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Remote Sensing data product Contribution from data providers/algorithm development team

Remote Sensing data product Contribution from data providers/algorithm development team. Data from many moderate resolution remote sensing sensor, mainly vegetation indices at a compositing period We broadly follow three steps to derive phenological matrices Data filtering

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Remote Sensing data product Contribution from data providers/algorithm development team

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  1. Remote Sensing data product Contribution from data providers/algorithm development team

  2. Data from many moderate resolution remote sensing sensor, mainly vegetation indices at a compositing period • We broadly follow three steps to derive phenological matrices • Data filtering • Temporal smoothing (many methods) • Derived matrices ( many method and many matrices) JÖNSSON and EKLUNDH, 2004

  3. MODIS NACP Phenology ProductsRetrieved Phenology Metrics Beginning of season End of season Length of season Base VI value Peak time Peak value Amplitude Left derivative Right derivative Integral over season - absolute Integral over season - scaled Maximum value Minimum value Mean value RMSE of fitting

  4. MODIS NACP Phenology ProductsAvailability and Status • Availability: From http://accweb.nascom.nasa.gov/ • Products: phenology metrics derived from LAI/EVI/NDVI, and original, smooth/gap-filled LAI, FPAR, EVI & NDVI. • Temporal Coverage: From 2001 to 2010. • Spatial Coverage: Full North America, partially South America. Asia is under processing. • Online data services: • Subset by geographic area • Subset by data layer • Reproject • Mosaic • Aggregation • Re-format (to GeoTIFF).

  5. MCD12Q2 C5 Product • Global database • Annual since 2001, 500-m • Includes 7 metrics • Onset of EVI increase • Onset of EVI maximum • Onset of EVI decrease • Onset of EVI mimimum • Min EVI • Max EVI • Sum of growing season EVI • Validation: • Opportunistic, largely in New England • Current focus on PhenoCam Data Timing Annual Metrics Mark Friedl

  6. USGS EROS Vegetation Dynamics • Availability: From http://phenology.cr.usgs.gov// • Products: Nine annual remote sensing phenological indicators (served as raster data sets) are available at two spatial resolutions (1000 m2 and 250 m2) based on NDVI • Temporal Coverage: AVHRR (1989-2011) • MODIS (2001-2011) • Spatial Coverage: conterminous U.S. • Method : Delayed Moving Average (DMA) method (Reed et al., 1994). • Considerable QA checking done on USGS phenological data Jesslyn Brown

  7. Phenological metrics available at multiple resolutions Jesslyn Brown

  8. Phenological metrics available at multiple resolutions Jesslyn Brown

  9. Jesslyn Brown

  10. The “VGT4Africa” phenology product • Algorithm developed by the Joint Research Centre (European Commission) • Product generated by VITO (Belgium) • Based on the processing of a moving time-window of 1.5 year of NDVI from the VEGETATION instrument • Updated within 3 days after every 10-day period (“dekad”) • Covers the whole African continent • Provides dekad dates for “start of growth”, “max NDVI” and “half-senescence” • Availability: from VITO through ftp and EUMETCast, jan 2007 until present • Product description: Combal B. & Bartholomé E. 2006: Phenology. In: Bartholomé edit: VGT4Africa user manual 1st edition, European Commission ref EUR 22344 EN: 165-212 • Method: Combal B. & Bartholomé E. 2010: Retrieving phenological stages from low resolution Earth observation data. In: Maselli & al.: Remote Sensing Optical Observations of Vegetation Properties, Research Signpost, Kerala, India, 115-129. Bartholomé

  11. Start dates as observed on 3rd dekad of Dec 2011 (note: actual time resolution of the product is the dekad, not the month) Bartholomé

  12. VIP Data Explorer:30 Years of Multi-Sensor VI and Phenology Data • Availability: From vip.arizona.edu/viplab_data_explorer.php • Products: Vegetation index and phenology from AVHRR, VEGETATION, MODIS (Sensor independent) • Temporal Coverage: 30+ • Spatial Coverage: Global • Spatial resolution : 0.05 deg • Considerable data quality assessment Kamel Didan

  13. Kamel Didan

  14. PHAVEOS – the Phenology And Vegetation EO Service • A service to provide: • Vegetation maps of several biophysical variables relevant to models of bio-geochemical cycles • Leaf Area Index (LAI) • fraction of Absorbed Photosynthetically Active Radiation (fAPAR) • MERIS Terrestrial Chlorophyll Index (MTCI) • fraction of green land cover (fCover) • Continuous time series to support phenology studies and monitoring • Visualisation of individual maps and phenology curves for individual locations Thomas Lankester

  15. Sentinel 3 Sentinel 2 (LDCM) Data sources MERIS / MODIS Biophysical processing and mapping HiProGen and Overland Daily Level 3 and Level 4 data dissemination Web client on user PC WebServer

  16. Level 3 daily product examples fCover LAI fAPAR

  17. Spring 2009 – 2010 comparison ftp://l3-server.infoterra.co.uk/pub/SNL/MTCI_L4_2009-2010_comparison.gif

  18. Core Site Selection Original Sites (2010 Dublin Workshop): • Do we keep the original sites? • Are more sites needed? • What are the essential variables and is it necessary for every site to offer the same set of core variables/instruments? Phenology Land Product Validation Workshop

  19. Panel Discussion • What standards need to be set for Phenology LPV: • Are standardized definitions needed for metrics? – Start of Season, End of Season • Are standardized methods needed to calculate metrics? – Curve fitting, Derivative peaks, etc. • What do we mean by Phenology Validation? Is it setting a realistic offset/error range between phenocam or in-situ and RS metrics? Is this application specific? • What are best practices for LPV using in-situ data? Phenology Land Product Validation Workshop • Working across scales: • Are site specific nested datasets (in-situ, phenocam, RS) and validation results applicable to validation of continental/global RS phenology products? • Do PhenoCams need to be validated with in-situ observations?

  20. Pilot Project Definition • Core Sites Selection and Considerations: • Do we agree upon the site selections? • Is all data freely available? Creation of formal data sharing agreement. Phenology Land Product Validation Workshop • Data Collections/Bundles: • RS products – size of subset over each site, 100km? • Centralized Storage and Access • Ground/In Situ Site Data – centralized storage? • Project Objectives: • Do we allow for a flexible structure and let researchers dictate site by site analysis OR do all projects follow a set protocol? • Timeline – What is a realistic expectation? The LPV 5yr Plan states Validation Protocol established by 2013. • Responsible Parties: • Data Collections/Bundles – must be available by…? • Who will conduct the research? PhD Students, Post-Docs, Staff Scientists.

  21. Workshop Review • Did we meet our objectives? • Provide a synopisis of the majority available data sets. • Review and discuss validation methods, current limitations and concerns. • Selection of Core Sites. • Agreement on data subsets, storage and access. • Define Pilot Projects. • Set a course for future Land Surface Phenology Validation Phenology Land Product Validation Workshop • For the future: • Do responsible parties understand their tasks (providing data, analysis, etc.) • Write up of a Meeting Summary Publication – EOS. • Summary Poster for AGU – Jadu and Matt with input from committee. • Informal Meeting at AGU 2012 to discuss progress.

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