IGARSS 2011, July 24-29, 2011, Vancouver, Canada
The Annual Behavior of Backscattering And Coherence of PALSAR Data
Wenjian Ni1,2, Zhifeng Guo1, Zhiyu Zhang3 , Guoqing Sun2
1Institute of Remote Sensing Applications of Chinese Academy of Sciences 2Department of Geography, University of Maryland, College Park
3Beijing Normal University
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
OutLine 1. Introduction
2.Test site and data
3. The annual behavior of Backscattering
4. The annual behavior of Coherence
5.Conclusion
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
• PALSAR Mosaic data provide a great chance to map biomass at regional scale;
• The data covered a year and several seasons.
• The seasonal effects on coherence have been investigated using ERS1/2 tandem (Koskinen, J.T. et. al., 2001), and JERS data (Eriksson, L.E. et al., 2003) ;
• How PALSAR data were affected by precipitation and temperature?
Introduction
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
The multi-temporal backscattering data (HV). Red: cycle 14, Green: Cycle 19, Blue Cycle 20;
The true color IKNOS image of study site (06/24/2002 )
missed
Test site and data
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
2007/07/10 2007/08/25 2007/10/10 2008/01/10
2008/02/25 2008/04/11 2008/05/27 2008/07/12
Backscattering over a year (HH)
There was no obvious change on spatial pattern
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
Precipitation: 2007/07/09: No record2007/07/10: No record2007/08/25: 4:00 (0.25 mm)
21:00 (1.52 mm) 23:00 (0.25 mm)No Precipitation on other dates of data acquisition.
Backscattering over a year Rain
Leaves fall
Frozen and snow
Frozen thawing and snow melting
sprout of vegetation
(HH)
2008/02/25 2008/04/11 2008/05/27 2008/07/12
2007/08/25 2007/10/10 2008/01/10IKNOS
Baseline length
Rows:horizontal baseline, Columns: vertical baseline
Coherence over a year
2007/07/10 vs. others
There were totally 28 interferometric pairs formed by the 8 scenes of PALSAR data.
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
2007/07/10 vs. others
Snow and frozen
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
2008/01/10-2008/02/25 2008/02/25-2008/04/11 2008/04/11-2008/05/27 2008/05/27-2008/07/12
2007/07/10-2007/08/25 2007/08/25-2007/10/10 2007/10/10-2008/01/10IKNOS
Successive interferometric pairs
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
•The interferometric pairs from summer was the best;
•that composed by summer and autumn or by spring and summer was the middle;
•that composed by winter data was the worst;
Nearly noise
Baseline 3992.907
m
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
(a) (b) (c) (d)
(a) H75 from LVIS Ground Elevation (lge) acquired on 2009; (b) SRTM minus DEM (2007/07/10~ 2007/08/25) (HV); (c) Coherence of 2007/07/10~2007/08/25 (HH); (d) Coherence of 2008/04/11~2008/05/27(HH);
Spatial pattern of coherence and SRTM minus PALSAR-DEM.
The spatial pattern of Figure a and b was consistent.
Figure d was obviously opposite to that of Figure 8-c. This may be attributed to the melt of snow which leads to the high soil moisture. The double bounce between canopy and ground at high biomass area was the dominant and stable scattering component.
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
Conclusion In terms of backscattering, Summer data was stable. Leaves falling,
frozen and Snow accumulation decrease the autumn and winter data. Thawing, melting of snow and vegetation sprout increase the spring data.
Interferometric pair from summer data has the best coherence; Snow and frozen hinder the interferometric process of winter data. Summer data is the best to be used to map biomass
The difference of SRTM and DEM from PALSAR InSAR data can provide forest height information.
Coherence from spring data was positively correlated with forest coverage. Why and How ?
Information lies in variations! How to use the data in other seasons?
IGARSS 2011, July 24-29, 2011, Vancouver, Canada
Thank you for your attention
And
Have a nice time in Vancouver!
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