On SEBI-SEBS validation in France, Italy, Spain, USA and · PDF fileOn SEBI-SEBS validation in...

September 17th 2003 - ICID RS ET - Montpellier 1

On SEBI-SEBS validation in France, Italy, Spain, USA and China

Massimo Menenti Li Jia2 and ZongBo Su2

- Laboratoire des Sciences de l ’Image, de l ’Informatique et de la Télédétection (LSIIT) , Strasbourg, France

-Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFoM), National Research Council (CNR), Italy2ALTERRA Green World Research, Wageningen University and Research Centre, 6700 AA Wageningen, The Netherlands;


land evaporation: processes and observations

potential

heat balancesurface

water balancesoil

water balanceair

actual

evaporationland

0=+++ LEHGRn PEqdivtv

v −=+δδ0=+++++ EwmQIP δδ


Actual evaporation:a history of methods

NDVI vs. Trad[3]

linear relationshipB, n variable

[2]

linear relationship[1]

SVAT+

PBL[5]

SVAT[4]

improvedobservations

[7]

local maximum ET[6]

heat balanceland surface

Menenti, 2001


RS flux-algorithms

• SEBAL (Bastiaanssen, 1995)

• SEBI (Menenti & Choudhury, 1993; • Su et al, 2000)

• Dual - view angle measurements of surface temperature (Menenti et al, 2001)

temperature

albe

do

LE ≈ 0

H ≈ 0

pbl-temp

obs


SEBI: theory and definitions

)r()T-T(-

)r()T-T(

)r()T-T(-

r)T-T(

SEBI

we

wa0

de

da0

we

wa0

e

a0

=SEBI-1=

EEwet

r λλ=Λ

GRE

n −λ=Λ

( )( )GRH n −Λ−= 1

��

��

��

�

�−��

�

�=

∆

max0hmax

*pamax Cln1Lh

zh

κHucρθ

��

��

��

�

�−��

�

�=

∆

minh0min

*pamin Clnκ1

Lh

zh

Hucρθ

Menenti and Choudhury (1993)

Hmin : ( ) ( )γ+

−+−=

seercρGQs

λE satapa*wet

/GQH −= *max

Reference height = PBL top or blending height

Ta = potential air temperature


Case studies

• France, DAISEX 1999 at Colmar and Hartheim (Jia et al., 2001)• Italy, Pian di Rosia 1997 (Roerink et al., 2000).• Spain (Jia et al., 2003)• USA SGP ’97 (Su et al., 2002)• China (Su et al., 2003)


DAISEXL Overview of data collected

- DAIS (Digital Airborne Imaging Spectrometer)- HYMAP (Hyperspectral Mapper)- ROSIS (Reflective Optics System Imaging Spectrometer)- POLDER (POLarized and Directional Earth's Reflectances)

-WAAC (Wide Angle Airborne Camera)

- LEANDRE LIDAR (aerosols lidar)- ARAT (in-situ atmospheric sensors)

- ERS-1/ERS-2 Tandem SAR

- Landsat TM / SPOT data (for the dates of campaigns)

THREE YEARS OF CAMPAIGNS:Barrax: 1998, 1999 and 2000; Alsace: 1999


SEBI from field measurements

-0.4

-0.2

0

0.2

0.4

0.6

0.17 0.18 0.19 0.2 0.21 0.22

albedo

Nor

mor

lized

(T0

- Ta)

(K /

(s m

-1))

Wet conditionActualDry condition

-100

0

100

200

300

400

500

600

09:00 09:20 09:32 09:40 12:00 12:20 12:48 16:14 17:00

Hour(UTC)

Ener

gy fl

ux (

W m

-2)

Rn G H_obsH_sebi LE_obs LE_sebi

SEBI Flux densities

200

250

300

350

200 250 300 350

LE obsevation ( W m-2 )

LE e

stim

atio

n by

SE

BI (

W m

-2 )

RMSD = 17.4 W m-2

Colmar, sugar beet: SEBI estimates vs. field measurements

RMSD = 17.4 Wm-2


Dry and Wet reference vs. Observations


From SEBI to LE - map

-0.4

-0.2

0

0.2

0.4

0.6

0.8

0 0.05 0.1 0.15 0.2 0.25

albedo

Nor

mal

ized

(T0-

Ta) (

K/(s

m-1

) )

Wet boundaryActualDry boundary

Colmar sugarbeet

Fallow

Sugar beet

Bare soil

maizDistribution of LE at Colmar sub-site; cross indicates location of field measurements

normalized (T0 – Ta) versus surface albedo; airborne HYMAP, DAIS, Colmar

Wm-2

LE


The Simplified Surface Energy Balance Index ( SEBI )

10

20

30

40

50

60

0 0.2 0.4 0.6 0.8 1

Surface reflectance (-)

Sur

face

tem

pera

ture

(o C)

mean temperature

T H

λE max (r 0)

H max (r 0)

T 0

T λE

0

50

100

150

200

250

0 50 100 150 200 250

H [S-SEBI] (W/m2)H

[me

asu

red

] (W

/m2

)

eddy correlationbowen ratioscintillometer

Menenti and Choudhury, 1993; Roerink et al., 1999


SEBS Core Modules

Boundary Layer Similarity Theory

Roughness for Heat Transfer

Surface Energy Balance Index

Meteorological Data

Boundary Layer Variables

Remote Sensing Data

VIS

NIR TIR

Input Output

EvaporativeFraction

Turbulence Heat Fluxes

Actual Evaporation

SEBS - The Surface Energy Balance System


Spain: validation with scintillometers

Location of scintillometer measurements sites

Transmitter Receiver Surface Site Location Height

(m) Location Height

(m)

Distance between transmitter and

receiver (m) Characteristics

Tomelloso 39°07.357′N

2°55.314′W

4.56 39°07.653′N

2°55.951′W

4.15 1070 Dry vineyard

Lleida 41°32.644′N

0°51.644′E

39 41°34.962′N

0°52.444′E

45 4440 Small scale irrigation area with fruit trees, alfalfa

Badajoz 38°55.697′N

6°36.590′W

68 38°56.298′N

6°40.141′W

56 5250 Large scale irrigation area with wheat, corn, alfalfa, lettuce, olives, beans, tomatoes.

Location and characteristics of scintillometer experimental sites in Spain.


SEBS Data RequirementsSurface temperature (K) ATSR

Surface albedo (–) ATSR

NDVI (–) ATSR

Fractional vegetation cover (–) ATSR

PBL depth (m) NWP-RACMO

PBL pressure (Pa) RACMO

PBL potential temperature (K) RACMO

PBL speci.c humidity (%) RACMO

PBL wind speed (m/s) RACMOChannel Central wavelength 50% band wid

(mm) (mm)1 * 12.0 11.60-12.502 * 11.0 10.52-11.333 3.7 3.47-3.904 1.6 1.575-1.6425 * 0.87 0.853-0.8756 * 0.65 0.647-0.6697 0.55 0.543-0.565 ATSR channels


Sensible heat flux: SEBI vs. scintillometers

100 150 200 250 300 350

100

150

200

250

300

350

H e

stim

ated

by

SEBS

(W m

-2)

H observed by LAS (W m-2)

Tomelloso Lleida Badajoz

SEBI (SEBS version)

ATSR-2: surface temperature, albedoand NDVI

vertical error bars = standard deviation over pixels along path

horizontal error bars = error LAS measurements


SEBI: Forward and nadir T0

(Nadir View) (Forward View)

USA: Southern Great Plain 1997 Hydrology Experiment (SGP’97)

Colour from red to yellow, green, blue indicates increasing evaporative fraction

forward view = higher fraction of foliage, lower surface brightness temperature

higher estimate of evaporative fraction


July 1, 2000July 1, 2000 July 8, 2000July 8, 2000

China: Monitoring Droughts


April 2000

01020304050607080

0 20 40 60

Relative Evaporation (%)

Aver

age

Rel

ativ

e So

il Moi

stur

e up

to d

epth

of 5

0cm

(%) Average

Relative SoilMoisture upto Depth of50 cmPredictedAverageRelative SoilMoisture

6

April 2000

01020304050607080

0 10 20 30 40 50


Ave

rgae

Rel

ativ

e So

il Moi

stur

e up

to 2

0 cm

Dep

th (%

) AverageRelative SoilMoisture upto Depth of20 cmPredictedAverageRelative SoilMoisture

April 2000

01020304050607080

0 10 20 30 40 50


Rela

tive

Soil M

oist

ure

(at1

0 cm

dep

th)

SOILMOISTURE(at10 cmdepth)PredictedAverageRelative SoilMoisture

China: Relative evaporation vs relative soil moisture

Time Series of Drought Severity Index

Comparison with Soil Moisture Measurements


Development – related changes in land cover and

water balanceColour composite of multitemporal images of the Soil Adjusted Vegetation Index (SAVI) calculated with AVHRR Ch1 and Ch2 reflectance at 1 km spatial resolution, Aral Sea Basin 1992: SAVI (April)= red; SAVI (june)= green; SAVI (august)= blue; area is 1568 km x 1232 km; greenish areas = irrigated lands


Concluding Remarks

• Method performs well under different conditions• Use of NWP models to determine PBL variables makes

large area applications feasible• Error budgets give significantly higher error estimates• SEBS will be further developed by integrating generic

algorithms to process TOA radiometric data• Case studies should be expanded to time series

On SEBI-SEBS validation in France, Italy, Spain, USA and · PDF fileOn SEBI-SEBS validation in...

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