9. The USGS EROS Data Center has developed a data set of seasonal metrics derived from multitemporal Advanced Very High Resolution Radiometer (AVHRR) satellite sensor Normalized Difference Vegetation Index (NDVI) observations. (http://edc2.usgs.gov/phenological/)
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11. Figure 1 is an animated loop of the NDVI observed over Colorado from 1990 through 1996. http://geochange.er.usgs.gov/sw/impacts/biology/Phenological-CO/
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19. The full set of metrics and their phenological interpretation are shown above. Note that the phenological interpretation is not an absolute value of photosynthesis, but the phenological metrics are surrogates for such values. Deceleration of photosynthesis Rate of senescence Acceleration of photosynthesis Rate of greenup Photosynthetic activity in growing season Seasonally integrated NDVI Maximum level of photosynthetic activity Maximum NDVI Level of photosynthetic activity at EOS NDVI at end of growing season Level of photosynthetic activity at SOS NDVI at start of growing season Time of maximum photosynthesis Time of Maximum Greenness - Julian Day Duration of photosynthetic activity Duration of Growing Season Cessation of measurable photosynthesis Time of End of Season (EOS) Julian Day Beginning of measurable photosynthesis Time of Start of Season (SOS) Julian Day Phenological Interpretation Phenological Metric
20. Metric Data gzip.file 131 Mb readme Cessation of measurable photosynthesis (1989-2001) End of Season Date gzip.file 70 Mb readme Level of photosynthetic activity at SOS (1989-2001) Start of Season NDVI gzip.file 129 Mb readme Beginning of measurable photosynthesis (1989-2001) Start of Season Date gzip.file 83 Mb readme Simulated Net primary production (1989-2001) Seasonal Integrated NDVI Image File More Info Description Metric Name
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30. Smoothing Swets, D.L., B.C. Reed, J.R. Rowland, S.E. Marko, 1999. A weighted least-squares approach to temporal smoothing of NDVI. In 1999 ASPRS Annual Conference, From Image to Information, Portland, Oregon, May 17-21, 1999, Proceedings: Bethesda, Maryland, American Society for Photogrammetry and Remote Sensing, CD-ROM, 1 disc.
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33. North side of SF Peaks Between SF Peaks and South Rim, GC North Rim, GC South Rim, GC
41. Phenology and Drought Monitoring Projects Phenology: Bradley Reed [email_address] http://edc2.usgs.gov/phenological Drought Monitoring: Jesslyn Brown [email_address] http://edc2.usgs.gov/phenological/drought/ Phenology is the study of the timing of biological events, particularly in response to climatic changes to the environment. Certain biological events, such as the time of the start of the growing season, have a key role in changing land surface/atmosphere boundary conditions such as surface roughness, albedo, humidity, etc. The phenology of ecosystems and its connection to climate is a key to understanding ongoing global change. The use of satellite imagery provides a unique vantage point for observing seasonal dynamics of the landscape. The USGS EROS Data Center has developed a data set of seasonal metrics derived from multitemporal Advanced Very High Resolution Radiometer (AVHRR) satellite sensor Normalized Difference Vegetation Index (NDVI) observations for the conterminous U.S. By analyzing the time-series vegetation index (Fig. 1), a set of algorithms derive phenology metrics such as onset, end, and duration of growing season. The output of these metrics then may be analyzed to produce products, such as temporal trends in integrated NDVI values (Fig. 2) Droughts are normal recurring climatic phenomena that vary in space, time, and intensity. They may affect people and the landscape at local scales for short periods or cover broad regions and have impacts that are felt for years. The spatial and temporal variability and multiple impacts of droughts provide challenges for mapping and monitoring on all scales. A team of researchers from the USGS EROS Data Center, the National Drought Mitigation Center (University of Nebraska) and the High Plains Regional Climate Center are developing methods for regional-scale mapping and monitoring of drought conditions for the conterminous U.S. The goal is to deliver timely geo-referenced information about areas where the vegetation is impacted by drought. We are integrating information provided by satellite-derived phenology metrics (Fig. 3) and climate-based drought indicators (Fig. 4) to produce a timely and spatially detailed drought monitoring product. Research and methods for Drought Monitoring are developed in tandem with Phenological Characterization. Figure 1 Figure 2 Figure 3 Figure 4
Hinweis der Redaktion
To eliminate the spurious data, which can affect algorithms that are searching for increasing or decreasing trends representing real phenological shifts, a temporal smoothing of the data is typically perfromed.
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