Vegetation Cover Changes Monitoring Using Remote Sensing Data

Dear Colleagues,

The alarming rates of global deforestation and the significant impacts of climate variations on crop production and vegetation health emphasize the critical need for precise vegetation monitoring. Current trends reveal that climate-induced changes are causing substantial shifts in vegetation patterns and are reducing agricultural productivity. The Special Issue “Vegetation Cover Changes Monitoring Using Remote Sensing Data” aims to investigate advanced remote sensing technologies to address these urgent challenges. By integrating big data to manage large datasets from high-resolution sensors, this issue explores advancements in satellite imagery and ground-based sensors for detailed vegetation analysis. Innovative data processing algorithms and enhanced analysis techniques are highlighted, focusing on the impacts of climate change and human activities on vegetation cover. This issue also addresses challenges such as data interoperability and the scalability of remote sensing applications, particularly in developing countries where high-resolution datasets are crucial. This collection aims to support the United Nations' Sustainable Development Goals (SDGs) by providing findings that contribute to sustainable environmental management and urban planning. We encourage contributions that tackle remote sensing data acquisition, processing, interpretation, and integration with other geospatial technologies and ground-based measurements.

We aim to answer questions such as the following:

• What are the latest advancements in remote sensing technologies for vegetation cover monitoring, and how do these technologies enhance the detection and analysis of vegetation changes?
• How can the fusion of multi-source remote sensing data improve the accuracy and reliability of vegetation cover assessments?
• What novel data processing algorithms and methodologies are being developed for detecting and quantifying vegetation changes, and how do they compare efficiency and accuracy?
• How can machine learning and artificial intelligence be utilized to improve the analysis and interpretation of remote sensing data for vegetation monitoring?
• What are the challenges and solutions for ensuring data interoperability and scalability of remote sensing applications, particularly in developing countries with limited access to high-resolution datasets?
• How do seasonal variations and extreme weather events influence vegetation cover changes, as observed through remote sensing data?
• What are the long-term trends in vegetation cover changes across different biomes and ecosystems, and how can remote sensing data help predict future scenarios?
• How can time-series analysis of vegetation cover changes be utilized to understand vegetation dynamics at different spatial scales, from local to global?

Dr. Dong Liang
Dr. Barjeece Bashir
Dr. Min Xu
Guest Editors

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• vegetation cover change
• remote sensing
• high spatial resolution
• big data
• satellite imagery
• data processing algorithms
• multi-source data integration
• climate change impacts
• biodiversity monitoring
• land management