effective in measuring and monitoring the environment. Conversely, hyperspectral remote sensing imaging combines imaging technology with spectral detection technology, which is characterized by integrating image information of the sample with spectral information. Thus, remote sensing images contain information that can reflect external quality characteristics, such as the size, shape, and defects of the sample. However, different components have different spectral absorption capacities, and so the image will reflect defects at a certain wavelength more significantly, while the spectral information can fully reflect the sample. Differences in internal physical structure and chemical composition determine the unique advantages of hyperspectral image technology in environmental science applications and are widely used in environmental resource detection and environmental monitoring tasks. However, the ability of existing methods to identify features is significantly affected by the high data dimensionality and massive information redundancy of hyperspectral remote sensing data. To solve the above problems, we must develop a variety of advanced hyperspectral remote sensing imaging analysis techniques for use in environmental monitoring systems.

This Special Issue encourages scholars and experts to submit works that systematically explore various advanced remote sensing imaging methods for application to environmental science to provide new ideas and references for exploring and addressing pressing environmental science issues. We welcome both original research and review articles.

Dr. Weiwei Cai
Dr. Jianlei Kong
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. Applied Sciences 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 2300 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.


  • advanced remote sensing imaging
  • environmental resource detection
  • hyperspectral image classification
  • environmental monitoring
  • advanced machine learning methods
  • neural networks
  • feature selection of complex environmental data
  • smart monitoring system
  • prediction of environmental pollution
  • multi-sensor data fusion

Published Papers

This special issue is now open for submission.
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