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Workshop on climatic analysis and mapping for agriculture 15 June 2005
Frost mapping with NOAA- AVHRR data
G. Antolini, V. Marletto
ISTITUTO DI BIOMETEOROLOGIA CONSIGLIO NAZIONALE DELLE RICERCHE
Meteorological Service – Enviromental Protection and Prevention Agency
Remote Sensing Laboratory
With the collaboration of:
M. Menenti, Z.L. Li, F. BeckerLaboratoire des Sciences de l'Image, de
l'Informatique et de la Télédétection Université Louis PasteurStrasbourg
Workshop on climatic analysis and mapping for agriculture 15 June 2005
What we needed…
We need to assess the spatial variability of frost, in order to:
- Validate our interpolation models and improve them- Realize a frost risk map for Emilia-Romagna- Assess the simulation of frost events with numerical meteorological models
By frost maps we mean night Land Surface Temperature (LST) maps, during a frost event
Workshop on climatic analysis and mapping for agriculture 15 June 2005
What is frost…
Physical meaning: a phase change in water (from liquid or vapor to solid)
We want to know where frost is more likely to occur in order to plan crop protection (radiative frost).
Agrometeorological meaning: low temperatures that causes ice formation in crop cells
Workshop on climatic analysis and mapping for agriculture 15 June 2005
What is frost…
Typical synoptic situation
Typical micrometeorological conditions
Workshop on climatic analysis and mapping for agriculture 15 June 2005
833 km, 7:30 a.m. descending node (NOAA12) ; 13:30 p.m. ascending node (NOAA14), sun-synchronous, near-polar, circular
Orbit:
± 55°± 55°± 55°± 55°± 55°FOV
1.11.11.11.11.1Spatial resolution km
2399
0.12 K
1.41
Insb
33.55-3.93
2399
0.12 K
1.41
HgCdTe
410.3-11.3
239923992399Swath km
0.12 KS/N > 3:1S/N > 3:1Radiometric precision
1.391.511.39 I FOV mrad
HgCdTeSiSiDetector
511.4-12.4
20.725-1.00
10.58- 0.68
Spectral bands (µm)
833 km, 7:30 a.m. descending node (NOAA12) ; 13:30 p.m. ascending node (NOAA14), sun-synchronous, near-polar, circular
Orbit:
± 55°± 55°± 55°± 55°± 55°FOV
1.11.11.11.11.1Spatial resolution km
2399
0.12 K
1.41
Insb
33.55-3.93
2399
0.12 K
1.41
HgCdTe
410.3-11.3
239923992399Swath km
0.12 KS/N > 3:1S/N > 3:1Radiometric precision
1.391.511.39 I FOV mrad
HgCdTeSiSiDetector
511.4-12.4
20.725-1.00
10.58- 0.68
Spectral bands (µm)
What we used…
NOAA Polar orbiter satellite
AVHRR sensor
Workshop on climatic analysis and mapping for agriculture 15 June 2005
What we used…
Workshop on climatic analysis and mapping for agriculture 15 June 2005
1exp 25
10
TC
CTB
Planck blackbody law:
A few words on theory…
Problems:
Land surface is not a perfect blackbody.
The emitted radiance depends on spectral emissivity and land surface temperature.We cannot assume homogenous emissivity.There are always one more missing variable than equations (N channel emissivities + surface temperature).
Atmospheric correction
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Processing of NOAA-AVHRR data
Pre-processing of raw data
- Calibration- Navigation (manual or automatic)
Processing of calibrated data
- Cloud detection and masking- Atmospheric correction- Surface emissivity retrieval- Land surface temperature retrieval
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Pre-processing…
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Cloud detection
Saunder and Kriebel (1988, IJRS, 9: 123-150)Gesell (1989, IJRS,10: 897-905) for ice/snow detection
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Atmospheric correction
Atmospheric water vapor retrieval
Ch. 4 Ch. 5
MODTRANRadiosoundsRadiative transfer modelling to compute unknown atmospheric radiative quantities
Computation of night and day surface brightness temperature
Atmospheric quantities
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Surface emissivity retrieval
TISI (Temperature-Independent Spectral Indices)
Day surface brightness temperature
Ch. 3, 4, 5
March 17th 2003, 04:25 UTC
Night surface brightness temperature
Ch. 4, 5
March 19th 2003, 15:01 UTC
Emissivity depends on:
Composition of surface
Roughness of surface
Other physical parameters (soil moisture…)
Wavelength
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Land surface temperature retrieval
Surface emissivityAtmospheric quantities maps (atmospheric correction results)
Split window algorythm
Workshop on climatic analysis and mapping for agriculture 15 June 2005
March 17th 2003 04:25 UTC
Workshop on climatic analysis and mapping for agriculture 15 June 2005
March 23th 2003 03:39 UTC
Workshop on climatic analysis and mapping for agriculture 15 June 2005
April 9th 1997 02:04 UTC
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Comparison with observations(spatial interpolation methods)
Some considerations:
- thermodynamique vs radiometric temperatures- time lag- spatial resolution- surface vs air temperature
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Frost risk mapping
LATE FROST RISK
low medium high very high
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Numerical weather simulations
RAMS (Regional Atmospheric Modeling System)
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Thanks for your attention
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Satellite
Atmosphere
Outer of atmosphere
Sun
Surface
A few words on theory…
Workshop on climatic analysis and mapping for agriculture 15 June 2005
T
B
RRTTTT
i
ati
i
iai
i
iiS
i
)(1)(
1
Effects on LST of atmosphere (transmissivity) and emissivity
i
0,89 0,90 0,91 0,92 0,93 0,94 0,95 0,96 0,97 0,98 0,99 1,00
Ts-
Tgi
0
1
2
3
4
5
6
TropicalMidlatitude summerMidlatitude winter
Channel 4
different slopes correspond to different Ts (20 °C variation) for same atmosphere
Tgi
250 255 260 265 270 275 280 285 290 295 300 305 310 315 320
Tg
i-Ti
-2
-1
0
1
2
3
4
5
6
7
8
9
10
11
12
TropicalMidlatitude summerMidlatitude winter
Channel 4
Workshop on climatic analysis and mapping for agriculture 15 June 2005
Becker F., Li Z. L., 1995. Surface temperature and emissivity at various scales: definition, measurement and related problems. Remote Sensing Reviews, vol. 12, 225-253.
Gesell, G., 1989. An Algorithm for Snow and Ice Detection Using AVHRR Data: An Extension to the APOLLO Software Package. Int. J. Remote Sensing 10, 897-905.
Li Z.L., Becker F., Stoll M.P., Wan Z., 1999. Evaluation of six methods for extracting relative emissivity spectra from thermal infrared images. Remote Sens. Environ. 69, 197-214.
Nerry F., Petitcolin F., Stoll M.P., 1998. Bidirectional reflectivity in AVHRR channel 3: application to a region in Northern Africa. Remote Sens. Environ. 66, 298-316.
Saunders R.W., 1986. An Automated Scheme for the Removal of Cloud Contamination from AVHRR Radiances over Western Europe. Int. J. Remote Sensing 7, 867-886.
Saunders, R.W., Kriebel, K.T., 1988. An Improved Method of Detecting Clear Sky and Cloudy Radiances from AVHRR Data. International Journal of Remote Sensing 9: 123-150.
Sobrino J.A. (ed.), 2000. Teledetección. Servicio de Publicaciones, Universidad de Valencia, ISBN 84-370-4220-8, 467 pp.
Sobrino J.A., Raissouni N., Li Z.L., 2001. A comparative study of land surface emissivity retrieval from NOAA data. Remote Sens. Environ. 75, 256-266.
BIBLIOGRAPHY