agriculture space

7/28/2019 Agriculture Space

1/17

Indian National (Weather) SATellites forAgrometeorological Applications

Bimal K. Bhattacharya Agriculture-Terrestrial Biosphere- Hydrology Group

Space Applications Centre (ISRO)Ahmedabad 380015, India

Email : [email protected]


2/17

1996

995/1997

1999 2003

IRS-1C/1D LISS-3(23/70M)

STEERABLE PAN (5.8 M)

WiFS (188M)

IRS-P3

WiFS, MOS X-Ray

IRS-P4 (OCEANSAT-1)

OCM, MSMRIRS-P6(RESOURCESAT)

LISS 3 23.5/140 Km

LISS 4 - 5.8M/ 27Km

AWiFS - 55M/ 730 Km

1999

1992

1990

1993

2002

2003

INSAT-1D

VHRR

INSAT-2A

VHRR

INSAT-2E

VHRR, CCD (1KM)INSAT-2B

VHRR METSAT-1

VHRR 2 Km(vis);

8 Km(IR & WV)INSAT-3A

VHRR 2

Km(vis);

8 Km(IR & WV)CCD 1 Km

PRESENT ...

2005

IRS-P5 (CARTOSAT-I)

PAN 2.5 m stereo

IRS-P7 (CARTOSAT-II)

PAN 0.85 m

2007


3/17

VIS : 2km TIR-day : 8km TIR-night : 8kmWV-day : 8km CCD FCC : 1km

Optical band Water Vapour band Thermal Infrared band Optical bands

KALPANA - 1 VHRR INSAT 3A CCD

Satellite Sensor Bands (m) Spatial res.Kalpana -1 VHRR VIS (0.55-0.75)

WV (5.7-7.1), Thermal IR (10.5-12.5)

2km x 2km

8km x 8km

INSAT 3A

VHRR

CCD Red (0.62-0.68), NIR(0.77-0.86), SWIR (1.55-1.69) 1km x 1km

INSAT 3D

(2011)

Imager VIS(0.52-0.75), SWIR(1.55-1.70)

MIR(3.8-4.0)

WV(6.5-7.0), TIR1(10.2-11.2), TIR2(11.5-12.5)

1km x 1km

4km x 4km

4km x 4km

Sounder 19 channels 10km x 10km

Geo-HR

(2015)

Imager Red, NIR, SWIR

Thermal IR

100m X 100m

1 km X 1km

Suite of Indian geostationary Sensors


4/17

MODIS precipitable water (cm)

Before noon (1200 hrs)

RED DN NIR DNSWIR DN

0300 GMT 0400 GMT 0500 GMT 0700 GMT 0900 GMT

Molecular scattering

(Rayleigh)

MODIS ozone (Dobson)

MODIS AOD (tau550)

DEM (m)

Mie scattering

Level 1A correction

N

D

V

I

Level 1B & 1C correctionCloud

masking

Cloud

masking

F

C

C

F

C

C

Flow of INSAT 3A CCD NDVI operational product generation


5/17

13 Aug to 28 Aug08

6 Mar to 21Mar09

25 May to 9June08

1 Nov to 16Nov08

16 Oct to 31Oct08

7 April to 22 April09

2 Feb to 17 Feb093 Dec to 18 Dec08

10 June to 25 June08 12 July to 27 July08

14 Sept to 29 Sept08

26 June to 11 July08 28 July to 12 Aug08

29 Aug to13 Sept08 30 Sept to 15 Oct08

17 Nov to 2 Dec08 18 Feb to 05 Mar09

22 Mar to 6 April09 23 April to 30 April09

VEGETATION DYNAMICS FROM INSAT 3A CCD

-1.00 0.00

0.13 0.15

0.16 0.18

0.19 0.21

0.22 0.24

0.25 0.26

0.27 0.30

0.31 0.34

0.35 0.37

0.38 0.41

0.42 0.46

0.47 0.50

0.51 0.60

0.61 0.69

0.70 0.790.80 0.90

0.01 0.12


6/17

INSAT TIR, WV Data

3 Hourly Image

Conversion fromGrey Count to TBs

Look Up Table forCalibration

Grid Average of

IR TBs (0.250x0.250)

Collocation of IR

TBs and MW

Rainfall

Estimation ofRainfall

IR and WV - Cloud

Classification

PW & RH

Correction

Corrected Rainfall

Estimation

Final Rain Rate, Daily, Pentad,

monthly & Seasonal Rainfall

Model PW

& RH Forecast

Satellite Microwave

Rainfall (TRMM/SSMI)

Grid Avg. Rainfall

(0.250x0.250)

Rainfall Validation/ Fine

Tuning (DWR/SFRG)

Flow Chart for rainfall estimation from INSAT VHRR

(Gairola et al. 2008)

Rainfall product


7/17

Surface Emissivity

Original VHRR

thermal IR data

Correction for

atmospheric water

vapour & surface

emissivity

Characteristic vertical

tropospheric air

temperature profiles and

AIRS sounder based

surface air temperature

cm

K

K

K1VHRR LST

Experimental product Land surface temperature (LST)

Precipitable water

290

295

300

305

310

315

320

290 295 300 305 310 315 320Aggregated MOD IS AQUA LST(K) at 0.08

ogrid

K1VHRRLST(K)at0.08

ogrid

r = 0.93, n = 1446

RMSE = 2.30 K1:1 Line


8/17

Agromet Applications

Late season drought detection from NDVI

Identification of cold wave zone

Disaster (flood)

Evapotranspiration monitoring for stress

detection & productivity mapping


9/17

30thSept to 15thOct 2008 30thSept to 15thOct 2009

Late season agricultural drought detection from

INSAT 3A CCD NDVI

-1.00 0.00

0.13 0.15

0.16 0.180.19 0.21

0.22 0.24

0.25 0.26

0.27 0.30

0.31 0.34

0.35 0.37

0.38 0.41

0.42 0.46

0.47 0.500.51 0.60

0.61 0.69

0.70 0.79

0.80 0.90

0.01 0.12

-1.00 0.00

0.13 0.15

0.16 0.180.19 0.21

0.22 0.24

0.25 0.26

0.27 0.30

0.31 0.34

0.35 0.37

0.38 0.41

0.42 0.46

0.47 0.500.51 0.60

0.61 0.69

0.70 0.79

0.80 0.90

0.01 0.12

16thOct to 31stOct 2008 16thOct to 31stOct 2009

IMD June-Sept 2009

NDVI ranges


10/17

5 Feb 087 Feb 08

8 Feb 08 9 Feb 08

-3-2-101234

oC

Capturing Coldwave spell over Northwestern India during January and February

2008 using nighttime thermal infrared data from Kalpana-1 VHRR

19 Jan 08 20 Jan 08 22 Jan 08


11/17

22 Aug 2008 31 Aug 2008 1 Sept 2008

2 Sept 2008 3 Sept 2008 5 Sept 2008

Capturing damaging events : Koshi flood 2008 from 3A CCD

M hl A l d R l i E i i d i bi


12/17

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

N

ov05_

dekad2

N

ov05_

dekad3

D

ec05_

dekad1

J

an06_

dekad1

F

eb06_

dekad1

F

eb06_

dekad2

F

eb06_

dekad3

M

ar06_

dekad1

M

ar06_

dekad2

AET(mmd-1)

Trans Gangetic Plain

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

6.5

7

7.5

N

ov05_

dekad2

N

ov05_

dekad3

D

ec05_

dekad1

Jan06_

dekad1

Feb06_

dekad1

Feb06_

dekad2

Feb06_

dekad3

Mar06_

dekad1

Mar06_

dekad2

AET(mm

d-1)

Forest

0

0.2

0.4

0.6

0.8

1

1.2

Nov05_

dekad2

Nov05_

dekad3

Dec05_

dekad1

Jan06_

dekad1

Feb06_

dekad1

Feb06_

dekad2

Feb06_

dekad3

Mar06_

dekad1

Mar06_

dekad2

AET(mm

d-1)

DesertAgriculture Forest

Desert

AET November AET December AET January AET February AET March

RET November RET December RET January RET February RET March

Monthly Actual and Relative Evapotranspiration during rabiseason

using surface energy balance approach

1.0

2.0

3.0

4.0

5.06.0

7.0

8.0

mm d-1

0.2

0.4

0.6

0.8

1.0

>1.0


13/17

Automated Microclimate

in situ observational Network

Using INSAT CommunicationTransponder A recent Initiative

from ISRO


14/17

Defining 10 m INSAT- uplinked micrometeorological tower for

short (2-3m) vegetation

Agro- Met Station (AMS)


15/17

Micromet tower network in India

Selection criteria : fetch ratio (1:50 to 1:100), Agroclimate,

vegetation, soil type

C

R

O

P

G

R

A

S

S

W

E

T

L

A

N

D

D

E

S

E

R

T


16/17

Forecasting Agricultural out put usingSpace,Agrometeorologyand Land basedobservations (FASAL)

Econ

ometry

Agro

Meteor

ology

Land

Observations RS,Mod.Re.Temporal RS,HighRe

.

Singledate

Conven

tiona

l RemoteSensing

MULTIPLE IN-SEASON FORECAST

Pre-

Season

Early-Season

Mid-SeasonState

Pre-HarvestState

Pre-HarvestDistrict

Cropped area

Crop condition

Crop acreage

Crop yield

RevisedIncorporating damage


17/17

Thankyou..

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