Upload
baylee-barton
View
219
Download
0
Tags:
Embed Size (px)
Citation preview
EUFAR - European Facility for Airborne Research
www.eufar.net
CNR IMAA airborne facilities
ODS3F – Observation and Detection Systems For Forest Fire MonitoringRome, 15th May 2014
Stefano Pignattiwww.imaa.cnr.it
Instrument Type Instrument nameSerial type Operator Measured
parameter + Range
Incident flow vector probeAIMMS-20-ARI ARI Airspeed; Incidence angle;
Turbulence
RadarRadio-echo-sounder AWI Reflectivity Penetrates ice up to
4000m thick
GPSTrimble-4000SSI AWI Aircraft position, velocity
and attitude
OtherLaCoste-Romberg-Gravimeter
AWI Gravity field
OtherScintrex-Magnetometer AWI Magnetic field: 20000 -
100000nT
Laser AltimeterRiegl-LD90-AWI AWI Aircraft height above
surface3 - 2500m (if reflectivity >
0.8) Laser scanner Riegl-LMS-Q280 AWI surface maps
VIS/NIR spectrometerOceanOptics CNR-IBIMET Radiance
Incident flow vector probeCNR-Mobile-Flux-Platform CNR-IBIMET Airspeed; Incidence angle;
Turbulence
Imaging SpectrometerTASI-600 S/N 5506 CNR-IMAA Radiance Spectra LWIR 8-12micron
CO2 and H20 by IR absorption
Licor7500-CNR CNR-ISAFoM CO2, H2O CO2: 0 - 3000ppm. H2O: 0 - 60ppm.
Incident flow vector probeBAT-ARA CNR-ISAFoM Airspeed; Incidence angle;
Turbulence
Dew/Frost-point hygrometer
Edgetech-Dewtrak200 CNR-ISAFoM Dew Point -40 - 60°C. Operating principle: thermo-electric
BBRLicor-Quantum-PAR CNR-ISAFoM Hemispheric broadband
radiance400 - 700nm
Laser AltimeterRiegl- LD90-CNR CNR-ISAFoM Aircraft height above
surface<500m
BBRCambell-Q7.1 CNR-ISAFoM Hemispheric broadband
radiance0.25 - 60µm
BBREverest-4000.4-ZL CNR-ISAFoM Hemispheric broadband
radianceInfraRed (-40 - 100°C)
Partenavia P68 Observer2
Technical information: - Typ. speed: 52 m/s - Ceyling height: 19200 ft - Typ. operating height: 18000 ft
- Empty weight: 1420 Kg - Max. take-off weight: 2084 Kg - Max payload: 660 Kg
TASI-600 installation
- Total electrical power: 1.925 KW - Electrical power available: 1 KW at 27.5V +/- 0.5V
- Usual range during measurements flight: 1620 Km
- Aircraft can flight in non iceing conditions @ low operat. costs - Avionics is is equipped with Garmin GNS 430W - Take-off runway lenght: 630 m - in ISA – MTOM - 0 Wind - Helicopter-like visibility through the plexiglas cockpit
Research InfrastructuresCNR IMAA’s property in terms of scientific equipment is now estimated at more than 12 million Euros. The main instrumental facilities operating at the IMAA laboratories are: CIAO-CNR-IMAA Atmospheric Observatory which is one of the 12 worldwide sites within the GRUAN network for the study of the high atmosphere; a system used for receiving, processing and storing satellite images (NOAA, MSG, EOS-AQUA, EOS-TERRA), which is capable of processing online more than 120 Tbyte of data; a Hydrogeosite Experimental test field at the the Marsico Nuovo Centre, which is the first full-scale laboratory in Italy for the investigation of hydrogeophysical processes; mobile laboratories consisting of a Lidar system, a system for interferometric and radiometric measurements, a system for non-invasive physico-chemical and geophysical measurements, a system for geochemical and mineralogical measurements and a mobile vehicle equipped with systems of satellite data reception and transmission as well as sensors for ground-based RS data acquisition.
Research TopicsDevelopment and Integration od Lidar, Radiometric and Microwave; Tecniques for the 4D Characterization of Atmosphere; Satellite Remote Sensing for Clouds and Precipitations; OT Multi-platform Methods and Techniques for Surface Process Characterization and Natural and Anthropic; Risk NRT Monitoring; Earth Observation Integrated Techniques for Environmental and Archeological Research - “ARGON”; Micro and Biominerals in Environmental and Human Health Issues; Integrated Methodologies for the Study of Soil and Subsoil; Integrated Modelling for Energy-Environmental Sustainability.
Networks and International Working TeamsNEREUS, Network of European Regions Using Space Technologies; Copernicus Regional Contact Office (RCO) Network ; IGOS-Geohazard Core Team; EGU Core Team; Working group on Satellite data-driven detection, tracking and modeling of volcanic hotspots; ISIS - Working Group.
Staff: more than 100 researchers involved in several international and national research projects.
References: - R. Casa, F. Castaldi, S. Pascucci, A. Palombo, S. Pignatti (2013). “A comparison of sensor resolution and calibration strategies for soil texture estimation from hyperspectral remote sensing”. Geoderma 01/2013.- S. Pascucci, C. Belviso, R. M. Cavalli, A. Palombo, S. Pignatti, F. Santini (2012). “Using imaging spectroscopy to map red mud dust waste: The Podgorica Aluminum Complex case study”. Remote Sensing of Environment, Volume 123, pp. 139-154.- R. Casa, F. Baret, S. Buis, R. Lopez-Lozano, S. Pascucci, A. Palombo, H. G. Jones (2012). “Estimation of maize canopy properties from remote sensing by inversion of 1-D and 4-D models”. Precis. Agric. 04/2012;11(4):319-334.- S. Pignatti, R.M. Cavalli, V.Cuomo, L.Fusilli, S. Pascucci, M.Poscolieri, F.Santini. “Evaluation of Hyperion capability for land covers mapping in a fragmented ecosystem: Pollino National Park (Italy) case study”. RSE, 113 (3) (2009) 622–634. - S. Pascucci, C. Bassani, A. Palombo, M. Poscolieri, R.M. Cavalli (2008). “Road Asphalt Pavements Analyzed by Airborne Thermal Remote Sensing: Preliminary Results of the Venice Highway”. Sensors 2008, 8, 1278-1296. - C. Bassani, R.M. Cavalli, F. Cavalcante, V. Cuomo, A. Palombo, S. Pascucci, S. Pignatti (2007). “Deterioration status of asbestos-cement roofing sheets assessed by analyzing hyperspectral data”. Remote Sensing of Environment, 109, pp. 361-378.- S. Pascucci, Fusilli L., Palombo A., Pergola N., Pignatti S., Santini F. (2013). «Karst water resources detection through airborne thermal data: MIVIS and TASI-600 im-agery”, in International Geoscience and Remote Sensing Symposium (IGARSS'13), 21-26 July 2013 , Melbourne, Australia..- F. Santini, U. Amato, M. Daraio, S. Pignatti, A. Palombo, S. Pascucci, “Calibration is-sues and pre-processing chain of the TASI-600 airborne LWIR hyperspectral scan-ner”. WHISPERS 2013, 25-28 June 2013, Gainesville, Florida, USA.- M. F. Carfora, A. Palombo, S. Pascucci, S. Pignatti and F. Santini. “ Land cover map-ping capability of multispectral thermal data: the TASI-600 case study“. WHISPERS 2013, 25-28 June 2013, Gainesville, Florida, USA.- S. Pascucci, M. Daraio, A. Palombo, S. Pignatti, F.Santini, G. Laneve, ‘TASI-600 high resolution airborne thermal data for accurate materials detection in urban scenarios’. 33rd EARSeL 2013:’Thermal Remote Sensing’ session. 5-7 June 2013- Matera(Italy). - S. Pignatti, Lapenna V., Palombo A., Pascucci S, Pergola N., Cuomo V. (2011). “An advanced tool of the CNR IMAA EO facilities: Overview of the TASI-600 hyperspectral thermal spectrometer“, in 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Lisbon, Portugal, 6 -9 June 2011...
Contacts: Director of CNR IMAA: [email protected]
Hyperspectral RS Lab and TASI facilities: [email protected]
Applications
Karst water resources detection through TASI-600 imagery
R:8383 nm; G:9697 nm; B:11230 nm
TASI-600 urban materials map from emissivities(K coeff. > 0.90)
TASI-600 sub-superficial pipeline monitoring
Strumentazione RS del CNR IMAA
Strumento Tipo Range(μm) Risoluzione
Ocean Optics 2000 Spettrometro 0.3÷0.8 3 nm
Flir SC7000 Camera 3.0÷5.0 integrata
Flir SC900VL Camera 8.0÷12.0 integrata
FT-IR D&P Model 102 Interferometro 2.0÷16.0 4.0 nm @ 8.0 μm
Sensori a terra IMAA
Carta delle principali tipologie vegetazionali del Parco Nazionale del Pollino
AEREO (MIVIS) SATELLITE (HYPERION)
Classificazioni MIVIS e Hyperion ottenute applicando il classificatore supervisionato MD considerando 13 classi CORINE (fino al 4° livello).
Fino al 4° livello CORINE MIVIS e Hyperion hanno prestazioni simili
150 metri
Test area = 484 pixels
Test area = 25 pixels
Test area = 22500 m2
Classificazione MIVIS
Hyperion Classification
RocciaArbusti
Praterie arideFaggi
MIVIS
Hyperion
Ortofoto aerea
Dimensione del pixel terra: 1.5 m
Classificazione Hyperion
Dimensione del pixel a terra: 7 m
Dimensione del pixel a terra: 30 m
Il confronto dei risultati con le percentuali abbondanze dei singoli endmembers a livello di subpixel è ottenute dal MIVIS. Errore definito tramite “Errore Residuale” (RE)
Endmembers% unmixing HYPERION
% MDMIVIS
arbusti 6.54 3.31
faggio 22.20 23.76
Praterie aride 71.26 72.93
RE% = 5.03
1001
1
%
1
2
1
2
L
l
L
l
RF
RFHF
lL
llLRE
Analisi di un sistema naturale ad elevata frammentazione attraverso tecniche di unmixing.
Studi per la missione PRISMA: analisi sub-pixel Parco Nazionale del Pollino
Campagna aerea VNIR per il progetto IOSMOS (IOnian Sea water quality MOnitoring by Satellite data)
Applicati diversi Indici di Vegetazione per il retrieving dello stato di salute della vegetazione(rosso-ottimo; giallo/verde - buono; verde/blu - stressata)