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Massimo Musacchio, Sergio Teggi, Fabrizia Buongiorno,

Angelo Amodio, Marco Gregnanin, Giulia De Marzi,

Stefano Vignoli, Sergio Perelli, Vincenzo Santacesaria

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The ASI-SRV provides support to the following volcanic activity phases addressed by the Italian Civil Protection Department (DPC):› Surveillance and early warning› Sin-eruption phase› Post-eruption phase

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EO-non EO data Providers

Added value Products

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ASI-SRV system will be developed in 3 phases› In the first version the core of the system has

been realized, including modules/algorithm well known and consolidated (TES, VAOT, Water Vapour, Effusion Rate, SO2 and LAOT) READY TO BE OPERATIVE

› During the following phases RTD based module will be developed and implemented (VAMP, Surface change detection, CO2 , Multiparametric analysis )

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To optimize the computer processing time the ASI-SRV architecture is based on two data processing chains in order to get advantage of partnership infrastructures and laboratories

This presentation is aimed to the “Optical-based” modules .

The Optical data processing chain is localized in Rome at INGV

The SAR data processing chain is localized in Naples at CNR-IREA

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Several spaceborne based EO optical data will be acquired and processed:

NASA EO-1 Hyperion NASA Terra/Aqua MODIS NASA Terra ASTER NOAA AVHRR EROS SPOT Quickbird

Each data is furnished with specific spectral and spatial characteristics

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Pre crisis

Surface Thermal anomalies monitoring ASTER

VAOT Volcanic Aerosol Optical Thickness estimation Hyperion

Water vapour estimation Hyperion

Crisis

Effusion rate AVHRR, MODIS

Ash clouds optical characteristics (VAMP) AVHRR, MODIS

Low resolution Aerosol Optical Thickness (LAOT) AVHRR MODIS

Degassing plumes SO2 Characterization AVHRR MODIS

Post Crisis

Change detection on surface characteristics due:

Lava flow Hyperion and HI-RES

Ash cover Hyperion and HI-RES

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Sensor ProviderRevisittime

Production time

Provision time

Note

QUICKBIRDDigital Globe Eurimage/Telespazio

On demand hours hours

SPOT SPOT IAMGE On demand hours hours

EROSImageSat International IPT

On demand hours hours

ASTER-TERRA NASA 16 days hours hours

Day and Night time passageOn-demand

HYPERION NASA 16 days hours hours

It follows the ASTER-TERRA-NASA orbitOn demand

AVHRRNOAADirect Broadcast

4 hour minutes hoursDirected broadcasted by INGV

MODIS ESA 2 per day minutes hours Night/day

Hig

her S

patia

l Res

oluti

on

Low

er R

evis

it Ti

me

Less than 1 mt

About 1 km

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L1A

Digital Count

L1B

Calibration

Sensor RadianceSensor Reflectance

Coreg

L1C

Sensor RadianceSensor ReflectanceDEMShadedSlopeAspect

Atmospheric Correction

BoA RadianceBoA Reflectance

DEMShadedSlopeAspect

Apparent RadianceApparent Reflectance

L1D

L2A

MapClassified Mask

sensor Geometry

Map Classified Mask

DEM Geometry

L2C

Vector generation

L2D

Vectorial Layer

DEM Geometry

GenericProcessor

Time, spatial Processor

L3A L3B

sensor Geometry DEM Geometry

Level 1

Level 2

Level 3

Auxiliari

Correction terms

LupLd.....

L2B

DEM Geometry

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To have EO “standardized” data, ready to be processed, by means of

Radiometric calibration,

Resized with a defined geographic extension and coverage,

Atmospheric and topographic effect removed

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The need to have common activities performed on the SRV product led to the development of a set of common tools, in order to perform, on different image standards, the same operations.The common tools (named GTR) are devoted to:

cut and mosaic of the input imagescoregistration of input DEM and georeferencing of final SRV products

GIS Referencing ToolGIS Referencing Tool

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Within the ASI-SRV project a well defined geographic window has been defined for each of the three area of interest. (Vesuvio Campi Flegrei, Etna).

This requirement leads to cut the low-res images, since they span over a geographic area wider than the one of interest; while each hi-res image may cover an area which is more narrow than the desired window, so a mosaic of several images followed by a cut of the temporary image obtained is needed.

The tasks are made more complex by the fact that input images are provided in sensor geometry, so the cut has to be done in an appropriate way, in order to avoid the loss of points falling into the desired geographic window.

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ETNA tes site

Satellite/sensor Km dimension Upper Left Lower Right

Width Height Longitude Latitude Longitude Latitude

MODIS regional 350.00 450.00 11° 40’ 00” 39° 50’ 00” 16° 50’ 00” 36° 00’ 00”

MODIS local 40.00 40.00 14° 45’ 32” 37°56’ 40” 15°13’ 04” 37° 34’ 43”

AVHRR regional 350.00 450.00 11° 40’ 00” 39° 50’ 00” 16° 50’ 00” 36° 00’ 00”

AVHRR local 40.00 40.00 14° 45’ 32” 37°56’ 40” 15°13’ 04” 37° 34’ 43”

ASTER 62.00 49.50 14° 42’ 41” 37° 58’ 14” 15° 16’ 32” 37° 24’ 36”

Hyperion 8.50 35.00 14° 58’ 00” 37° 50’ 00” 14° 59’ 11” 37° 30’ 00”

Very High Resolution

26.00 26.00 N/A N/A N/A N/A

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Vesuvio and Campi Flegrei test site

Satellite/sensor Km dimension Upper Left Lower Right

Width Height Longitude Latitude Longitude Latitude

MODIS regional 55.00 33.00 13° 59’ 47” 40° 55’ 07” 14° 36’ 06” 40° 39’ 12”

AVHRR regional 55.00 33.00 13° 59’ 47” 40° 55’ 07” 14° 36’ 06” 40° 39’ 12”

ASTER 65.00 42.00 14° 00’ 00” 41° 00’ 54” 14° 46’ 28” 40° 37’ 14”

Hyperion (Vesuvio)

7.60 12.00 14° 23’ 32” 40° 51’ 50” 14° 27’ 29” 40° 45’ 02”

Hyperion (Campi Flegrei)

16.00 18.50 14° 01’ 26” 40° 54’ 52” 14° 13’ 05” 40° 44° 51”

Very High Resolution

26.00 26.00 N/A N/A N/A N/A

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The DEM Co-registration tool implements the two major functions of orthorectification and georeferentiation of raw images.

The following two different models will be used:› Satellite Sensor Rigorous Orbital Model› Rational Polynomial Coefficients (RPC)

Dem coregistration module produces HDF file as output. This output will be used as input for all DPS. The output level of the generated product is 1C (e.g. ASTER_1C, AVHRR_1C)

The tools are automated and do not require human interaction. The tools execution is scheduled by the SRV system.

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• No specific algorithms are required. The module consists in the mere application of calibration coefficients.

• The ASTER and HYPERION data will be calibrated, while MODIS data will be not calibrated because level 1B data products contain calibrated radiances for all 36 MODIS bands and reflectances for the reflective Solar bands (Bands 1 through 19 and 26).

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• ASTER

Input: Level 1B in Digital Number (DN) Algorithm: Rad=(DN-1)*ASTERFACT

(ASTERFACT are ancillary data files) Output: Radiance [W/m2/ster/m]

• HYPERION

Input: Level 1R in Digital Number (DN) Algorithm: Rad=(DN)* 1/40 (VNIR )

Rad = (DN)*1/80 (SWIR) Output: Radiance [W/m2/ster/m]

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Using CIRILLO the spectral values of atmospheric terms, (i.e. transmittances, reflectance contribution due to solar radiance scattered by the atmosphere and downward spherical albedo of the atmosphere) are computed

The second reason to prefer CIRILLO is due to the capability to evaluate altitude and b factor for each pixel of the image. For these calculations CIRILLO requires as input three images (files), geographically registered with the image to be corrected and with the same spatial resolution, containing elevation, slope and aspect

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A. The sun radiance that reaches directly the pixel viewed by the sensor (target) and that is directly reflected by the target to the sensor;

B. The sun radiance that reaches directly the pixel viewed by the sensor (target) and that is reflected by the target to the sensor following a multiple scattering path;

C. The sun radiance that reaches the target following a multiple scattering path and that is directly reflected by the target to the sensor;

D. The sun radiance that reaches the target following a multiple scattering path and that is reflected by the target to the sensor following a multiple scattering path;

E. The sun radiance that directly reaches the surface surrounding the target and that is reflected by the surface to the sensor following a multiple scattering path;

F. The sun radiance that reaches the surface surrounding the target following a multiple scattering path and that is reflected by the surface to the sensor following a multiple scattering path;

G. The sun radiance that is directly scattered by the atmosphere to the sensor without reaching the ground.

All of these terms, with the exception of G), are also influenced by the orientation of the surface with respect to the sun illumination direction.

A-B-C-D-E-FG

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User Input

Data relevant the sensor, the

acquisition timeand geometry

Data image to be corrected

Data relevant the radiative transfer

models

DEM

Data relevant the adjacency effect

ROI

Computing Modules Output

Ground ReflectanceModule

TOA reflectance Image

Atmospheric Correction LUT

Illumination condition

Ground reflectance Image

Graphic and ASCII file

Graphic and ASCII file for Atmospehric Correction check

Atmospheric correction

"6S" Module for the diffusion terms

"MODTRAN" module for the absorption terms

TOA reflectance Module

Orographic terms Module

Ground Radiance Module

Sensor Response FunctionBand number and position

Solar spectrum

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Massimo Musacchio, Malvina Silvestri, Claudia Spinetti,

Stefano Corradini, Valerio Lombardo, Luca Merucci, Maria

Fabrizia Buongiorno, Sergio Pugnaghi, Gabriele Gangale,

Lorenzo Guerrieri, Sergio Teggi, Vincenzo Santacesaria,

Sergio Perelli

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For each product a historical series of remote sensed data have been processed

By means of specific algorithm and using Auxiliary and Ancillary…

…the product is obtained

Before to post on the foreseen WEBGIS each raster needs to be converted in a ESRI like shapefile

Shapefile

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Discontinuous measurements Webcam network UV-scanner network for SO2 flux Seismic network GPS permanent network Gravimetric network Magnetic network Analysis of the erupted ash Analysis of the erupted products Geologic and structural surveys Thermal mapping from helicopter Lava mapping from field

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At the end of the scientific processing chain, raster classified products are available, and they need to be georeferenced before their transformation in vector products, in order to be displayed as a geographic information layer on a map.This task is performed by the “Map Projection” module, in order to warp them in an UTM projection.

This georeferenced product is then stored in a Geo-TIFF file, that contains all the information needed for a correct visualization on a GIS.The product obtained is then ready to be analyzed by the Operator using the GTA, in order to validate or discard it before the publishing to the end user.

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The GTA is a customization of ESRI ArcGIS Desktop to support the operator in performing the Validation Process Workflow.

GTA will use ESRI ArcGIS (and its extensions):

ArcGIS is powerful to manage a huge amounts of SRV productsArcGIS is widely used within DPC and INGVArcGIS includes a wide variety of programmable components, so that plug-in functionalities to validate SRV products can be integratedArcGIS, using some extensions, is compliant with the OGS protocols to be used in the frame of the project (LDS)

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SRV Process Validation Workflow

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For further information on ASI-SRV project contact:Maria Fabrizia Buongiorno: buongiorno@ingv.it