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A synergetic use of observations from MODIS, SEVIRI MSG, ASAR and AMSR-E to infer a daily soil moisture index C. Notarnicola 1 , F. Di Giuseppe 2 , K. Lewinska 1 , L. Pasolli 1,3 , M. Temimi 4 , B. Ventura 1 ,  M. Zebisch 1 1   EURAC-Institute for Applied Remote Sensing, Viale Druso 1, Bolzano, Italy. 2 ARPA-ServizioIdroMeteoClima, Viale Silvani 6, Bologna, Italy   3 Dep. of Information Engineering and Computer Science, University of Trento,  Via Sommarive, 14, Trento, Italy.  4 NOAA-CREST/NOAA-CREST/The City University of New York, The City College, 140th St @ Convent Ave.  Steinman Hall (T-109), New York, NY 10031. IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2011  Vancouver, Canada  -  July 24-29, 2011
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
ATI from MODIS images (or equivalent sensors) ATI from MSG images (or equivalent sensors) Soil moisture estimates from AMSR-E sensors Soil moisture estimates from SAR sensors Check spatial distribution and calibration steps Check temporal trends and  regularization Downscaling and cloud cover reduction Daily Soil Moisture Index (3-4 classes)
[object Object],[object Object],[object Object],[object Object],[object Object],Test sites Dates  Product  Polarization  Swath/  MODIS acquisistion SCRIVIA   Apr .  4, 2008 Oct 31, 2008 IMS  IMS  VV VV 2/23 o 2/23 ° April 4. 2008  cloudy MATERA July 13, 2008 Oct.10, 2008 May 7 2008 April 11, 2009 APS APS IMS APS HH/HV HH/HV VV HH/HV 2/23 o 2/23 ° 2/23 ° 2/23 o July 13, 2008 Oct.10, 2008 May 7,  2008 April11, 2009 CORDEVOLE June 14, 2004  July 19, 2004 Sept. 27, 2004 IMS  IMS  IMS VV VV VV 2/23 o 2/23 o 2/23 o cloudy July 19, 2004 Sept.27, 2004 ST-IT , test site located in Italy : Emilia Romagna region-red dot (ARPA Emilia Romagna) ST-FR , test site located in France (belonging to SMOSMANIA network), near the Pyrenees-yellow dot (after Google Earth©). ST-IT , test site located in Italy : South Tyrol-green dot (EURAC-Institute for Alpine Environment)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],12:00 Temperature 00:00 24:00 Time bare soil water vegetation MYD L1B Day acq. MYD L1B Night acq. Georeferencing/ Radiometric cal. BT 11  m day BT 11  m night MYD 09 Albedo calculation Re-projection ATI Cloud screening (MYD035)
If the limit of   T =10K   is considered in order to have reliable ATI estimates [Cai et al., 2007],  the error on ATI is around 0.002  which corresponds to 5% of the lowest values detected in this analysis.
ATI-Ground measurements ATI=1.8*10 -3* SMC+0.0154 R 2 =0.76 (SMC expressed in %) ATI-SMC_SAR ATI=1.3*10 -3* SMC+0.019 R 2 =0.78 (SMC expressed in %) ATI SAR Three classes (Emilia Romagna Test site): ATI < 0.04, SMC-SAR < 10% 0.04 < ATI < 0.05, 10% < SMC-SAR < 15% ATI > 0.05, SMC-SAR > 15%, OA=72% Urban Forest Water  bodies ATI (K -1 )
Even under similar soil moisture conditions and acquisition time, the  ATI values show a high variability .  It is therefore necessary to introduce a  filtering technique  to reduce the noise in the observed data.  The use of microwave based time series of soil moisture to refine the ATI based product should perform better than any other stand-alone signal analysis technique like moving average as the  microwave estimates are intrinsically consistent with ATI estimates.  The main assumption of this study is the agreement between  soil moisture estimates from microwave and ATI . This expected agreement fosters using the microwave time series to filer and refine the ATI product. A temporal moving window has been considered by using the following expression: ,[object Object],[object Object],[object Object]
Analysis of temporal trends: Emilia Romagna Comparison of the temporal trend among SMC (cm3/cm3), ATI originally calculated and ATI filtered.  H stands for High NDVI values (> 0.4) and L stand for Low NDVI values (< 0.4). Comparison between ATI and measured soil moisture values (SMC) over 1 year period for Emilia Romagna test site. The values represent the determination coefficients between ATI values and SMC in the different cases considered . No filter Simple filter  Filter using AMSRE data NDVI < 0.4 0.58 0.59 0.72 NDVI > 0.4 0.45 0.45 0.56
SMC classes from ATI ,[object Object],[object Object],[object Object],[object Object],[object Object],The overall accuracy with four classes is around 51%.  If we exclude the values of ATI within the confidence interval corresponding to the error measurements of SMC values that  can be misclassified,  the accuracy raises to 81%. In this case, the overall accuracy is around  65% , and rises to  88%  considering the misclassified values due to their position very close to the class boundaries.  4 - classes 3 - classes ATI/SMC 1 (< 0.05) 2 (0.05-0.07) 3 (0.07-0.085) 4 (>0.085) 1 (<0.17) 0.57 0.43 - - 2 (0.17-0.25) 0.24 0.62 0.09 0.05 3 (0.25-0.3) - 0.22 0.33 0.44 4 ( >0.3) - 0.25 0.25 0.50 SMC/ ATI 2 (<0.055) 3 (0.055-0.085) 4 (>0.085) 2 (<0.20) 0.76 0.24 - 3 (0.20-0.30) 0.12 0.60 0.28 4 ( >0.30) - 0.50 0.50
Analysis of temporal trends: France Comparison of the temporal trend among SMC (cm3/cm3), ATI originally calculated and ATI filtered. H stands for High NDVI values (> 0.4) and L stand for Low NDVI values (< 0.4). Temporal comparison between ATI and measured soil moisture values (SMC) over 1 year period for France test site. The  values represent the determination coefficients between ATI values and SMC in the different cases considered. No filter Simple filter  Filter using AMSRE data NDVI < 0.4 0.61 0.68 0.70 NDVI > 0.4 0.23 0.24 0.43
SMC classes from ATI The overall accuracy with three classes is around 58%.  If we exclude the values of ATI within the confidence interval corresponding to the error measurements  of SMC values that can be misclassified,  the accuracy raises to 73%. 3 - classes The ranges adopted are slightly different from the previous test site, because the SMC values were in  general higher while the corresponding ATI did not change due to the presence of vegetation detected  with high NDVI values. In fact in the confusion matrix most of the values of SMC higher than 0.35  cm 3 /cm 3  are in class 3 instead of 4. This happens because all the highest SMC values were in the period  with the highest values of NDVI. ATI/SMC 2 (<0.06) 3 (0.06-0.085) 4 (>0.085) 2 (<0.25) 0.78 0.22 - 3 (0.25-0.35) 0.37 0.53 0.10 4 ( >0.35) 0.17 0.75 0.08
 
ATI (K -1 ) ,[object Object],[object Object],[object Object],[object Object],[object Object],Matchertal watershed – One of the driest valley in South Tyrol
Time of acquisitions
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],NDVI and Land cover classes are significant in all the analyzed days.  This impact (value of F-statistic) depends on the day, so probably on NDVI value – phenology; BUT weather conditions (cloud cover, fog etc) also might play here important role! Tests of Between-Subjects Effects Dependent Variable:145 Source Type III Sum of Squares df Mean Square F Sig. Noncent. Parameter Observed Power b Corrected Model .274 a 81 .003 12.780 .000 1035.194 1.000 Intercept .509 1 .509 1924.258 .000 1924.258 1.000 LC .023 10 .002 8.819 .000 88.192 1.000 NDVI_145 .014 8 .002 6.651 .000 53.206 1.000 LC * NDVI_145 .024 63 .000 1.424 .016 89.743 1.000 Error 1.920 7256 .000 Total 26.702 7338 Corrected Total 2.194 7337 a. R Squared = .125 (Adjusted R Squared = .115) b. Computed using alpha = .05 Tests of Between-Subjects Effects Dependent Variable:156 Source Type III Sum of Squares df Mean Square F Sig. Noncent. Parameter Observed Power b Corrected Model .234 a 51 .005 24.856 .000 1267.661 1.000 Intercept 1.284 1 1.284 6955.441 .000 6955.441 1.000 El .011 5 .002 11.751 .000 58.754 1.000 NDVI_156 .043 8 .005 29.079 .000 232.630 1.000 El * NDVI_156 .042 38 .001 6.035 .000 229.344 1.000 Error 1.353 7327 .000 Total 20.566 7379 Corrected Total 1.587 7378
 
 
Cross-comparison with SEVIRI- MSG data A cross-comparison with METEOSAT MSG data is under  evaluation. Some MSG images contemporary to MODIS acquisitions have been processed  and analyzed over the Emilia Romagna test sites. One of the major problems is the use of a correct cloud mask in order to not introduce  not corrected ranges of  ATI values.
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for the attention! Comments/questions?

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Notarnicola_TU3_TO3.3.ppt

  • 1. A synergetic use of observations from MODIS, SEVIRI MSG, ASAR and AMSR-E to infer a daily soil moisture index C. Notarnicola 1 , F. Di Giuseppe 2 , K. Lewinska 1 , L. Pasolli 1,3 , M. Temimi 4 , B. Ventura 1 , M. Zebisch 1 1 EURAC-Institute for Applied Remote Sensing, Viale Druso 1, Bolzano, Italy. 2 ARPA-ServizioIdroMeteoClima, Viale Silvani 6, Bologna, Italy 3 Dep. of Information Engineering and Computer Science, University of Trento, Via Sommarive, 14, Trento, Italy. 4 NOAA-CREST/NOAA-CREST/The City University of New York, The City College, 140th St @ Convent Ave. Steinman Hall (T-109), New York, NY 10031. IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2011 Vancouver, Canada - July 24-29, 2011
  • 2.
  • 3.
  • 4. ATI from MODIS images (or equivalent sensors) ATI from MSG images (or equivalent sensors) Soil moisture estimates from AMSR-E sensors Soil moisture estimates from SAR sensors Check spatial distribution and calibration steps Check temporal trends and regularization Downscaling and cloud cover reduction Daily Soil Moisture Index (3-4 classes)
  • 5.
  • 6.
  • 7. If the limit of  T =10K is considered in order to have reliable ATI estimates [Cai et al., 2007], the error on ATI is around 0.002 which corresponds to 5% of the lowest values detected in this analysis.
  • 8. ATI-Ground measurements ATI=1.8*10 -3* SMC+0.0154 R 2 =0.76 (SMC expressed in %) ATI-SMC_SAR ATI=1.3*10 -3* SMC+0.019 R 2 =0.78 (SMC expressed in %) ATI SAR Three classes (Emilia Romagna Test site): ATI < 0.04, SMC-SAR < 10% 0.04 < ATI < 0.05, 10% < SMC-SAR < 15% ATI > 0.05, SMC-SAR > 15%, OA=72% Urban Forest Water bodies ATI (K -1 )
  • 9.
  • 10. Analysis of temporal trends: Emilia Romagna Comparison of the temporal trend among SMC (cm3/cm3), ATI originally calculated and ATI filtered. H stands for High NDVI values (> 0.4) and L stand for Low NDVI values (< 0.4). Comparison between ATI and measured soil moisture values (SMC) over 1 year period for Emilia Romagna test site. The values represent the determination coefficients between ATI values and SMC in the different cases considered . No filter Simple filter Filter using AMSRE data NDVI < 0.4 0.58 0.59 0.72 NDVI > 0.4 0.45 0.45 0.56
  • 11.
  • 12. Analysis of temporal trends: France Comparison of the temporal trend among SMC (cm3/cm3), ATI originally calculated and ATI filtered. H stands for High NDVI values (> 0.4) and L stand for Low NDVI values (< 0.4). Temporal comparison between ATI and measured soil moisture values (SMC) over 1 year period for France test site. The values represent the determination coefficients between ATI values and SMC in the different cases considered. No filter Simple filter Filter using AMSRE data NDVI < 0.4 0.61 0.68 0.70 NDVI > 0.4 0.23 0.24 0.43
  • 13. SMC classes from ATI The overall accuracy with three classes is around 58%. If we exclude the values of ATI within the confidence interval corresponding to the error measurements of SMC values that can be misclassified, the accuracy raises to 73%. 3 - classes The ranges adopted are slightly different from the previous test site, because the SMC values were in general higher while the corresponding ATI did not change due to the presence of vegetation detected with high NDVI values. In fact in the confusion matrix most of the values of SMC higher than 0.35 cm 3 /cm 3 are in class 3 instead of 4. This happens because all the highest SMC values were in the period with the highest values of NDVI. ATI/SMC 2 (<0.06) 3 (0.06-0.085) 4 (>0.085) 2 (<0.25) 0.78 0.22 - 3 (0.25-0.35) 0.37 0.53 0.10 4 ( >0.35) 0.17 0.75 0.08
  • 14.  
  • 15.
  • 17.
  • 18.  
  • 19.  
  • 20. Cross-comparison with SEVIRI- MSG data A cross-comparison with METEOSAT MSG data is under evaluation. Some MSG images contemporary to MODIS acquisitions have been processed and analyzed over the Emilia Romagna test sites. One of the major problems is the use of a correct cloud mask in order to not introduce not corrected ranges of ATI values.
  • 21.
  • 22. Thank you for the attention! Comments/questions?