• DocumentCode
    124459
  • Title

    Vegetation phenology monitoring with SeaWinds scatterometer in eastern Asia

  • Author

    Linlin Lu ; Qingting Li ; Huadong Guo ; Cuizhen Wang

  • Author_Institution
    Key Lab. of Digital Earth Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
  • fYear
    2014
  • fDate
    11-14 June 2014
  • Firstpage
    24
  • Lastpage
    27
  • Abstract
    Vegetation phenology tracks plants´ lifecycle events, revealing the response of vegetation to global climate changes. Microwave backscatter is insensitive to signal degradation from solar illumination and atmospheric effects and could provide an alternative data source to optical remote sensing in phenology studies. In this study, we analyzed a time series of Ku-band radar backscatter measurements from the SeaWinds scatterometer on board the Quick Scatterometer (QuickSCAT) to examine its effectiveness for vegetation phenology monitoring across eastern Asia. Phenological metrics including the start of season (SOS) and end of season (EOS) were derived from time series of backscatter data with a weighted curve fitting method. Comparing with MODIS phenology products, backscatter detects earlier greenup dates for the grasslands in Kazakhstan and eastern Tibetan Plateau and forests in southern and northern China areas. For agricultural lands in the middle of China and northern India, the backscatter data shows later greenup dates than MODIS data. The backscatter EOS is later the MODIS senescence dates in most areas, whereas showing spatial patterns agreeing with regional climate gradients. In the grasslands in Kazakhstan, Mongolia and China, the EOS detected by MODIS is later than backscatter data. The bias of backscatter phenological metrics and MODIS products might be caused by the temporal shifts between backscatter increase and canopy greenups. Overall, the results indicate that SeaWinds backscatter is sensitive to seasonal canopy dynamics across a range of vegetation types and provides a quantitative view that is independent of optical/NIR remote sensing instruments.
  • Keywords
    climatology; curve fitting; phenology; radiometry; remote sensing; time series; vegetation mapping; China grassland; Kazakhstan grassland; Ku-band radar backscatter measurement time series; MODIS data greenup date; MODIS phenology product; MODIS product; MODIS senescence date; Mongolia grassland; Quick Scatterometer; QuickSCAT; SOS; SeaWinds scatterometer; agricultural land; alternative data source; atmospheric effect; backscatter EOS; backscatter data; backscatter data time series; backscatter increase temporal shift; backscatter phenological metric bias; canopy greenup temporal shift; earlier greenup date bacscatter detection; eastern Asia; eastern Tibetan Plateau; end-of-season; global climate change; microwave backscatter; middle China; northern China area; northern India; optical remote sensing; optical-NIR remote sensing instrument; plant lifecycle event tracking; regional climate gradient spatial pattern; seasonal canopy dynamic; solar illumination signal degradation; southern China area; start-of-season; vegetation phenology monitoring effectiveness; vegetation response; vegetation type range; weighted curve fitting method; Backscatter; Earth Observing System; MODIS; Meteorology; Remote sensing; Time series analysis; Vegetation mapping; phenology; radar backscatter; scatterometer; time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Earth Observation and Remote Sensing Applications (EORSA), 2014 3rd International Workshop on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-5757-6
  • Type

    conf

  • DOI
    10.1109/EORSA.2014.6927842
  • Filename
    6927842