1 / 30

PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS

PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS. by : P. Ferrazzoli Tor Vergata University Roma, Italy ferrazzoli@disp.uniroma2.it. CLASSIFICATION OF REMOTE SENSING INSTRUMENTS Based on physical processes.

anisa
Download Presentation

PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS by : P. Ferrazzoli Tor Vergata University Roma, Italy ferrazzoli@disp.uniroma2.it

  2. CLASSIFICATION OF REMOTE SENSING INSTRUMENTSBased on physical processes

  3. CLASSIFICATION OF REMOTE SENSING INSTRUMENTS: Summary Active Passive Optical/UV Lidar Radiometer Microwave Radar Radiometer

  4. PASSIVE SYSTEMS: the emission process Background: every surface, at T>0 K, emits electromagnetic power

  5. PASSIVE SYSTEMS: the emission process at microwaves Brightness: Black body brightness: Brightness temperature (definition): Microwave emissivity:

  6. PASSIVE SYSTEMS: the emission processReciprocity Pr Pi Pa Reflectivity: R(f, θ,φ)= Pr / Pi (reflectance) Absorbivity: A(f, θ,φ) = Pa / Pi = 1- R(f, θ,φ) (absorbance) Kirchhoff (reciprocity) law: e(f, θ,φ) = A(f, θ,φ)

  7. Horizontal polarization Vertical polarization depends on volumetric soil moisture (SM) is a roughness factor

  8. Real and imaginary parts of soil permittivity as a function of volumetric soil moisture content (SMC) at 1.4 GHz (L band) Measured values (by Ulaby, Moore, Fung, 82) SOILS Important for applications: εr is stongly influenced by moisture.

  9. Increasing moisture, ε increases, Reflectivity increases, Emissivity decreases GENERAL PROPERTIES OF EMISSIONFROM NATURAL MEDIA Emissivity of flat surfaces vs. angle (computations) (by Ulaby, Moore, Fung, 82)

  10. BARE SOILS Constant roughness, Moisture variations moisture Emissivity vs. angle, L band (1.4 GHz) Ground based measurements (by Ulaby, Moore, Fung, 82)

  11. BARE SOILS Constant moisture, Roughness variations Emissivity vs. angle, L band (1.4 GHz) Ground based measurements (by Ulaby, Moore, Fung, 82) roughness

  12. VEGETATION COVERED SOILS e3 e1 e2 e=e1+e2+e3 • e1 = (1-) [1- exp(- σev h sec)] • e2 = (1-) [1- exp(- σev h sec)] exp(- σev h sec) rs • e3  = esexp(- σev h sec) • : vegetation “albedo” τ= σev h (“optical depth”) es :soil emissivity rs : soil reflectivity (rs =1 – es)

  13. RECENT MICROWAVE INSTRUMENTS Spaceborne radiometric systems launch bands (GHz) AMSR-E 2002 6.9, 10.6, 18,21,37, 89 SMOS 2009 1.4

  14. SMOS Launch: 2009 Spatial resolution: 35-50 km (suitable to studies at global scale) Rivisit time: 3 days Goal in soil moisture retrieval accuracy: 4%

  15. To improve spatial resolution: Interpherometric technique: 69 small antennas located on 3 long arms “The BIG Y” For each pixel: Simultaneous measurements at V and H polarization, 20°< θ<60°

  16. Estimating soil moisture in the root zone is important: • short- and medium-term meteorological modelling, • hydrological modelling, • monitoring of plant growth, • forecasting of hazardous events such as floods. By ESA SMOS site http://www.esa.int/esaLP/LPsmos.html

  17. The soil-vegetation-atmosphere transfer (SVAT) schemes used in meteorology and hydrology are designed to describe the basic evaporation processes at the surface, the water partitioning between vegetation transpiration, drainage, surface runoff and soil moisture variations. At present, soil moisture maps are simulated and forecasts are generatedby models Objective of SMOS: maps improvement, maps update By ESA SMOS site http://www.esa.int/esaLP/LPsmos.html

  18. The retrieval process • Initial estimate of SM and Leaf Area Index LAI (ECMWF and ECOCLIMAP data bases) • - Models for τ(LAI) and eS (SM) • For each angle () and polarization: • TB= TS(1-) [1- exp(- τ sec)]  [1+exp(- τ sec) (1-es)] +TS esexp(- τ sec) • Compare initial simulations with measurements • Start an iterative process • Adjust SM in order to obtain the minimum rms difference between simulations and measurements.

  19. Tests: Multitemporal over single sites Global in selected dates

  20. World map of retrieved Optical depth

  21. World map of retrieved Soil moisture

  22. AMSR-E Conical scanning. Local incidence angle: 55°

  23. Application: flood monitoring Test area: Sundarbans delta Polarization Index:

  24. Polarization Index: Increases with soil moisture, decreases with vegetation height Sensitive to flooding Best frequencies: C and X band

  25. PI maps

  26. Multitemporal PI trends in 2005, all bands PI vs. Day of Year Measured water level

  27. Multitemporal PI trends in all years, X band PI vs. Day of Year Measured water level

  28. Correlation PI vs. water level

  29. References • F.T. Ulaby, R.K. Moore, A.K. Fung, “Microwave Remote Sensing. Active and Passive, Vol. II” Addison Wesley, Reading (USA), 1982 • F.T. Ulaby, R.K. Moore, A.K. Fung, “Microwave Remote Sensing. Active and Passive, Vol. III” Artech House, Dedham (USA), 1986 • ESA Living Planet Programme – SMOS http://www.esa.int/esaLP/LPsmos.html

More Related