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Advanced Application of Artificial Intelligence and Machine Vision in Remote Sensing III

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 189

Special Issue Editor

1. Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW, Australia
2. McGregor Coxall Australia Pty Ltd., Sydney, NSW, Australia
Interests: machine learning; geospatial 3D analysis; geospatial database querying; web GIS; airborne/spaceborne image processing; feature extraction; time-series analysis in forecasting modelling and domain adaptation in various environmental applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to introduce a new Special Issue, building upon the success of our previous endeavor, “Advanced Application of Artificial Intelligence and Machine Vision in Remote Sensing”. This forthcoming edition dives deeper into the confluence of cutting-edge technology, with a particular focus on drone-based and LiDAR-based image processing as well as the integration of artificial intelligence (AI) in urban planning.

Over the last decade, AI and machine learning (ML) techniques have significantly impacted image processing and spatial analysis across various applications. AI has empowered us to unlock the true potential of imagery data, employing tailored algorithms for tasks such as classification, regression, clustering, spatial correlation modeling, and more. Deep neural networks, commonly known as deep learning, stand out as powerful tools within this domain, performing functions like pattern recognition, feature detection, trend prediction, instance segmentation, semantic segmentation, and image classification within neural network frameworks.

Traditionally, structured remotely sensed data often required painstaking manual labelling for training models, a subjective and non-transferable process. To address these challenges, "machine vision" (MV) has emerged as a holistic solution, streamlining the workflow from image acquisition to knowledge extraction. MV leverages AI technology to minimise computation time and maximise replicable accuracy, encompassing software products and hardware architectures such as CPUs, GPU/FPGA combinations, parallel processing, and computer vision techniques.

In this Special Issue, we invite scholarly manuscripts proposing frameworks that combine machine vision with state-of-the-art AI techniques and geospatial information systems to automate the processing of remotely sensed imagery from diverse sources, including drones, LiDAR, radar, SAR, and multispectral sensors. The primary objective is to achieve higher precision in a range of spatial applications, from urban planning to environmental studies, weather and climate analysis, the energy sector, natural resource management, landscape assessment, and geo-hazard monitoring.

As we explore this Special Issue, we anticipate groundbreaking contributions that will reshape urban planning and related domains. These endeavors, enriched by drone-based and LiDAR-based image processing, alongside innovative image processing AI, will guide us towards a more intelligent, efficient, and sustainable future.

Dr. Hossein M. Rizeei
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at 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. 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.


  • artificial intelligence (AI)
  • machine vision (MV)
  • machine learning (ML)
  • geospatial information systems (GIS)
  • optimisation
  • spatial framework
  • deep learning (DL)

Related Special Issues

Published Papers

This special issue is now open for submission.
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