Indian National (Weather) SATellites for Agrometeorological Applications Bimal K. Bhattacharya Agriculture-Terrestrial Biosphere- Hydrology Group Space.
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Indian National (Weather) SATellites for Agrometeorological Applications
Bimal K. Bhattacharya Agriculture-Terrestrial Biosphere- Hydrology Group Space Applications Centre (ISRO) Ahmedabad 380015, India Email : bkbhattacharya@sac.isro.gov.in
1996
1995/1997
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
19991992
1990
1993
2002
2003
INSAT-1DVHRR
INSAT-2AVHRR
INSAT-2E VHRR, CCD (1
KM)INSAT-2BVHRR 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
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
MODIS precipitable water (cm)
Before noon (<1200 hrs) Afternoon (>1200 hrs)
RED DN NIR DNSWIR DN0300 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
maskingCloud
masking
F C C
F C C
Flow of INSAT 3A CCD NDVI operational product generation
13 Aug to 28 Aug’08
6 Mar to 21Mar’09
25 May to 9June’08
1 Nov to 16 Nov’08
16 Oct to 31Oct’08
7 April to 22 April’09
2 Feb to 17 Feb’093 Dec to 18 Dec’08
10 June to 25 June’08 12 July to 27 July’08
14 Sept to 29 Sept’08
26 June to 11 July’08 28 July to 12 Aug’08
29 Aug to13 Sept’08 30 Sept to 15 Oct’08
17 Nov to 2 Dec’08 18 Feb to 05 Mar’09
22 Mar to 6 April’09 23 April to 30 April’09
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 – 0.79
0.80 – 0.90
0.01 – 0.12
INSAT TIR, WV Data3 Hourly Image
Conversion from Grey Count to TBs
Look Up Table for Calibration
Grid Average of IR TBs (0.250x0.250)
Collocation of IR TBs and MW
Rainfall
Estimation of Rainfall
IR and WV - Cloud Classification
PW & RH Correction
Corrected RainfallEstimation
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
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 MODIS AQUA LST(K) at 0.08o grid
K1V
HR
R L
ST
(K) a
t 0.0
8o g
rid
r = 0.93, n = 1446 RMSE = 2.30 K
1:1 Line
Agromet Applications
• Late season drought detection from NDVI• Identification of cold wave zone• Disaster (flood)• Evapotranspiration monitoring for stress
detection & productivity mapping
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 – 0.18
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 – 0.79
0.80 – 0.90
0.01 – 0.12
-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 – 0.79
0.80 – 0.90
0.01 – 0.12
16thOct to 31stOct 2008 16thOct to 31stOct 2009
IMD June-Sept 2009
NDVI ranges
5 Feb’ 087 Feb’ 08
8 Feb’ 08 9 Feb’ 08
-3-2-101234
oC
Capturing Coldwave spell over Northwestern India during January and February2008 using nighttime thermal infrared data from Kalpana-1 VHRR
19 Jan’ 08 20 Jan’ 08 22 Jan’ 08
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
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
No
v05_
dek
ad2
No
v05_
dek
ad3
Dec
05_d
ekad
1
Jan
06_d
ekad
1
Feb
06_d
ekad
1
Feb
06_d
ekad
2
Feb
06_d
ekad
3
Mar
06_d
ekad
1
Mar
06_d
ekad
2
AE
T (
mm
d-1
)
Trans Gangetic Plain
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
No
v05_
dek
ad2
No
v05_
dek
ad3
Dec
05_d
ekad
1
Jan
06_d
ekad
1
Feb
06_d
ekad
1
Feb
06_d
ekad
2
Feb
06_d
ekad
3
Mar
06_d
ekad
1
Mar
06_d
ekad
2
AE
T (
mm
d-1
)
Forest
0
0.2
0.4
0.6
0.8
1
1.2
No
v05_
dek
ad2
No
v05_
dek
ad3
Dec
05_d
ekad
1
Jan
06_d
ekad
1
Feb
06_d
ekad
1
Feb
06_d
ekad
2
Feb
06_d
ekad
3
Mar
06_d
ekad
1
Mar
06_d
ekad
2
AE
T (
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 rabi season using surface energy balance approach
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
mm d-1
0.2
0.4
0.6
0.8
1.0
>1.0
Automated Microclimatein situ observational NetworkUsing INSAT Communication
Transponder – A recent Initiativefrom ISRO
Defining 10 m INSAT- uplinked micrometeorological tower for short (2-3m) vegetation
Agro- Met Station (AMS)
Micromet tower network in India
Selection criteria : fetch ratio (1:50 to 1:100), Agroclimate, vegetation, soil type
CROP
GRASS
WETLAND
DESERT
Forecasting Agricultural out put using Space, Agrometeorology and Land based observations (FASAL)
Econometry
Agro
Meteorology
LandObservations RS, Mod. Re.
Temporal RS, High Re.
Single date
Conventional Remote Sensing
MULTIPLE IN-SEASON FORECAST
Pre- Season
Early- Season
Mid- Season State
Pre- Harvest State
Pre- Harvest District
Cropped areaCrop condition
Crop acreage
Crop yield
RevisedIncorporating damage
Thank you……..
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