TRISHNA : UNE NOUVELLE MISSION SATELLITAIRE …...Jean-Pierre Lagouarde INRA, UMR 1391 ISPA, 33140...

Jean-Pierre Lagouarde

INRA, UMR 1391 ISPA, 33140 Villenave d'Ornon, France

[email protected]

TRISHNA : UNE NOUVELLE MISSION SATELLITAIRE À HAUTE RÉSOLUTION SPATIO-TEMPORELLE POUR LE

SUIVI DE L’ENVIRONNEMENT

9ème Journée9ème Journée Thématique de l ’OASU, Bordeaux, 12 octobre 2017SU

TRISHNA : A NEW HIGH RESOLUTION THERMAL

INFRARED INDO-FRENCH MISSION CONCEPT

FEW Resources.org

General context

Global change (climate, population growth, land use, urbanization, deforestation…) increasing scarcity and deteriorating quality of the water resource monitoring of the water cycle more and more crucial

Thermal infrared → AET, EB (evapotranspiration réelle, bilan d’énergie)

Variability of processes at local scale Need of Spatial systems combining both high spatial resolution and revisit capacities, not existing today

Several projects from the mid 90’s (since IRSUTE, CNES Seguin et al., 1999)…

● 4 LWIR + 3-4 VNIR ● 1 day / 32 km swath● Microbolometers

Lagouarde et al., 2013

…MISTIGRI (CNES)

● HyspIRI (7 LWIR+1MWIR) + 3-4 VNIR● 3 days / Global coverage

● Cooled detector

Crebassol et al., 2014

…THIRSTY (CNES/NASA JPL)

CNES-ISRO projectTRISHNA

Seguin et al. (1999), Rem. Sens. of Environ., 68, 357-369Lagouarde et al. (2013), Int. J. of Remote Sensing, 34 (9-10), 3437-3466Crebassol et al. (2014), IGARSS Symposium, July 13th-18th, Québec City, Canada


1) Ecosystem stress and water use design driver 2) Coastal and inland waters design driver

3) Urban4) Solid Earth5) Cryosphere6) Atmosphere

TRISHNA scientific objectives

Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment


Part of cultivated area under irrigation

Proportion of total water withdrawal

withdrawn for agriculture

20% arable land irrigated →

45% food production (FAO)

Scientific objectives - Ecosystem stress and water use

70% of world water used for agriculture

Severe water stress in manyparts of the world

Rapid increase of water consumption

Trends in water use by sector (UNEP)(http://www.unep.org/dewa/vitalwater/article43.html)


● Agriculture/forestry

- water stress detection / water needs / irrigation optimisation

- water resources management

- growth/ crop production, food security (see 2011 G20)

- impact of agricultural practices on water use, climate change adaptation

- forest fire risks, frost detection…

● Biogeochimical cycles

- carbon cycle ↔ global warming processes

- water quality

- soil pollution

- arctic permafrost

● Hydrology

- link with meteorology (mesoscale circulation)

- water budgets and biogeochimistry at watershed scale

● Ecosystem monitoring, ecology

- microclimates, biodiversity

- natural vegetation droughts


Scientific objectives - Ecosystem stress and water use

res=6 km

res=0.75 km

Modelled SST fields in the California Upwelling System: zooms of the black box at 6 and 0.75 km resolutions (Capet et al., 2008)

Scientific objectives - Coastal and inland waters

Gulf Stream portion seen by the TIRS sensor, Landsat 8, April 9, 2013

2.5 km diameter eddy adjacent to Catalina Island (CA): airborne SST image (left) within situ temperature transects from two boat tracks (right). (after Holt et al., 2012)

Coastal waters

Submesoscale activity (mixing processes) ↔ ecosystems productivity (phytoplankton)

Gaz fluxes (CO2, CH4) at the air-sea interfaces

Coastal zone monitoring and management: water quality, algaeblooms, halieutic resource, fresh water resurgences, discharges(water, pollutants, thermal plumes…)

10x10km


Sea ice

Monitoring melting/freezingprocesses (meltponds, leads, polynyas)

Feedbacks climate ↔ melting ice

Thermal ice thickness as derived from AVHRR

surface temperatures (18 Feb 2004, 1200 UTC) in

the eastern Laptev Sea (After Krumpen et al., 2011)

GTN-L lakes (GCOS) [Essential Climate Variable Ts]

Deltas, estuary hydrology, lagunaes

Biological activity and productivity

Warning of water borne diseases (application to human health)

Thermal discharges

…

Inland waters (lakes and rivers)


Scientific objectives - Coastal and inland waters

● Urban heat island and comfort (welfare of inhabitants, health…)

● Urban vegetation

● Urban and peri-urban hydrology (run-off, urban planning)

● Urban meteorology and atmospheric flow (dispersion of pollutants…)

● Anthropogenic fluxes and energy consumptions (heating, air

conditionning …) AVHRR Aug. 9, 2003 UHI

over Paris (Dousset, 2007)

2008 2050

3.3 5

Urban population (109 inhabitants)

URBAN

● Monitoring volcanic activity(prediction of eruptions, mitigation of risks…)

● Detection of peat and coal fires(pollution,CO2…)

● Detection of thermal anomalies

(geothermal exploration, earthquakes precursors...) Thermal precursors to lava flow at Kliuchevskoi:

anomalies in the crater, ASTER data (Murphy et al., 2013)

SOLID EARTH


Scientific objectives - Secondary objectives

CRYOSPHERE

ATMOSPHERE

(from NASA Earth Observatory)

Himalaya-Karakoram-Hindukush (HKH), virtually a ‘third pole’

● snow and glacier melt runoff

● debris detection in glaciers

● dynamics of glacial lakes

● surface radiation budget

● clouds (high clouds, cirrus…)

● atmospheric water vapor


Scientific objectives - Secondary objectives

0verview on recent research for defining mission specifications

• Impact of atmospheric turbulence on LST measurementsaccuracy

• Analysis of TIR directionnal anisotropy• Development of models and methodologies for estimating

surface fluxes

Recent attention paid on particular topics :

… reveals crucial for determining the mission specifications


Impact of atmospheric turbulence on LST measurements

Experimental measurements of LST temporal fluctuations over a dry maize field

0 200 400 600 800 1000 120033

34

35

36

37

38

39

time (sec)LS

T (

°C)

0 200 400 600 800 1000 120033

34

35

36

37

38

39

time (sec)

LS

T (

°C)

0 200 400 600 800 1000 120033

34

35

36

37

38

39

time (sec)

LS

T (

°C)

0 200 400 600 800 1000 120033

34

35

36

37

38

39

time (sec)

LS

T (

°C)

95 m50 m

20 m5 m

6°C

6°C

Similar fluctuations are observed over a bare dry smooth soil

Low frequency ↔ Planetary BL (PBL), high frequency ↔ Surface BL (SBL) 9ème Journée9ème Journée Thématique de l ’OASU, Bordeaux, 12 octobre 2017SU

Statistics of the satellite LST departure from its mean value

0

10

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40

50

60

70

80

90

100

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2

Fre

qu

en

cy (

%)

Ts uncertainty (°C)

Seq 1

Seq 2

maize

bare soil

Bray 1995

Experimental characterization of the uncertatinty on Ts

0

10

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30

40

50

60

70

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100

0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6

Fre

qu

en

cy (

%)


7m

21m

35m

56m

105m

203m

LES simulation, Pine forest

0.6 °C for ~60% measurements0.8 °C for ~80% measurements

at 50m resolution

Lagouarde et al., RSE 2013Lagouarde et al., RSE 2015

Flexibility on NeDTspecification?


Impact of atmospheric turbulence on LST measurements

UrbanImpact of rows

(vineyard)

Lagouarde et al., RSE 2004, 2010 Lagouarde et al., IEEE, 2013

Lagouarde et al., RSE 2000

Impact of pine stand structure

20°

30°

40°

50°

60°

30°

60°

90°

120°

150°

180°210°

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330°

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120°

150°

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~ 11:30 UT

~ 14:00 UT

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10° 20° 30° 40° 50°

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360°

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0 0

2

10° 20° 30° 40° 50°

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60°

90°

120°

150°

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330°

360°

E - W

N - S

48 ans

15 ans

6 ans

Directional anisotropy

LST prone to important directional anisotropy effects and hot spot

-10

8

6

0

2

Dir

ecti

on

alan

iso

tro

py

(°C

)

-2

4

-8

-6

-4

VZA

Impact of structure(SCOPE simulated)

Comparison of HS inprincipal solar planefor 3 crop structures(spherical, planophile,erectophile)


Directional anisotropy (modelling)

Measured ModeledU

rban

Mar

itim

e P

ine

stan

dModelling directionalanisotropy:

3D models (urban daytimeand nighttime[Lagouarde et al., RSE 2010 and 2012]

SCOPE multilayer model [Duffour et al., 2015 and 2016a]

Parametric approach[Duffour et al., 2016b]

Duffour et al. / RSE, 158 (2015) 362–375Duffour et al. / RSE, 177 (2016a) 248–264Duffour et al. / RSE, 186 (2016b) 250–261

Research currently conducted toimprove parametric approaches bycombining TIR with VNIR anisotropy→ See Zunjian Bian’s Poster


Modelling surface fluxes

Different approaches are followed within the TRISHNA SWG group :

Modèle mono-source Modèle double-source

Ts Tsol

rara

Ta Ta

T0 T0

re

rac

ras

1 source- and 2 source-models based on resistive schemes (Kustas et al.)

SEBAL (Bastiansen, 1998)

B

A

Hmax

LEmax

Ts

Tem

pe

ratu

re d

e s

urf

ace

Albédo

S-SEBI (Roerink et al., 2000)

EF = CB / AB

LE = EF*AE

LE : flux de chaleur

latente

EF : fraction

évaporative

AE: énergie

disponible

WDI (Water Deficit Index) (Moran et al 1994)

METRIC (Allen et al., 2007)

Ta

ux

de

co

uv

ert

ure

vé

gé

tale

=f(

ND

VI)

WDI = AC / AB

WDI = 1 – LE / LEp

LE : flux de chaleur

latente

WDI: indice de stress

LEp : LE en

conditions

potentielles

C

Ts - Ta

BA

C

Contextual approaches (S-SEBI, WDI,…)

Lagouarde and Boulet, 2016. Land Surface Remote Sensing in Continental Hydrology (chapter 10)

Multi-layers TSVA models (MuSICA, SCOPE…) Ogée et al., 2003; Van der Tol et al., 2009; Duffouret al, 2015

soil

canopy

atmosphere


Important methodological know-how → Efforts to develop practical tools for ET mapping

s

From Richard Allen (METRIC/SEBAL workshop Fort Collins, Colorado, February 7, 2005)

Operational applications to water management developed in USA

Development of EVASPA : a tool for

mapping actual evapotranspiration

Gallego Elvira et al., DOI: 10.1016/j.proenv.2013.06.035


Modelling surface fluxes

Regional-scale ET and agricultural consumptive water use from Indian Geostationary Satellites

In : Bhattacharya et al, 2013; ISRO-GBP Scientific report


Main mission specifications


MISTIGRI

HyspIRI

TIRS Landsat 8 TM LandsatLandsat ETM+

m20 30 50 7040 8060 90 100 110 120

ASTER

Mission specifications - Spatial resolution

Acces to field scale require <100m

(Agam 2007, Garrigues 2006, Kustas2004….)

SBL Turbulence limitsaccuracy

0 200 400 600 800 1000 120041

42

43

44

45

46

47Ts(t) pour la résolution de 8 m

Temps (s)

Tem

péra

ture

(°C

)

Puducherry region

Optimum range of resolution at nadir

Degradation of end of swath pixels

Nadir resolution :

TRISHNA


Revisit imposed by 4 combined constraints:

0 50 100 150 200 250 300 350 4000

0.5

1

1.5

2

2.5

3

3.5

4

4.5

DoY

Num

be

r clo

udfr

ee

da

ys

/ 5

da

y p

eri

od

AVIGNON

1 day

2 days

5 days Statistical analysis of ahourly solar radiationdataset (1993-2009, INRAAGROCLIM) over France

Cloud frequency analysis withcriteria: 1 cloudfree day / 5 daysrequired], RAQRS 2010

Analysis of 2000-2009 MODIS cloud masks

1 day 2 days

● minimum availability of cloud free data1

● providing sufficient accuracy on derived products (meteo, irrigation…)

Analysis of ISBA-AGsETR (IPCC scenario A1B,period 1950 - 2100 )

Delogu, E. et al. (2012). HESS, 9, 1699-1740

2

DoY

Flux, LST

0 2 4 6 8 10 12 14 16 18 2034

34.5

35

35.5

36

36.5

37

37.5

38maïs sec

time (minutes)

Ts (°

C)

4°C

20 mn

Dry maize

Assimilation and/or interpolations more robust with higherrevisit

● Necessity of reducing the impact of atmospheric turbulence uncertainty

3


Mission specifications - Revisit

● global coverage requirement orbit/revisit/swath/scan angle4

THIRSTY666 km orbit



Also refer to Anderson et al., 2012

uncertainty SBL (HF)turbulence

Revisit1 2 3 54

MISTIGRI HyspIRI

days

THIRSTY

Temporal variability of meteoforcingwater status (rainfall, irrig.)

Cloud frequencylimits the number of observations

Global coverageToo large scan angles

TRISHNA



1.0

0.9

0.8

0.7

0.5

0.4

0.6

1413121110

Revisit time (LST)

Nas

h e

ffic

ien

cy

1 Overpass time must cope with maximum sensitivity for flux estimation

→ ~12:00 - 13:00 UTC overpass

time providing maximum accuracy

on fluxes retrieval


Mission specifications - Overpass time

Minimizing the sensitivity of LST measurement to overpass time

-5

0

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15

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25

30

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40

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Su

rfac

e t

em

pe

ratu

re (

°C)

Time(UT)

223

252

257

268

272

273

274

275

276

277

286

289

294

296

313

LST at different dates along the year (pine stand)

→ 13 LST minimises possible errors due to variation in acquisition time

→ 13 LST more suited to models having30mn-1hour time steps

2

~

4°C/h

1.0

0.9

0.8

0.7

0.5

0.4

0.6

1413121110

Revisit time (LST)

Nas

h e

ffic

ien

cy

1 Overpass time must cope with maximum sensitivity for flux estimation

→ ~12:00 - 13:00 UTC overpass

time providing maximum accuracy

on fluxes retrieval



13:00 LST daytime 01:00 nightime overpass

1:00 AM preferred for ST measurements over water surfaces (by avoiding remainingskin thermal effects)

3 SST measurements

simulation 13:00 TU 15/07/2004 Toulouse

20°

30°

40°

50°

60°

30°

60°

90°

120°

150°

180°210°

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270°

300°

330°

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-1

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1

2

3

4

5

For mid-latitudes, scan perpendicular to principal plane →limitations of hot spot effects

4 Hot spot impact

!Not true for inter-tropicalzone!



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Fre

qu

en

cy (

%)


Seq 1

Seq 2

maize

bare soil

Atmospheric turbulence- induceduncertainty on LST

NeDT specification betterthan 0.3 K not necessary forcontinental surfaces at 50 mresolution

TBC for water surfaces

0 200 400 600 800 1000 120041

42

43

44

45

46

47Ts(t) pour la résolution de 8 m

Temps (s)

Tem

péra

ture

(°C

)


Mission specifications - Instrument sensitivity

The TIR Hot Spot within the inter-tropical area

No robust model of HotSpot available today large uncertainty of LSTclose to HS

-10

8

6

0

2

Dir

ect

ion

alan

iso

tro

py

(°C

)

-2

4

-8

-6

-4

VZA

HS from SCOPE simulations(Duffour et al., RSE 177, 248-264, 2016)

Duffour et al. / RSE 186 (2016) 250–261Duffour et al. / RSE 177 (2016) 248–264

Debate between (i) a 3 day (666 km) and (ii) a 8 day(679 km) orbit providing 3/2/3 day sub-cycles withdifferent viewing configurations

Scan = HS

January February March

April JuneMay

July August September

October DecemberNovember

Bangalore : position of the TIR hot spot throughout the yearRL model simulations (qualitative)

In inter-tropical (IT)area, HS very oftenclose to the scanline


Mission specifications - Orbit definition

Simulations being performed with a end-to-end simulator to consolidateTIR bands (jointly at CNES, ONERA, IRD and Univ. Valencia)

TOA Luminance at satellite level

Instrument filters and noise

Luminance in satellite bands

T, separation

PrescribedLST and () Estimated and LST

?Comparison/evaluation

Atmospheremodel

Atmospherecorrection

(SW)

4 bands : 8.6 µm = 0.35 µm9.1 µm = 0.35 µm

10.3 µm = 1 µm11.5 µm = 1 µm

0.0

0.2

0.4

0.6

0.8

1.0

7 8 9 10 11 12 13 14 15

Wavelength (m)

Atm

osp

heri

c T

ran

sm

issiv

ity

spectral

smoothed

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

1.05

7 8 9 10 11 12 13 14

Wavelength (m)

Em

iss

ivit

y

MEAN

MAX

MIN

MEAN-STD

MEAN+STD


Mission specifications - TIR spectral bands specification

→ Registrating TIR imagery→ Cloud detection and filtering→ Disaggregation of TIR→ Contextual approaches→ Surface parameters estimation→ …

VNIR bands together with TIR for :

Simultaneity between TIR and VNIR measurements needed both instruments on the same platform

Band Central wavelength (µm)

Need Status

Blue 0.485 Cloudsdiscrimination

Mandatory(degraded resol)

Green 0.555 Coastal, sediments,snow

Mandatory

Red 0.650 Vegetation Mandatory

Near Infrared 0.860 Vegetation Mandatory

SWIR 2 2.13 Atmosphere ISRO requirement

SWIR 1 * 1.38 Atmosphere, cirrus detection

Optional, TBD(degraded resol)


Mission specifications - VNIR spectral bands specification

Current studies - Concept & technologies trade-offs

Concept

Push-broom concept killed off

One study on a scanner

One study with step and stare

Technologies

µbolometer too “slow” for such required performances

MCT cooled detector as

baseline


Mislestones

• November 2017 : French-Indian Mission Design Review, to verify :• the scientific needs and how they are interpreted in a mission specification

• the data distribution policy

• The work share between France and India

• 2018-2019 : phase A, including an industrial instrumental phase A study

• Launch 2024-2025 ?


TRISHNA : UNE NOUVELLE MISSION SATELLITAIRE …...Jean-Pierre Lagouarde INRA, UMR 1391 ISPA, 33140...

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Transcript of TRISHNA : UNE NOUVELLE MISSION SATELLITAIRE …...Jean-Pierre Lagouarde INRA, UMR 1391 ISPA, 33140...