Applications in Land-surface properties

Transcrição

1 Applications in Land-surface MONITORING WEATHER CLIMATE SEISMIC ACTIVITY properties Isabel Monteiro, IM workshop on EUMETCast data and products, XV Simpósio Brasileiro de Sensoriamento Remoto 5 May 2011 TO A SUSTAINABLE DEVELOPMENT AND A SAFER WORLD

2 Outline LSA SAF Definition, objectives and requirements SEVIRI/MSG and AVHRR/EPS products Land applications - Energy balance - Vegetation biophysics and ecology - Forest fires Pratical issues

3 SAFs SAFs: Development & Processing Centres within the EUMETSAT Applications Ground Segment: Meteorological and Bio-geophysical products Software Packages Using MSG and EPS data. SAF Network

4 LSA SAF LSA SAF The EUMETSAT Satellite Applications Facility on Land Surface Analysis (LSA SAF) AIM Develop techniques that allow an effective use of MSG and EPS data related to: LAND LAND-ATMOSPHERE Interactions BIOSPHERIC Applications REAL TIME Operations (24/365) Products available ~ 1 h after sensing time NRT dissemination by Eumetcast Offline dissemination by ftp User support ANNUALLY REVIEWED Technical and scientific revision Compliance with user requirements

5 Energy Balance and Surface Radiation LST Albedo DSSF DSLF LSASAF Products Vegetation Biophysics and Ecology FVC LAI FAPAR ET *NDVI *Reference ET Forest Fires Fire Detection Fire risk (Euro) Fire Radiative Power * Burnt Areas Physical assessment of land-surface processes Ecossytem functioning & characterization; vegetation state and seasonal productivity patterns Improved carbon budget; deforestation; sustainable development

6 Land Surface Temperature Algorithm Generalised Split-Window Channel 9 (10.8µm) and Channel 10 (12.0µm) T + T 2 T LST = K1 + K3 + T K 4 Surface temperature is linear dependent of brightness temperatures of atmosphere window channels The difference between the two channels is propotional to the atmosphere TCWV K 1, K 3, K 4 depend: implicitly explicitly Water vapour content Satellite viewing angle Surface emissivity Dependent of the atmosphere optical thickness

7 Downwelling Surface Short-wave Flux à frente do nosso tempo LSA SAF DSSF from MSG/SEVIRI From the short wave radiation that reaches the satellite DSSF is the fraction that goes downward to the surface Reflected by the atmosphere and clouds upwards Reflected by clouds and atmosphere downwards Reflected by the surface F Top - F Top = (1- A)F Sun + F A Given by the solar constant and solar zenith angle Measured by the satellite DSSF albedo The effect of the atmosphere

8 Energy Balance products applications à frente do nosso tempo Land-atmosphere interaction Extreme events monitoring Crops Forecast

9 Land atmosphere interaction à frente do nosso tempo ALMIP Intercomparison, intermodel variability Products for atmospheric model studies & water budget Large scale evaluation Aaron Boone- LAND-SAF application within ALMIP Phase 2 LSA SAF 4th User Workshop Toulouse, France November, 2010

10 Energy Balance products applications à frente do nosso tempo Land-atmosphere interaction Extreme events monitoring Crops Forecast

11 Extreme events monitoring à frente do nosso tempo LST July 2007 Heat wave over southeastern Europe July 2007

12 Energy Balance products applications à frente do nosso tempo Land-atmosphere interaction Extreme events monitoring Crops Forecast

13 Crops Forecast MARS (Monitoring Agriculture with Remote Sensing) project runs since 1993 at JRC it s an operational activity on the analysis of crop growth condition assessment and crop yield forecasts Level I weather station data complemented by remote sensing parameters Level II - calibration or update of state variables of crop growth simulation Level III - crop yield/production estimation and forecast by means of scenario and regression analysis LSA SAF products: - DSSF - LST B. BaruthThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B8. Beijing 2008

14 Energy Balance and Surface Radiation LST Albedo DSSF DSLF LSASAF Products Vegetation Biophysics and Ecology FVC LAI FAPAR ET *NDVI *Reference ET Forest Fires Fire Detection Fire risk (Euro) Fire Radiative Power * Brunt Areas Physical assessment of land-surface processes Ecossytem functioning & characterization; vegetation state and seasonal productivity patterns Improved carbon budget; deforestation; sustainable development

15 FRP algorithm FRP computation is based on the MIR method. L MIR, fire L MIR, No fire FRP Atmospheric window Max. emission from fires MSG-1 (SEVIRI), 2003/04/24 12:00 UTC MIR Channel (3.9 µm) (From MSG CHANNELS Interpretation Guide)

16 Forest fire products applications à frente do nosso tempo Fire detection and monitoring Assessment of fire activity Air quality forecasting Estimation of fire carbon emissions Carbon cycle assessment and modelling Monitoring of gas flares

17 Fire detection and monitoring à frente do nosso tempo Temporal evolution of (41.34N,8.55W) 16 August 2010 (12:00 19:00 UTC) At the 13:30 UTC slot, ~70MW of measured radiant energy output from the fire! No FRP up to 13:30

18 Forest fire products applications Fire detection and monitoring Assessment of fire activity Air quality forecasting Estimation of fire carbon emissions Carbon cycle assessment and modelling Monitoring of gas flares

19 Assessment of Fire activity à frente do nosso tempo Fire diurnal cycle in America Courtesy of J. W. Kaiser (LandSAF User workshop 15 Nov 2010)

20 Forest fire products applications Fire detection and monitoring Assessment of fire activity Air quality forecasting FRP operational used by ECMWF at the aim of the GEMS/MACC (EU) project Estimation of fire carbon emissions Smoke plumes modelling from fires over the Mediterranean region Carbon cycle assessment and modelling. Monitoring of gas flares

21 Air Quality Forecasting GEMS: Aerosol emission simulation based on FRP F R P A E R O S O L Courtesy: Instituto de Meteorologia, J. kaiser I. P. Rua C Aeroporto de Lisboa Lisboa Portugal Tel.: (351) Fax: (351) informacoes@meteo.pt URL:

22 Air quality forecasting GEMS: Aerosol emission simulation based on FRP Sunday 26 August UTC ECMWF Forecast t+10 VT: Sunday 26 August UTC Surface: **Aerosol type 10 sink/loss accumulated Sunday 26 August UTC ECMWF Forecast t+10 VT: Sunday 26 August UTC Model Level 56 **Experimental product MODIS Overpass on 26 August, 0935 UTC Courtesy: J. kaiser AUGUST UTC 0 0.1

23 Forest fire products applications Fire detection and monitoring Assessment of fire activity Air quality forecasting Estimation of fire carbon emissions Carbon cycle assessment and modelling Monitoring of gas flares

24 Estimation of Carbon Fire emissions FRP is related to the rate at which the fuel biomass is being consumed (Wooster et al., 2005): Rate of Biomass x FRP Combustion [Kg s -1 ] [MW] t M [kg] x Time Integrated FRP [MJ] Total Fuel Biomass Combusted Emission of Trace = M [kg] x Species Emissions Gas Species [g] Factor (EF, g/kg) (e.g. CO2, CO, CH4)

25 Estimation of Carbon Fire emissions à frente do nosso tempo Wild Fire Carbon emissions over Portugal The amount of Carbon released by wild fires into the atmosphere over Portugal is being routinely computed at IM: 2008: atypical year (very low numbers of fire events and total burnt area over Portugal) 2009 Courtesy: L. Pessanha

26 Forest fire products applications Fire detection and monitoring; Assessment of fire activity; Air quality forecasting; Estimation of fire carbon emissions; Carbon cycle assessment and modelling Monitoring of gas flares

27 Carbon cycle assessment and modeling à frente do nosso tempo GLOBAL TOTAL CO FORECAST 29/09/ UTC

28 Forest fire products applications Fire detection and monitoring; Assessment of fire activity; Air quality forecasting; Estimation of fire carbon emissions; Carbon cycle assessment and modelling Monitoring of gas flares

29 Monitoring of gas flares Example of FRP product application: Monitoring of gas flares with MSG active fire data LSA SAF 4 th User Workshop Toulouse, France November, 2010 Keith Peterson, Peter Navratil 2010/09/30 08:00 UTC

30 Monitoring of gas flares à frente do nosso tempo What is a gas flare? Gas flares, or flare stacks, are associated with oil wells, gas wells, rigs, refineries, natural gas plants and landfills. Commonly used practice for the disposal of waste gas in oil rich regions lacking distributive infrastructure. In 2008 estimated emissions from gas flaring amounted to 9% of the total CO2 emissions of the European Union (EU-15). An estimated billion m 3 of gas has been flared annually over the past 14 years (GGFR, Worldbank). To date, reliable and accurate data on gas flaring is hard to find and is mostly based on self-reporting, independent assessments of flared gas volumes are not being carried out. The LSA SAF FRP Product suitability for gas flare monitoring in comparison to other satellite fire products (from MODIS & ESA World Fire Atlas) was assessed, over an extended period of time ( ).

31 Monitoring of gas flares à frente do nosso tempo Persian Gulf Includes the oil rich Al Basrah region in southern Iraq and the productive oil fields of Kuwait 73 Flare Sites: 68 onshore 5 offshore

32 Energy Balance and Surface Radiation LST Albedo DSSF DSLF LSASAF Products Vegetation Biophysics and Ecology FVC LAI FAPAR ET *NDVI *Reference ET Forest Fires Fire Detection Fire risk (Euro) Fire Radiative Power * Brunt Areas Physical assessment of land-surface processes Ecossytem functioning & characterization; vegetation state and seasonal productivity patterns Improved carbon budget anthropogenic effetcs. Deforestation. Sustainable development

33 Vegetation Parameters Parameters that represent the structural characteristics of vegetated surfaces: Fraction of Vegetation Cover [0 1]: fraction of the surface covered by vegetation (FVC) Leaf Area Index : total area occupied by the leaves per unit area [m 2 /m 2 ] (LAI) Parameter directly related with the state (and health) of vegetation: Fraction of Absorbed Photosynthetically Active Radiation: part of radiation used for photosynthesis ( µm) absorbed by the green parts of the canopy (FAPAR)

34 Vegetation Parameters Estimations FVC, LAI, FAPAR estimations from Remote Sensing are based in the analysis of vegetation signature in the 0.6 µm, 0.8 µm & 1.6 µm channels. Starting with the characterization of reflectance in different channels for different types of vegetation (V1,V2, V3,...) and soil (S1, S2, S3). Channel 2 Channel 1

35 LSA SAF FVC Algorithm FVC ESTIMATION For any given observation ( ) the algorithm assumes this value can be modelled by the pairs (vegetation, soilsubclass) Channel 2 observation the pure types, Vi and Si for each pixel are obtained by the prevalent Land-cover the distances between ( ) and Vi, Si give the fractions of each vegetation and soil type qithinh the scene Channel 1 FVC = N i= 1 fvc Vi Number of vegetation subclasses present in the pixel Fraction of vegetation cover for vegetation type Vi

36 LSA SAF LAI Algorithm LAI ESTIMATION - semi-empirical method proposed by Roujean and Lacaze (2002), in which LAI is related to FVC trough the following expression: LAI = 1 b.g( θs = ln(a. 0). Ω 0 FVC) a Where b and G are constants and a 0 and Ω depend on the LandCover Map.

37 LSA SAF fapar Algorithm fapar ESTIMATION the LSA SAF fapar is estimated from a NDVI-like vegetation index: RDVI = ρ channel2 ρ channel1 ρ ρ channel1 channel2 Since the view-illumination geometry may have a large impact on reflectance observations, RDVI is computed from surface reflectances corrected to an optimal geometry. fapar = 1.81RDVI opt

38 Vegetation Products Fractional Vegetation Cover - FVC Leaf Area Index- LAI Fraction of Absorbed Photosynthetically Active Radiation - fapar TEMPORAL RESOLUTION: Daily SPATIAL RESOLUTION: native SEVIRI (3 x 3 FREELY AVAILABLE (NRT) Via FTP: SINCE JAN 2006 Via EUMETCAST: APRIL 2009

39 Vegetation Products Applications à frente do nosso tempo Amplitude of the growing season Timing of phenological stages Length of the growing season Extraction of phenological parameters Fire effects on vegetation Drought effects on vegetation

40 Vegetation Products Applications à frente do nosso tempo Amplitude of the growing season Timing of phenological stages Length of the growing season Extraction of phenological parameters

41 Timing of phenological stages The date of the SOS (start of the growing season) is a critical parameter for food security monitoring: Subsahelian region FVC FVC product from VEGETATION (VGT JRC) FVC product from SEVIRI (LSA SAF) LSA SAF team (F. Camacho, J. Garcia-Haro)

42 Vegetation Products Applications à frente do nosso tempo Amplitude of the growing season Timing of phenological stages Length of the growing season Extraction of phenological parameters Dry matter productivity Fire effects on vegetation Drought effects on vegetation

43 Dry Matter Productivity Dry Matter Productivity represents the increase in dry matter biomass. It is a function of (Monteith, 1972): Incoming solar radiation ( µm); Surface Temperature; fapar The Joint Research Center (JRC) is computing this parameter for crop monitoring using meteorological information and the fapar product from the LSA SAF (LSA SAF 3rd User Training Workshop).

44 Dry Matter Productivity 2008, February, Dekad 3 over Africa SPOT MSG Very good spatial consistency; A North-South transect through Africa (from Lybia to Cape Town) also highlights the good correspondence between SPOT and MSG:

45 Vegetation Products Applications Amplitude of the growing season Timing of phenological stages Length of the growing season Extraction of phenological parameters Fire effects on vegetation Drought effects on vegetation

46 Fire effects on vegetation Monitoring of Vegetation: Effects of the Fire Activity FVC 1 st May 2007 FVC before fire season of 2007, that mainly affected Italy and Greece There is a drastic reduction of the vegetation cover to which fires have most likely contributed, besides other reasons as harvested crops or drying out of leaves. FVC 31 st Aug 2007

47 Vegetation Products Applications à frente do nosso tempo Amplitude of the growing season Timing of phenological stages Length of the growing season Extraction of phenological parameters Fire effects on vegetation Drought effects on vegetation

48 Drought Effects on vegetation à frente do nosso tempo

49 Drought Effects on vegetation à frente do nosso tempo

50 Vegetation Products Applications More Applications at:

51 Data provided by the Land-SAF Files Format: HDF5 HDF5 file attributes Version, Dimensions, Projection: GEOS (0º) Pixel size=3.1 km at equator Aquisition Time Region Name...

52 FILES FORMAT Software Purpose Free Available from HDFVIEW view the file hierarchy in a tree structure display data ILWIS Geonecast toolbox display data GIS operations Python (programming language) display data GIS operations Matlab (programming language) display data GIS operations cts/

53 Questions/Comments?