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Land Use Monitoring Based on Remote Sensing and Artificial Intelligence

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

Deadline for manuscript submissions: 29 March 2024 | Viewed by 213

Special Issue Editors

Institute of Agriculture Resource and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: agricultural land use; land use intensity; land use and land cover chang
Special Issues, Collections and Topics in MDPI journals
Geosystems Research Institute, Mississippi State University, 2 Research Boulevard, Starkville, MS 39759, USA
Interests: machine learning; pattern recognition; signal processing; remote sensing
Special Issues, Collections and Topics in MDPI journals
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
Interests: crop monitoring with remote sensing; big earth data for cropland monitoring; agricultural remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land use has always been a key element for the sustainable development of human society. Understanding the state of land use plays a crucial role in urban and rural planning, environmental protection, resource management, and addressing climate change. However, the existing land use monitoring activities largely ignore the multi-faceted characteristics of land use, and the traditional monitoring methods are often limited by factors such as time, space, and cost, making it difficult to meet the precise monitoring needs of large-scale and complex geographical environments.

With the rapid development of sensing technology and artificial intelligence (AI), we now have more powerful tools to address the challenges of land use monitoring. Remote sensing technologies, such as satellite and aerial sensors, can provide high-resolution geographic information data, covering extensive geographic areas. A crowdsourcing approach—supported by smartphones and tablets—transmits on-site land use information to end users if the location is far away from them. Meanwhile, AI methods, including deep learning and machine learning, have the capability to handle large-scale or unstructured data, perform automated classification, and make predictions. This opens up new opportunities for land use monitoring.

By combining remote sensing, crowdsourcing, and AI, we can efficiently obtain land cover information, monitor changes in land use, identify urbanization trends, quantitatively assess the impact of human activities on the environment, and predict future land use trends. This interdisciplinary approach provides more comprehensive and accurate data for land use monitoring, benefiting government decision makers, urban planners, environmental scientists, agricultural experts, and professionals from various fields in gaining a better understanding of dynamic land changes.

This Special Issue will focus on exploring the synergy between advanced sensing technology and AI in the field of land use monitoring and how they collectively drive further advancements in land use monitoring. We look forward to receiving contributions from researchers and practitioners, discussing the latest developments in this interdisciplinary field, and sharing insights on how to better apply these emerging technologies.

Dr. Qiangyi Yu
Dr. Sathishkumar Samiappan
Dr. Miao Zhang
Prof. Dr. Wei Su
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. 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

  • land use
  • remote sensing
  • crowdsourcing
  • artificial intelligence

Published Papers

This special issue is now open for submission.
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