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Report by Goffredo La LoggiaUniversity of Palermo
Laboratorio diTelerilevamento eSistemi Informativi
Territoriali
Universit di Palermo -Dipartimento di
Ingegneria Idraulica edApplicazioni Ambientali
Mediterranean basin, floods, droughts, coastal
problems
Promozione dellinnovazione nella Regione
di Sviluppo Sud-Est della Romania
Sicilia - Romania
Strategia Regionale per lInnovazionedella Regione di Sviluppo Sud-Est
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MEDILAB Laboratorio diTelerilevamento e Sistemi
Informativi Territoriali
DIIAA Dipartimentodi Ingegneria Idraulica
ed Applicazioni Ambientali
E. Cox
H. Nollet
G. La Loggia
V. Noto
G. Ciraolo
A. Maltese
Manager/director/
supervisor andcoordinator
Modelling andimageprocessing
GIS programmingand geostatistics
Model Makerprogramming and
Image processing
IDL programmingand ImageProcessing
Image Processingand databases
Personnel Equipments
Hardware
Software
GIS Platforms
- ARCINFO
- ARCVIEW GIS
- ARCIMS
- ARCPAD
Image Processing
- IDL
- ENVI 3.x
- ERDAS IMAGINE 8.x:
- ER MAPPER 6.x
- IDRISI 32
- EASY TRACE
- CARTALINX
- MSTAR COMMUNICATOR
Data Processing
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ACTIVITY
Remote SensingGeographical
Information SystemsFieldwork
WEB-GIS in an open-source environment
Integrated models within GIS systems
Environmental applications (Monte Pellegrino, Stagnone di Marsala,etc.)
Hydrological applications (GIS to calculate river levels, precipitationanalysis, etc.)
GeographicalInformation Systems
Fieldwork
Bathymetric measurements with echosounder
LAI (Leaf Area Index) measurements
GPS measurements
Spectroradiometric measurements
m
8m
10m
15m
20m
MEDILAB Laboratorio diTelerilevamento e Sistemi
Informativi Territoriali
Numericalmodeling
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ACTIVITY
Remote Sensing 1) Monitoring submerged vegetation in coastal areasusing multi-platform data;
2) Monitoring coastal water quality using remotesensing;
3) Integrating numerical modelling and remote sensingdata to simulate water circulation in coastal lagoons;
4) Applying remote sensing techniques to determinemarine fronts;
5) Analysis of terrestrial vegetation dynamics using timeseries analysis of satellite imagery;
6) Remote sensing and GIS for archaeologicalapplications.
MEDILAB Laboratorio diTelerilevamento e Sistemi
Informativi Territoriali
Remote SensingGeographical
Information SystemsFieldwork Numerical
modeling
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ACTIVITY
Implement, validate and calibrate numericalmodels for the simulation of hydrodynamicconditions and solute transport in coastalareas
Understanding the interaction betweenhydrodynamic local conditions and submergedvegetation (phytobentos) in a coastal lagoon
To set up a field measurements system inorder to understand the dynamical behaviourof the simulated variables (velocities, water
elevations, etc)
To forecast the evolution of the ecosystemwhen the hydrodynamic regime varies
To map flooded areas both in rural and urban
catchments using one and two dimensionalmodels
MEDILAB Laboratorio diTelerilevamento e Sistemi
Informativi Territoriali
Remote SensingGeographical
Information SystemsFieldwork Numerical
modeling
Numerical modeling
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Water resources and hydrology
Keywords:
Flood extent
Flood forecasting
Water resources assessment
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Floods
The importance of a correct modeling of thehydrological processes in flood
Field Data and Remote Sensing
Continuous in-situ measurementsover spatially distributed locations
within nested watersheds.
Repeat-visit, high-resolution, hyper-spectral observations from spaceborneand airborne sensor platforms.
Physically-based DistributedModels
Process-based representations of
basin hydrology, geomorphology andlandatmosphere interactions.
Incorporation of spatial andtemporal distribution of topography,
rainfall, soils, vegetation,meteorology, soil moisture.
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Floods
Field and Remote Sensing Dataover Hydrologic Catchments
Precipitation Hydrologic Statedata estimates
Satellite & AircraftMeteorological Data
EM Data
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Floods
Hydrologic Observations
Measurements ofEarths Topography
Major advances in remote sensing have improved ourcapabilities to simulate and forecast watershed
hydrology. Numerical models capable of utilizing thesedata sources at multiple scales are required.
Measurements ofEarths Precipitation
Measurements of
Earths HydrologicVariables
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Floods
Modeling hydrological processes
Lake
Coastal
Mountain
Riverine
Rainfall-Runoff Transformation
Surface-Groundwaterinteractions in different
scales and lanscapes
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GIS and Floods
SIRI is based on the ArcView GIS environment andallows the determination of maximum probabledischarge all over the Sicilian territory.
The prediction of flood discharge is performed usingtwo different approaches: direct and indirect analysis
DIRECT METHODS
Regional analysis of data
coming from the streamgauge using GEV or
TCEV
INDIRECT METHODS
Hydrologic models
transform the rainfallrecorded on the gaugesover the watershed intodischarge at the outlet.
INDIRECT ANALYSIS
1. RAINFALL MODULE: probabilistic analysis of therainfall using one of the many rainfall pdf implementedin the system (GEV, TCEV; EV1, EV2).
2. LOSS MODULE: transformation of rainfall into runoff
(the runoff coefficient and the SCS-CN method).
3. ROUTING MODULE: the transformation of rainfallexcess to direct runoff (unit hydrograph approach).
SIRI offers the possibility to compare estimation of QT
obtained by different approaches and by different models.
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Flooding delimitation
One image taken by Shuttle astronauts, using SIR-C, appears on the left. On theright is an image of merged JERS-1 radar and a SPOT 3-band composite, whichoffers considerable detail (notice how farmlands show through the water).Mississippi River basin
http://rst.gsfc.nasa.gov/Sect14/Sect14_16.html
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Radar data is used to issue special weather statements
This image shows a map of radar-estimated precipitation totals for a 12 hour period.Since the radar reflectivity is closely related to the precipitation rate, the total amountof precipitation falling on a region over a fixed period of time can be determined byanalyzing reflectivity field over that period.
Flash Floods
http://ww2010.atmos.uiuc.edu/(Gl)/guides/rs/rad/appl/flood.rxml
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Radar data is used to issue special weather statements
This image shows a map of radar-estimated precipitation totals for a 12 hour period.Since the radar reflectivity is closely related to the precipitation rate, the total amountof precipitation falling on a region over a fixed period of time can be determined byanalyzing reflectivity field over that period.
Storm Tracking using raingauges
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Flooding in urban areas
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Urban planning and retrofitting
Planning new urban areasRetrofitting extisting dense
urban contexts
Best Management Practices (BMP)
Road runoff reductionSustainable Urban
Developments (SUDS)
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Infiltration BMPs
Trenches Basins
Pavements Pits and wells
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Storage BMPs
Under parking lots and
streets
Available open spaces
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Vegetated surfaces (diversion BMPs)
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BMP integration example in road engineering
Pervious pavements
Infiltration trenchesVegetated area diversion
Sidewalk storage
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Storage BMPs application
0
0,5
1
1,5
2
2,5
3
3,5
0 40 80 120 160 200 240
tempo [min]
portata
[lps]
T=10 anni
T=5 anni
T=3 anni
T=2 anni
26,1523,1220,618Before [lps]
3,022,852,72,53After [lps]
10532Return period [yrs]
88,5%87,7%86,9%86%Mitigation effect
10532Return period [yrs]
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Parking area with pervious pavement
26,1523,1220,618Before [lps]
17,6613,6410,248,82After [lps]
10532Return period [yrs]
32,5%41%50,3%51%Mitigation effect
10532Return period [yrs]
0
4
8
12
16
20
0 15 30 45 60 75 90
tempo [min]
portata
[lp
s] T=10 anni
T=5 anni
T=3 anni
T=2 anni
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Droughts
Keywords:
Correlation of climatic data vegetation indices;
Correlation analysis;
Water saving measures in rural and urban catchments
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ARIDITY INDEX
Location of areas vulnerable to desertification
and climate change
MSAVI1 VEGETATION INDEX
CLIMATIC DATA REMOTE SENSING DATA
Improvement of the understanding of the relationship betweenclimatic variables and vegetation indices
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LANDSAT 7 ETM+
Satellite: LANDSAT7Sensore: ETM+Data di Acquisizione: 07/07/2002
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MSAVI1
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Aridity Index (Thorntwaite)
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Correlation between climatic parameters and
vegetation indices
Correlazione NDVI-AI
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
1986 1988 1990 1992 1994 1996 1998 2000 2002
Anni
Indice
dicorrelazione
Correlazione NDVI-P
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
1986 1988 1990 1992 1994 1996 1998 2000 2002
anni
Indice
dicorre
lazione
Correlazione MSAVI-P
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
1986 1988 1990 1992 1994 1996 1998 2000 2002
Anni
Indice
dicorrela
zione
Correlazione MSAVI-AI
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
1986 1988 1990 1992 1994 1996 1998 2000 2002
Anni
Indice
dicorrela
zione
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REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING
Aim of the research:
improving of crop water requirement estimation at regional scale in
semiarid regions (water scarcity)
Arguments studied:
1. Evaluation of different Remote Sensing systems for biophysical
variables estimation.
2. Integration use of Remote Sensing and agro-hydrological models:
2.a Soil Water Balance models applications
2.b Surface Energy Balance models applications
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REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
S
W
A
P
Lower boundary
a) Groundwater tableb) No flux
c) Free drainage
d)
Water flow in unsatured soils:
Richards equation
+
Feddes model
Soil-Water and root interactions
Upper Boundary:Crop & Canopy parameters
The Soil-Plant-Atmosphere (SPA) system: Processes and interactions
LAImax = 3.5
LAImin = 0.0+
PotentialEvapotranspiration
Plant - Atmosphere (SPA) interactions
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TEST AREAS
Test area 2002
Menfi
Test area 2005CASTELVETRANO
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
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REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Scene 189/34
Center Lat: +37:28:31
Center Long: +013:49:05
Satellite data: LandSat TM7
(3 bands VIS + 1 NIR 30m x 30m)
22/09/2001
13/02/2002
27/05/2002
07/07/2002
Test data
Airborne sensor: MIVIS
(20 bands VIS + 8 NIR 3m x 3m)
Test area
19/06/2002
Acquisition date
REMOTE SENSING DATA
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REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the MENFI test AreaLeaf Area Index (LAI) estimation
METHODOLOGY
Canopy Radiative Transfer s Models
SAIL+PROSPECT (Verhoef, 1984)
Semi-empiricals Models
CLAIRS (Clevers, 1989)
13/02/2002LAI value
[Minacapilli, DUrso, Qiang, 2004]
Simulation and Management of Irrigation System
Approach:Use of Remote Sensing data
into a Soil Water Balance
model (SWAP code)
[DUrso, Iovino, Minacapilli, 2005]
Etp [mm/d]
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METHODOLOGY
The application of the SEBAL (Surface Energy BAlance for Land) model has been investigated using
hyperspectral (VIS/NIR + TIR) and high resolution airborne data.
HGRET0n
=
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the MENFI test Area
ESTIMATING EVAPOTRANSPIRATION BY MEANS OFHYPERSPECTRAL AIR-BORNE REMOTE SENSING DATA
VIS NIR Mivis bands TIR Mivis bands
Net Radiation Soil Heat Flux Sensible Heat Flux
[Ciraolo, Minacapilli, Sciortino, 2006]
SEBAL OUTPUT: Real Evapotranspiration map
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INVESTIGATIONS
We are validating SWAP and SEBAL model has by means of soil water content and scintillometer flux
and/or eddy tower measurements.
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the CAstelvetrano test Area
ESTIMATING EVAPOTRANSPIRATION BY MEANS OFHYPERSPECTRAL AIR-BORNE REMOTE SENSING DATA
Test area and instruments
location
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Field data acquisitions
- 3D sonic anemometer;
- Fine-wire thermocouple;
- Infrared Gas Analyzer :
CO2. H2O
- Electronic tipping-bucketrain gauge;
- Pyranometer;
- Radiation shield;- Infrared temperature soil
sensor;- Net radiometer;- 107 soil temperature
probes;
-Data logger.
MICRO-METEOROLOGIC MEASUREMENTS: EDDY CORRELATION METHOD
Fastre
sponse
instru
ments
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Field data acquisitions
- 3D sonic anemometer;
- Fine-wire thermocouple;
- Infrared Gas Analyzer :
CO2. H2O
- Electronic tipping-bucketrain gauge;
- Pyranometer;
- Radiation shield;- Infrared temperature soil
sensor;- Net radiometer;- 107 soil temperature
probes;
-Data logger.
MICRO-METEOROLOGIC MEASUREMENTS: EDDY CORRELATION METHOD
Fastre
sponse
instru
ments
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Field truth data acquisition
Capanno contenente la centralina
di rilevamento dati
Pluviografo
0
0
0
0
0 2 4 6 8 1 0 12
Scala portate
LAI (Leaf Area Index) and SPAD: 52 ground stations
Humidity TDR (Time Domain Reflectometry): 15 ground
stations.
Humidity thermo-gravimetric method: 22 soil samples.Soil temperature soil thermometer: 15 ground stations.
Soil and vegetation temperature non contact infrared
thermometer: 15 ground stations.
Spectroradiometric measurements: spectral solar radiance and
irradiance.
Discharge measurements.
Soil use: field prospecting.
Satellite positioning (GPS) WAAS: 3m accuracy.
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The application range is
the visible and the near
infrared (350-2500nm).
Vegetation is one of the
most interesting object to
measure due to its
particular shape in the red-
infrared region.
The spectroradiometer is
an instrument useful to
measure radiance,
irradiance and reflectance
of different material
Field data acquisitions
RADIOMETRIC MEASUREMENTS: SPECTRORADIOMETER
0.00
0.10
0.20
0.30
0.40
0.50
443 523 603 683 763 1175
Wavelength [nm]
Reflectance
2. Vineyard
1. Bare soil
1
2
2
1
3
4
50.00
0.10
0.20
0.30
0.40
0.50
443 523 603 683 763 1175
Wavelength [nm]
Reflectance
4. Meadow
3. Light Asphalt
5. Sand
4
53
REMOTE SENSING AND AGRO HYDROLOGICAL MODELLING:
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FIRST RESULTS:
Scintillometers measurements and SEBAL model validation
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the CAstelvetrano test Area
ESTIMATING EVAPOTRANSPIRATION BY MEANS OFHYPERSPECTRAL AIR-BORNE REMOTE SENSING DATA
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
17-mag 18-mag 19-mag 20-mag 21-mag
ET[mm/h]
Scintillometro
ETrif
Erba medica
17 - 20 maggio 2005
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
8 9 10 11 12 13 14 15 16 17 18
ore
ET[mm/h]
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Scintillometro
Sebal
15/07/2005
ETr
Scintillometro
SEBAL
b)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
8 9 10 11 12 13 14 15 16 17 18
ore
ET[mm/h]
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
ETref
Scintillometro
SEBAL
EFm
14/07/2005
a)
ETr
Scintillometro
SEBAL
REMOTE SENSING AND AGRO HYDROLOGICAL MODELLING:
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FIRST RESULTS:
Soil Water content measurements and SWAP model validation
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the CAstelvetrano test Area
ESTIMATING EVAPOTRANSPIRATION BY MEANS OFHYPERSPECTRAL AIR-BORNE REMOTE SENSING DATA
0
10
20
30
40
50
60
70
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0
[% vol]
z
[cm
]
22 lug
05-ago
08-ago
12-ago
16-ago
Pozzetto A1 D=0
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
19-giu 05-lug 21-lug 06-ago 22-ago 07-set 23-set
10-20 cm
30-40 cm
40-50 cm
50-60 cm
SWAP
DIVINERMeasure
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
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NEXT INVESTIGATIONS:
Use of ASTER Satellite and NERC Airborne remote sensing data for precision farming
applications
REMOTE SENSING AND AGRO-HYDROLOGICAL MODELLING:
a combined approach aimed to improve the crop water requirement estimation in semiarid regions
Applications and results in the CAstelvetrano test Area
ESTIMATING EVAPOTRANSPIRATION BY MEANS OFHYPERSPECTRAL AIR-BORNE REMOTE SENSING DATA
Aster 16/08/2005 (VIS/NIR 15m) Hyperspectral CASI2 image (16 bande 3m x 3m)
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EMERGENCY
Insufficient water resources:Hydrological drought (act of Nature)
Antropic Drought (human responsibilities)
PLANNING (LONG TERM)
INTERMITTENT DISTRIBUTION
PRIORITY USES PRESERVATION
ALT. RESOURCES HARVESTING
REAL TIME NETWORK ANALYSIS
ADVANCED WATER METERINGWATER DEMAND REDUCTION
RAIN/GRAY WATER REUSE
Impact of hydrological drought in urban areas
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Impact of hydrological drought in urban areas
Definition ofdistributiondistricts
Remotelyautomatedcontrol
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I t f h d l i l d ht i b
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M-BUS connectionto the operator
REAL TIME USER MONITORING AND CONTROL
Pulse electronic meters
Local data logger
GPRS/GSM WiFiconnection
Early failure warning
Advanced water metering
Impact of hydrological drought in urban areas
I t f h d l i l d ht i b
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Reducing residential water consumption
Impact of hydrological drought in urban areas
Impact of hydrological drought in urban areas
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Noo!!
Introduction of best water practice
Impact of hydrological drought in urban areas
Impact of hydrological drought in urban areas
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Raccoglie acqua dal tetto e
rifornisce esterno, toilet elavatrice
Alternative resources for non potable uses
Impact of hydrological drought in urban areas
Landslides
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Keywords:
Differential interferometry;
Monitoring.
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The 1983 Thistle landslide at Thistle, Utah
http://landslides.usgs.gov/html_files/landslides/slides/landslideimages.htm
The 4th November 1963 Vajont landslide
www.vajont.net
Comparison of radar scattering mechanisms determined from L-band AIRSAR
polarimetry (Left) and IRS panchromatic data (Right) over the Tsaoling mega
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polarimetry (Left), and IRS panchromatic data (Right) over the Tsaoling mega-
slide south (09/1999).
Jeffrey Weissel and Kristina Rodriguez http://www.slamservice.info/
Coastal
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Keywords:
distribution and dynamic of submerged vegetation;
water column correction; airborne, satellite and field data;
numerical modeling of water circulation and transport
Field Truth Data
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Salt field spectrum
0.0000.1000.2000.3000.4000.5000.600
0.7000.8000.9001.000
350 565 780 995 1210 1425 1640 1855 2070 2285 2500
Wavelength [nm]
Reflectan
ce
Submerged vegetation spectra
0 . 0 0 0 0
0 . 0 10 0
0 . 0 2 0 0
0 . 0 3 0 0
3 5 0 4 0 0 4 5 0 5 0 0 5 5 0 6 0 0 6 5 0 7 0 0 7 5 0 8 0 0
w a v e le n g t h [ n m ]
Posidonia
oceanica
Sand
Deep Water
Deep water
Reflectance measurements on a salt field close the Stagnone, and on submerged vegetation - ASD Field Spec Pro FR
Surveying and precise positioning of field data: Cressi Sub bathyscope and a pair of MagellanProMARK X CPTM GPS
July 2002 and July 2003
Water column correction
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R0 i( ) = R i( )+ Rb i( ) R i( )[ ] e2Kdz( )
LyzengaBen Moussa
Xj =Kd i( )
Kd j( ) Xi + ln
Rb i( ) R i( )[ ]
Rb j( ) R j( )[ ]Kd i( )
Kd j( )
Ben Moussa method require the
knowledge of the opticalproperties of the water
a slight error in the bathymetry causessubstantial over-correction of theinfluence of the water column
Water column correction
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Original image5 m
8 m
10 m
15 m
20 m
Bathymetry Corrected Image
Daedalus AADS 1268 CZCS
Classification of submerged vegetation at the Gulf ofMondello
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Original image
Dipartimento di Ingegneria Idraulica edApplicazioniAmbientaliUniversity of Palermo (Italy) Numerical modelling
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Torna alla primapagina
University of Palermo (Italy)
To implement, validate and calibrate numerical models for the
simulation of hydrodynamic conditions and solute transport incoastal areas
Understanding the interaction between hydrodynamic localconditions and submerged vegetation (phytobentos) in a
coastal lagoon
To set up a field measurements system in order to understandthe dynamical behaviour of the simulated variables (velocities,
water elevations, etc)
To forecast the evolution of the ecosystem when thehydrodynamic regime varies.
Numerical modelling
of water circulationand transport
Dipartimento di Ingegneria Idraulica edApplicazioniAmbientaliUniversity of Palermo (Italy)
Th t d
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University of Palermo (Italy)The study area
shallow water (mean depth 0.95 cm) two openings connecting the lagoon with the open sea
northern mouth characterised by low depths (20 cm;
dry during low tide)
two main sub-basins (northern and southern) water exchange given by wind and tidal effects
presence of islands within the lagoon
presence of a submerged road connecting Mothia with
the coast in the north-south direction presence of seagrasses: Posidonia oceanica
(sometimes emerging during low tide) and Cymodocea
nodosa
Stagnone is a coastal lagoon (2200 ha - naturalreserve) characterised by:
Mothia
Dipartimento di Ingegneria Idraulica edApplicazioniAmbientaliUniversity of Palermo (Italy)
The study area:
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University of Palermo (Italy) y
batimetry
channel
Dredged3
1
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Hydrodynamic numerical
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y ( y)
models (SWE, in-house)
2D model (finite difference) Quasi-3D model (finite elements)
Dipartimento di Ingegneria Idraulica edApplicazioniAmbientaliUniversity of Palermo (Italy)
Transport numerical
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y ( y)
model (in-house)
Passive solute transport Residence time (tide only)
Tide only
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Field measurements
In order to acquire information about the
forcing factors, a tidal gauge (1) and a
meteo station (2) have been installed in2002
The first measurement campaign of
velocities and water levels inside the lagoon
was carried out in July 2003
Two other measurement campaigns were
performed in July and December 2004Mediterra
neanSea
0
South MouthValeport < 0.5 Hz
7, 8 Vector 1-16 Hz
9 ADV 25 Hz
3, 4, 5, 6
2 Meteo gauge
1 Tidal gauge
S.Maria
Northern
8
5
9
4
1
3
2 km
Grande
Isola
6
72
Mothia
East
North
x
y
channelDredged3
1
Mouth
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The equipments
Special platforms rising above the sea
surface were designed and built using
aluminium metal tubes (3 m times 3 m) The platforms enable us to shift the
instruments upwards and downwards
MediterraneanSea
0South Mouth Valeport < 0.5 Hz
7, 8 Vector 1-16 Hz
9 ADV 25 Hz
3, 4, 5, 6
2 Meteo gauge
1 Tidal gauge
S.Maria
Northern
8
5
9
4
1
3
2 km
Grande
Isola
6
72
Mothia
East
North
xy
channel
Dredged3
1
Mouth
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Offshore
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Keywords:
Water quality
Primary production Phytoplancton
Sea Surface Temperature
Suspended solids concentration map - Landasat TM(no atmospheric correction applied)
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South-westSicily
Suspended solids concentration map - Landasat TM(atmospheric correction applied histogram method)
WATER
QUALITY
Suspended solids concentration map - Landasat TM(no atmospheric correction applied)
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Sicily- Palermoand Carini area
Suspended solids concentration map - Landasat TM(atmospheric correction applied histogram method)
WATER
QUALITY
Suspended solids concentration map - Landasat TM(no atmospheric correction applied)
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Suspended solids concentration map. Landasat TM(atmospheric correction applied histogram method)
Sicily- North-east (Milazzo)
WATER
QUALITY
Suspended solids concentration map - Landasat TM(no atmospheric correction applied)
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Suspended solids concentration map - Landasat TM(atmospheric correction applied histogram method)
Sicily- North-west (Trapani)
WATER
QUALITY
Chlorophyll distribution
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Chlorophyll distributionby Seawifs
20 june 98 12 june 9825 june 98
WATERQUALITY
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Marine thermal fronts usingSST by NOAA
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Please visit our website:
www.idra.unipa.it
And then click on MEDILAB
Contact:
Prof.Goffredo La Loggia
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Please visit our website:
www.idra.unipa.it
And then click on MEDILAB
Contact:
Prof.Goffredo La Loggia
Thanks!