Time-Series Mapping and Analysis of Land Surface Parameters and Changes Using Remote Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 539
Special Issue Editors
Interests: vegetation remote sensing and carbon neutrality; remote sensing big data; dynamic monitoring of land surface changes
Interests: remote sensing of vegetation ecosystem structure and functioning; land cover dynamics; ecoinformatics; ecosystem restoration and conservation
Special Issues, Collections and Topics in MDPI journals
2. Department of Geography and Planning, University of Toronto, No. 100 St. George St., Toronto, ON M5S 3G3, Canada
Interests: remote sensing; urban vegetation; vegetation index; spatial-temporal reconstruction; ecosystem carbon cycle; climate change
Special Issues, Collections and Topics in MDPI journals
Interests: land disturbance; agricultural remote sensing; time series analysis; near real-time monitoring
Interests: forest disturbances; multi-source remote sensing; artificial intelligence
Interests: image processing; data fusion; machine learning for understanding remote sensing images; applications to disaster management and environmental monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
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
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Keywords
- 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
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