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
Link To Document :
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