Progress and prospects of crop phenology remote sensing monitoring research
[purpose]The phenological period is a crucial growth information for crops.It has significant impliactions for crop growth monitoring,field management,phenological zoning,rational crop allocation,and agricultural decision making.[Method]Using the methodology of literature review and condensation,this article retrospectively reviewed the progress made in remote sensing monitoring of crop phenology.Firstly,it delved into the traditional approach based on time-series optical vegetation indices,examining both data pre-processing and phenology extraction algorithms.Secondly,it introduced the applications of Synthetic Aperture Radar(SAR),Unmanned Aerial Vehicle(UAV)remote sensing,and phenocameras in crop phenology monitoring.Finally,it provided an outlook on the research directions that were being pursued in remote sensing monitoring of crop phenology at that time.[Result]Remote sensing based crop phenology monitoring had been widely applied due to its advantages of large coverage,high detection frequency,minimal human subjectivity,and low cost.The use of satellite-derived optical vegetation index time series and the extraction of crop phenophases based on these indices was the most prevalent monitoring approach at that time.In addition,advancements in observational technologies such as Synthetic Aperture Radar(SAR),Unmanned Aerial Vehicle(UAV)remote sensing,and phenocameras also enriched the means of crop phenology monitoring.Depending on the remote sensing platform,these methods could be categorized into spaceborne observation platforms,airborne observation platforms,and near-surface observation platforms.[Conclusion]The development of remote sensing technologies for crop phenology monitoring contributes to providing scientific and accurate decision support for farmers and agricultural managers,thereby promoting a more sustainable direction for agricultural production.
crop phenologyremote sensingUnmanned Aerial Vehicle(UAV)Synthetic Aperture Radar(SAR)phenological camera
NETL
NSTL
万方数据
