Advances in Leaf Area Index Estimation: Methods, Products, and Applications

Dear Colleagues,

Leaf Area Index (LAI) is significant indicator for vegetation growing status, and it is also the key parameter of vegetation canopy in response to global change. Meanwhile, LAI relates to many bio-physical processes of vegetation, i.e., photosynthesis, respiration, transpiration, carbon cycle, and precipitation interception. There are various methods in LAI estimation, especially with the development of advanced technology in remote sensing such as lidar, hyperspectral imaging, and some methods with theoretical models These developments bring some great opportunities and challenges. Therefore, the main goal of this Special Issue is to summarize the development achievements of LAI estimation, discuss and look forward to the future development path, and promote the rapid application of LAI products in different fields.

This Special Issue encourages the methods and products of LAI for retrieving vegetation parameters, monitoring environmental quality, and estimating vegetation growing status, among others. Additionally, processing and applications of LAI products in landslides, earthquakes, smart cities, or ecological remediation in the ecologically vulnerable areas (like mines, disater-hit area etc.) are welcome. Related hardware design and retrieval algorithms for ground, airborne, and space-based sensors for LAI estimation are all encouraged. Furthermore, data fusion and assimilation approaches for acquiring new LAI data with higher accuracy and temporal and spatial resolution are encouraged. In summary, we invite submissions exploring cutting-edge research and recent advances in the fields of LAI estimation in this Special Issue; both theoretical and experimental studies are welcome, as well as comprehensive review and survey papers.

Dr. Lin Du
Guest Editor

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