Satellite Applications for Detecting Vegetation Phenology

  • Min Li
  • John J. Qu


Vegetation phenology describing the seasonal cycle of plants is currently one of the main concerns in the study of climate change and carbon balance estimation in ecosystems. Satellite-derived information has been demonstrated to be an important source for detecting vegetation phenology. A variety of methods have been developed to generate phenological metrics from satellite measurements varying from empirically, simple threshold of vegetation index to automated, elaborate logistic model. Each method provides certain advantages and paves the way for the success of satellite-derived vegetation phenology. The vegetation phenology derived from satellite measurements has been utilized for tracking vegetation dynamics, invasive species, and land use changes as well as assessing crop conditions, drought severity, and wildfire risk. Satellite sensors have their specific characteristics of temporal and spatial resolution, spatial coverage, and data quality and archive history. Each satellite takes advantages of its respective strengths to provide certain phenological applications. Despite the insights gained form satellite observations of vegetation phenology, the scale problem brings a big challenge for comparing satellite-derived vegetation phenology and ground records. In the future, more detailed information of ground records together with phenophases of individual species could be integrated to reflect the canopy phenology and compared with the satellite-derived phenology. The well-validated vegetation phenology from satellite measurements will contribute to the improvement in ecosystem process models.


Normalize Difference Vegetation Index Leaf Area Index Advance Very High Resolution Radiometer Advance Very High Resolution Radiometer Satellite Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.I. M. Systems Group, IncCollege ParkUSA
  2. 2.Department of Geography and GeoInformation Science, Environmental Science and Technology CenterGeorge Mason UniversityFairfaxUSA

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