USA NPN National Phenology Network

Taking the Pulse of Our Planet

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Remote Sensing for Phenology

Applications of Landsat data paved the way for remote sensing-based phenology and these data are still used for some applications. However, current research using satellite sensors with a more frequent repeat cycle currently dominate the field. The longest-running series of high repeat-frequency sensors is the National Oceanic and Atmospheric Administration’s (NOAA) advanced very high resolution radiometer (AVHRR). The AVHRR series has a near daily repeat cycle of the Earth and a 1km spatial resolution. Both the temporal density of the data and the moderate spatial resolution make this sensor well suited for studying large area phenology. AVHRR vegetation index data are available in a consistently processed database from 1982 at an 8km resampling grid covering the globe (http://glcf.umiacs.umd.edu/data/gimms/) and at 1km resolution from 1989 covering the conterminous United States (http://earthexplorer.usgs.gov/). More recent and much better calibrated moderate resolution satellite sensors that have the proper instrumentation for studying vegetation greenness include SPOT Vegetation (1-km data, launched in 1998) and Envisat MERIS (300-m data, launched in 2002). The moderate resolution imaging spectroradiometer (MODIS) launched in December, 1999, and MODIS is frequently used for phenology studies. Improved geometry, radiometry, and overall data quality of MODIS, combined with its free-of-charge data policy, provide readily available high quality data for time-series analysis. One of the standard MODIS land products is the MOD12Q2 product (Land Cover Dynamics), distributed from the Land Processes Distributed Active Archive Center, which includes phenological data.

The key phenological variables that are often estimated from satellite remote sensing are the start, end, and length of the growing season. These metrics are derived using algorithms that are based on a number of strategies, including threshold values, inflection points in time-series greenness curves, or rates of change in vegetation index values.

The seasonal pattern of variation in vegetated land surfaces that can be observed from remote sensing can be described by the term land surface phenology. While the observed patterns are certainly related to biological phenomena, land surface phenology is distinct from traditional definitions of vegetation phenology, which refer to specific life cycle events such as budbreak, flowering, or leaf senescence using in situ observations of individual plants or species. Although the meaning of land surface phenology in many ecosystems is clear, there are many environments in which the precise meaning is less clear such as mixed forests, evergreen forests and drylands.