Time-Series Mapping and Analysis of Land Surface Parameters and Changes Using Remote Sensing Data

Dear Colleagues,

In this era of rapid global change, it is of utmost importance to understand the dynamics of the Earth’s surface. Land surface parameters, encompassing land cover and land use types, vegetation structure, biochemical parameters, and soil parameters, serve as indispensable indicators of environmental well-being, providing crucial insights into multi-scale environmental changes, including climate change, urbanization, and deforestation. The advent of multi-source remote sensing, particularly satellite remote sensing, has revolutionized our ability to monitor land surface parameters at unprecedented spatial and temporal scales. As a result, time-series mapping and analysis have emerged as powerful tools for tracking and predicting land surface changes over time. Advanced research into the applications of time-series remote sensing for mapping and analyzing land surface parameters and their associated dynamic changes will empower people to enhance global land use management and monitoring.

This Special Issue of Remote Sensing, entitled “Time-series Mapping and Analysis of Land Surface Parameters and Changes”, aims to showcase cutting-edge research that harnesses the potential of time-series data to understand the dynamics of land surface parameters. We invite contributions that:

• Develop data pre-processing algorithms for time-series mapping and analysis.
• Develop novel methodologies for retrieving, estimating, and mapping land surface parameters.
• Develop novel approaches for time-series mapping of land surface changes (including land cover and land use changes, land or forest disturbances, forest transitions, etc.).
• Employ remote sensing data to study long-term trends, cyclic patterns, or abrupt changes in land surface parameters.
• Integrate multi-source data, including ground observations, to validate and enhance the accuracy of remote sensing-derived time-series datasets.
• Explore the implications of land surface changes on ecosystems, climate, and human societies.

By bringing together a collection of high-quality research articles, this Special Issue seeks to foster a deeper understanding of the Earth’s changing landscapes and to promote the development of innovative solutions for sustainable land management. Potential authors are encouraged to contribute their expertise and research insights in order to enrich the global discourse on the importance of time-series mapping and analysis in the realm of remote sensing.

Dr. Rong Shang
Dr. Wang Li
Dr. Xiaobin Guan
Dr. Su Ye
Dr. Feng Zhao
Dr. Naoto Yokoya
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.

• time-series mapping
• time-series analysis
• change detection
• dynamic monitoring
• data pre-processing
• data fusion
• land surface parameters
• vegetation structure parameters
• vegetation biochemical parameters
• land cover mapping
• land disturbance
• forest disturbance
• remote sensing