Satellite Applications for Detecting Vegetation Phenology - Satellite-based Applications on Climate Change - page 260

17.3 Applications
The vegetation phenology derived from satellite-based sensors with a variety of
spatial and temporal resolutions has been utilized for tracking vegetation dynamics,
invasive species, and land cover changes as well as assessing crop conditions,
drought severity, and wildfire risk. Since phenological events are sensitive to climate
variation, satellite-derived phenology data also represent a powerful tool for
detecting the response of terrestrial ecosystems to climate change at multiple scales.
Satellite sensors have their own 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.
17.3.1 Landsat-Derived Vegetation Phenology
For monitoring vegetation phenology at regional scale, the Landsat data offers three
primary advantages. First, with more than 30 years of data archive, it provides the
longest-running time series of systematically collected remote sensing data. Second,
the 30-m spatial resolution facilitates landscape characterization. Third, the free-of-
charge data through the US Geological Survey (USGS) make it possible to acquire by
all researchers.
Landsat data have been translated into useful phenological behavior both on the
methods and applications. A “temporal profile” model (Badhwar 1984a , b )that
simulates phenological dynamics as a quadratic rise and exponential decay has been
utilized to extract features to classify the agriculture crops. Goetz and Prince ( 1996 )
have used the species-specific foliar phenology to estimate the amount of incident
photosynthetically active radiation (PAR) and further to estimate the net primary
production (NPP) in boreal forest stands. Fisher et al. ( 2006 )haveprovidedan
approach to bridge the in situ, plot-level phenological measurements and satellite-
derived phenological metrics through Landsat data and quantified the accuracy
by comparing the half-maximum leaf onset and offset. Although Landsat's 16-day
repeat cycle does not provide readily available data for the rapidly changing pheno-
logical stages, application of Landsat data paved the way for remote sensing-based
phenology, and the development of new methodologies can potentially overcome the
shortcomings of Landsat series.
17.3.2 AVHRR-Derived Vegetation Phenology
Current research using satellite sensors with a more frequent repeat cycle dominates
the study of remote sensing phenology. The AVHRR provides data globally with
daily repeat cycle since the 1980s. A variety of AVHRR collections are available
for phenology study. AVHRR vegetation index data are available in a consistently