1. J. S. Parihar Agricultural Resources Group Space Applications Centre (ISRO) Ahmedabad, India E-mail: jsparihar@sac.isro.gov.in Land applications from Megha Tropiques data 3 rd ISRO-CNES Workshop on Megha-Tropiques, Ahmedabad, October 17-20, 2005

2. Water and energy fluxes of land surface coupled with atmospheric parameters have direct impact on Earth’s productivity and food security.Water and energy fluxes of land surface coupled with atmospheric parameters have direct impact on Earth’s productivity and food security. Understanding and modeling of land surface processes help in improved use of natural resources, mitigation of environmental hazards, and knowledge of climate change scenarios.Understanding and modeling of land surface processes help in improved use of natural resources, mitigation of environmental hazards, and knowledge of climate change scenarios. Global observation from various space missions operating in different EM regions are important source of data to retrieve many critical land surface parameters.Global observation from various space missions operating in different EM regions are important source of data to retrieve many critical land surface parameters. Megha Tropiques (MT) is unique satellite, which will have sensors operating in optical, thermal and microwave regions for characterizing land-ocean- atmospheric parameters and earth radiation budget.Megha Tropiques (MT) is unique satellite, which will have sensors operating in optical, thermal and microwave regions for characterizing land-ocean- atmospheric parameters and earth radiation budget.Background

3. Soil Vegetation Atmosphere Interaction Radiation components: Net radiation R n (short, long wave) & Albedo  ; Temperature, SM are very important Parameters Needed in Process Modeling (Retrievable from satellite) Soil Moisture Radiation Albedo Rainfall Surface Temperature SM i = SM i-1 + P - RO – AET- DP

4. MT SENSORS AND THEIR UNIQUENESS ScaRaB MADRAS ScaRaBSensorParameterMADRAS Soil moisture Vegetation phenology Temperature ScaRaB Albedo (planetary) Net radiation Temperature

5. Experience with (a) Passive Microwave Data: Soil moisture, vegetation phenology, temperature (b) Energy Radiation Budget Experiment Data: Albedo, fluxes- Net Radiation Experience with (a) Passive Microwave Data: Soil moisture, vegetation phenology, temperature (b) Energy Radiation Budget Experiment Data: Albedo, fluxes- Net Radiation

6. NDVI MPDI 19 GHz MPDI 37 GHz MPDI 85 GHz Microwave Polarization Difference Index (MPDI) It is a difference of vertical and horizontal polarized brightness temperature for a specified microwave frequency and expressed as MPDI = (Tb v – Tb h )/ (Tb v + Tb h ) Where v & h stands for vertical and horizontal component of brightness temperature Tb. Since vegetation depolarizes the radiation emitted from the soil, the increase in the vegetation fraction decreases the MPDI June 1-10, 1999

7. Multi frequency (19, 37 and 85 GHz) observation of MPDI of wheat crop MPDI for vegetation growth assessment NDVI MPDI 37 GHz (1999) Inverse relationship between NDVI and MPDI observed for rice crop in Punjab for year 1999. Rice crop, Punjab Wheat crop

8. Amritsar Jodhpur (Basist, 1998) MULTI-FREQUENCY APPROACH

9. SURFACE WETNESS AS OBSERVED FROM SSM/I DATA 2001 2002 May 14-20 May 21-27 Surface wetness index Source: NCDC-NOAA

10. May 28-June 03 June 04-June 10 2001 2002 Surface wetness index

11. June 11-June 17 June 18-June 24 2001 2002 Surface wetness index

12. June 25-July 01 July 02 – July 08 2001 2002 Surface wetness index

13. July 09 – July 15 July 16 – July 22 2001 2002 Surface wetness index

14. 0.010.48 Water Body Surface flooded with water Soil Moisture WEEKLY SOIL MOISTURE IMAGES (2000) 12345678 9 10111213141516 17 18192021222324 25 26272829303132 33 34353637383940 41 42434445464748 49 505152

15. Interannual variation in agricultural practices

16. RETRIEVAL OF LAND SURFACE TEMPERATURE (LST) LST=C0 + C1*T19V + C2*T19H + C3*T22V + C4*T37H 9 10 Feb. 7, 2000 Land Cover LST (McFarland, 1991) 275 303

17. Some examples of Albedo and other Radiation components over India using ERBE products

18. 44220 Short wave radiation W/m 2 132301 Long wave radiation W/m 2 -8173 Net radiation W/m 2 060 Albedo percent Examples of Radiation components over India using ERBE data Jan 1989 Earth Radiation Budget Experiment (ERBE) (Source: Langley Research Centre)

19. Albedo using ERBE products over India

20. Monthly average Albedo Profile over different targets over India

21. Net Radiation using ERBE data

22. Jan 89 May 89 The zonal distribution of net radiation in winter and summer seasons of 1989 over India using ERBE data A positive value of net radiation indicates a warming of the Earth while a negative value indicates cooling

23. Approaches and some issues Derivation & comparison of parameters from other satellites Approach for Derivation of Broadband Albedo from ScaRaB sensor data

24. Issues: Spectral characteristics and corrections Spectral normalization and comparison of Narrow/Broad bands with other sensors BROADBAND SW ALBEDO [%] VISIBLE ALBEDO [%]

25. Issues: Angular Parameters View zenith angle Sun zenith angleSun azimuth angle Schematic showing viewing geometry Example: Viewing geometry parameters for INSAT 0 53 00 58 0 0 178 0 10:30 IST

26. Angular normalization for vegetation class Anisotropic factor for vegetation Canopy Reflectance RT model Atmospheric RT model I/Ps: Biophysical, Viewing geometry input At-sensor Bidirectional Reflectance I/Ps: Atmo. inputs Modeling Angular effects for vegetation  s =53 0

27. Feasible study and use of MT data Feasible study and use of MT data Development of model to describe the relationship between passive microwave multi frequency/polarization brightness temperature and land characteristics for different MADRAS channels.Development of model to describe the relationship between passive microwave multi frequency/polarization brightness temperature and land characteristics for different MADRAS channels. To understand the spectral (narrow to broadband conversion) and angular characteristics of veg. targets for ScaRaB Sensor.To understand the spectral (narrow to broadband conversion) and angular characteristics of veg. targets for ScaRaB Sensor. Retrieval of parameters viz. soil moisture, land surface temperature, albedo etc from MT sensors data and comparison with other satellite data products.Retrieval of parameters viz. soil moisture, land surface temperature, albedo etc from MT sensors data and comparison with other satellite data products. Assessment and Comparisons of MADRAS and ScaRaB Data (Radiances, Brightness Temperature) using other satellite data and products (INSAT, EOS-AQUA/TERRA etc ) and ground measurements.Assessment and Comparisons of MADRAS and ScaRaB Data (Radiances, Brightness Temperature) using other satellite data and products (INSAT, EOS-AQUA/TERRA etc ) and ground measurements. Hydrological and vegetation dynamics modeling in different agro- ecosystem using estimated parameters from MT data.Hydrological and vegetation dynamics modeling in different agro- ecosystem using estimated parameters from MT data.

28. Thank You

29. Global Status on Passive Microwave Radiometers for Land Applications SensorSatellite Frequency (Ghz) Spatial Resolution (km) Remark Special Sensor Microwave Imager (SSM/I) Defense Meteorological satellite Program (DMSP) 19.422.237.085.569503715 Vertical and Horizontal Polarizations (except 22.2 only H) Swath = 1200 km Viewing 53.1deg TRMM Microwave Imager (TMI) Tropical Rainfall Measuring Mission(TRMM) 10.719.421.337.085.5381817104 Swath = 790 km Viewing 52.7 deg Coverage : -38 deg to 38 deg Scanning Multi channel Microwave Radiometer (SMMR) Nimbus-76.6310.6918.021.037.0 150 & 25 Vertical and Horizontal Polarizations (except 21.0 only H). Data: 1978-1987 Multi-frequency Scanning Microwave Radiometer (MSMR) IRS-P46.610.651821 40 to 150 Advanced Microwave Sensing Radiometer (AMSR) EOS – AQUA and ADEOS-II 6.92 to 89 Planned Soil Moisture as a Product MEGHA TROPIQUE (MT)Planned 10 to 157 10 Electronically scanned Thinned array radiometer SMOS Synthetic Aperture Radiometer Soil moisture and Ocean Salinity Mission (ESA) Planned 1.450 Vertical and Horizontal Polarizations (Several Angles)

30. Global Status on Earth Radiation Budget Experiment Sensors SensorSatelliteRef. ERBE ERBS, Nimbus, NOAA-9, NOAA-10 Raschke et al., 1973 Jacobowitz et al., 1984 Barkstorm et al., 1986 ScaRaB METEOR, Resurs Kandel et al., 1994 CERES TRMM, EOS- TERRA, AQUA Wielicki et al., 1996 GERBMSG-1 Harries et al., 1999, 2000 ScaRaB Megha Tropiques Proposed sensor