Leveraging Multitemporal Remote Sensing Data for Land Use and Land Cover Classification

Dear Colleagues,

The dynamic nature of Earth’s surface necessitates advanced methodologies for accurate and timely land use and land cover classification. Multitemporal remote sensing data, by capturing seasonal and phenological patterns, provide valuable information that is not discernible in single-date imagery. Moreover, leveraging sequences of observations helps mitigate issues of sensor noise, cloud cover gaps, and land‐surface variability, paving the way for robust, scalable workflows that keep pace with dynamic environmental change.

This Special Issue aims to consolidate cutting-edge research that leverages multitemporal remote sensing data for land use and land cover classification. We welcome contributions that integrate multitemporal remote sensing datasets with modern analytical techniques to enhance classification. Studies may employ a range of approaches, from traditional machine learning classifiers to advanced AI models with deep learning architectures, handling variability in data sources, temporal sampling, and spatial detail. Articles may address, but are not limited to, the following topics:

• Algorithmic developments;
• Advanced AI and deep learning models for analyzing multitemporal remote sensing data;
• Integration of spectral indices;
• Multimodal data fusion combining optical, SAR, and other remote sensing data;
• Development of benchmark datasets and evaluation metrics for multitemporal land use and land cover classification;
• Applications of multitemporal analysis in monitoring changes, urban expansion, deforestation, burned areas, mining sites, and agricultural dynamics.

Dr. Ioannis Kotaridis
Dr. Hazem Ghassan Abdo
Dr. Linlin Lu
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.