Quantitative Remote Sensing of Vegetation and Its Applications

Dear Colleagues,

Vegetation is the basic component of the terrestrial ecosystem and it plays an important role in energy exchange as well as biogeochemical and hydrological cycling processes on Earth’s surface. Quantitative remote sensing of vegetation can provide spatially and temporally continuous monitoring of Earth’s system parameter data and deliver invaluable insights into diverse fields such as agriculture, forestry, and environment. The past decades have witnessed great progress in satellite remote sensing data processing and the retrieval of Earth’s system parameter, as well as their applications. The advances in monitoring methodologies/technologies, such as empirical statistical models, radiative transfer models, artificial intelligence, and cloud computing technology, have improved the quality and accuracy of remote sensing products. Furthermore, remote sensing products play an increasingly critical role in resolving global environmental issues and climate change mitigation.

This aim of this Special Issue is to advance novel techniques/approaches for retrieving and estimating vegetation structure and function parameters at various spatial (e.g., leaf, canopy, stand, landscape, and regional levels) and temporal scales using remote sensing data across various ecosystems and vegetation types, as well as their applications such as in delineating the responses of vegetation structure and the function of climate change and disturbance in key ecological issues.

Potential topics for this Special Issue may include, but are not limited to, the following:

• Satellite-based vegetation monitoring, estimation, and modeling: techniques (artificial intelligence, multi-sensor data fusion, etc.), evaluation, and future missions;
• Applications of new sensors/algorithms to biochemical/biophysical parameters, such as FVC, LAI, vegetation productivity, biomass, pigments;
• Novel data fusion of spectral, LiDAR, or Radar data obtained from different platforms;
• New product development or evaluation of uncertainty in current products;
• Vegetation degradation and structure variation monitoring using remote sensing;
• Evaluations of ecosystem vulnerability and resilience to climate change;
• Remote sensing applications in global environmental issues;
• Remote sensing applications in efforts to mitigate climate change, such as nature-based climate solutions.

Prof. Dr. Kun Jia
Dr. Linqing Yang
Guest Editors

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