Application of Artificial Intelligence in Land Use and Land Cover Mapping II
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: closed (1 July 2024) | Viewed by 30654
Special Issue Editors
2. Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, University of the Punjab, Lahore, Pakistan
3. Department of Land Survying and Geo-Informatics, The Hong Kong Polytechnic, University, Hong Kong
Interests: earth obsersation and analytics; spatial data science; digital technologies; smart cities; environmental monitoring; landscape ecology; forest; urban ecologyurban climate; climate change; land-cover and land-use change; drought; cropland; air pollution; water quality; cloud computing; machine learning; big data for SDGs
Special Issues, Collections and Topics in MDPI journals
Interests: geo-informatics; environmental change; landscape change; urban climate; air pollution; climate change; tropical forest ecology; aerosols
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; land degradation; croplands; droughts; environmental monitoring; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: land cover land use change; landscape restoration; biodiversity conservation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nexus of data analytics and computer vision with remote sensing data has revolutionised the information extraction of earth’s features. The rapid evolution of Artificial Intelligence and Earth Observation technologies is providing enhanced insights into landscape change and sustainable development. Land-use change data from satellite remote sensing, along with climate modelling and socio-economic indicators are playing vital roles in advancing interdisciplinary research. The huge amount of data currently produced by modern Earth Observation satellite missions and Unmanned Aerial Vehicles (UAVs), the availability of high-performance computing platforms and the development of Artificial Intelligence provide new opportunities to advance our knowledge about patterns of resource distribution and resource use. Machine learning approaches tailored for Earth Observation data can effectively support the challenges of spatial and temporal domain adaptation, hyperspectral data mining, integration of multi-source information and large-volume data analysis.
The previous special issue “Application of Artificial Intelligence in Land Use and Land Cover Mapping” was a great success. This indicates that the development of new approaches for information extraction from remote sensing data using Artificial Intelligence is incessant. Therefore, this second volume is launched aiming at collecting articles capitalizing on the integration of emerging remote sensing technologies and recent advances in computer vision and machine learning.
We welcome submissions that provide the community with the most recent advancements in all aspects mentioned above. We welcome, Original Research Articles, Reviews, Letters, and Technical Notes, as well as Highlight articles for a broader audience.
Dr. Sawaid Abbas
Prof. Dr. Jianchu Xu
Dr. Faisal M. Qamer
Prof. Dr. Janet E. Nichol
Guest Editors
Manuscript Submission Information
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Keywords
- object detection in remote sensing images
- dynamic features extraction
- land cover
- land use
- monitoring change
- urban morphology
- hyperspectral mapping
- machine learning and deep learning
- pattern recognition and data mining
- hyper-temporal mapping
- biophysical and social data integration
- sustainable development goals (SDGs)
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