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Remote Sensing Applied in Urban Environment Monitoring

This special issue belongs to the section “Urban Remote Sensing“.

Special Issue Information

Dear Colleagues,

(1) Introduction, including scientific background and highlighting the importance of this research area.

The world is witnessing an unprecedented rate of urbanization, which brings forth complex challenges in environmental management, public health, and sustainable development. Remote sensing technology, with its capability for synoptic, repetitive, and objective observations, has become an indispensable tool for monitoring and understanding the intricate dynamics of urban environments. The advent of massive amounts of multi-source, multi-temporal data, coupled with breakthroughs in Geospatial Artificial Intelligence (GeoAI), is revolutionizing this field. These advancements enable us to move beyond traditional mapping towards modeling complex urban processes, predicting future scenarios, and assessing human exposure to environmental risks with unprecedented accuracy and detail.

(2) Aim of the Special Issue and how the subject relates to the journal scope.

This Special Issue, “Remote Sensing Applied in Urban Environment Monitoring,” aims to compile the latest innovative research and practical applications that address the multifaceted challenges of contemporary cities. It seeks to highlight how modern remote sensing data—from very-high-resolution optical and SAR satellites to UAVs and LiDAR—combined with advanced analytical methods, such as machine learning, deep learning, and data fusion, are transforming our understanding of urban systems. This topic is central to the scope of Remote Sensing, which is dedicated to the science and application of remote sensing technology, fostering the dissemination of cutting-edge research featuring data collection, analysis, and interpretation.

(3) Suggested themes and article types for submissions.

We encourage submissions on topics including, but not limited to, the following:

  • GeoAI for urban land use/cover mapping and change detection.
  • Monitoring urban redevelopment and renewal processes.
  • Assessing environmental exposure (e.g., heat, air pollution, green space).
  • Urban infrastructure and settlement analysis.
  • Social sensing and remote sensing data fusion for urban studies.
  • Sustainable Development Goal (SDG) 11 monitoring.

Dr. Peixiao Wang
Dr. Yan Zhang
Dr. Tao Hu
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.

Keywords

  • urban remote sensing
  • GeoAI
  • environmental exposure
  • urban redevelopment
  • sustainable cities
  • geospatial big data
  • machine learning
  • SDG 11

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Remote Sens. - ISSN 2072-4292