Variability in Normalized Difference Vegetation Index (NDVI) in relation to south 

west monsoon, western ghats, India

T.V. Lakshmi Kumar, R. Uma, Humberto Barbosa & K. Koteswara RaoAtmospheric Science Research Laboratory, Dept of Physics

Faculty of Engineering & TechnologySRM University

International SWAT Conference, 18th to 20th July 2012, IIT, New Delhi

• Vegetation over a ground, forms naturally or by cultivation attained a great importance in the  context of changing climate scenario over the globe.

• Vegetation is also controlled by the climate which in turn leads to climate – vegetation feedback mechanism.

Background

MONITORING VEGETATION

• Vegetation can be monitored by– Crop experiments– Satellites

• Advantage of satellite– Satellite can cover large areas        

MONITORING VEGETATION THROUGH SATELLITE

• Satellites such as– AVHRR–MODIS Terra

provide Normalized Difference Vegetation Indexto study the ground vegetal cover.

• The Normalized Difference Vegetation Index(NDVI) is used to measure and monitor plantgrowth , vegetation cover and biomassproduction from multispectral satellite data.

MODIS Terra

• Resolution : 250m

• Time Interval: 8 days

• Data period: South West (June to September) monsoon of 2000 to 2011

• MODIS makes use of frequency band 645 nm for red and 857 nm for near Infra‐Red to obtain the NDVI

NDVI• NDVI is calculated from the visible and near‐infrared light reflected by vegetation.

• Healthy vegetation (left) absorbs most of the visiblelight that hits it, and reflects a large portion of the nearinfrared light.

• Unhealthy or sparse vegetation (right) reflects morevisible light and less near‐infrared light.

• NDVI valves from ‐1 to +1.NDVI < 0 ‐‐‐ Water Bodies0 < NDVI < 0.2       ‐‐‐ Less Vegetation0.2 < NDVI < 0.4    ‐‐‐ Medium Vegetation0.4 <  NDVI < 0.8 ‐‐‐ High VegetationNDVI > 0.8 ‐‐‐ Rain Forest

Objectives of the work

• Study on interannual variability of NDVI

• Study on the relation of NDVI with Rainfall

• Understanding NDVI variations with south west monsoon distribution and activity

• Investigation on a few crop phenological stages

Deriving NDVI

MODIS  DATA DOWNLOADING

GEOMETRIC CORRECTION

RESAMPLING CLOUD MASKING

NDVI MAP GENERATION

STATISTICAL EXTRACTION

NON –AGRICULTURAL AREA MASKING

NDVI CALCULATION

Study Area

•The Western Ghats extends along  the West coast of  India 

from latitude 8.2°to 15.6° N 

•Area  ‐ 160,000 sq km. 

•Western Ghats is an all time humid region.

• Mean annual rainfall  ‐ 2200 mm 

• Mean annual temperature ‐ 20°C ‐ 22° C. 

•Moisture Index is always above 80%

Western Ghats ‐ Test sites

Name of Test site Latitude (N) Longitude(E)Madikeri 12.42 75.73Somwarpet 12.59 75.84Virajpet 12.20 75.80Bantwal 12.89 75.03Mangalore 12.91 74.85Puttur 12.75 75.19Sulya 12.55 75.38Karkala 13.21 75.00Udupi 13.33 74.76Kundapur 17.46 78.35Haliyal 15.32 74.75Honnavar 14.28 74.45Karwar 14.81 74.13Kumta 14.42 74.41Supa 15.16 74.30Yellapur 14.96 74.70

Vegetation  (NDVI)

Rainfall Amount

No of Rain Events

Monsoon Distribution

Monsoon Activity

Antecedent Precipitation Index (API)

Where  j ‐ current week j‐1   ‐ previous week Ct = (Pt/Po)

Where• Pt ‐ tth week rainfall • Po  ‐initial rainfall

API (j) = API (j‐1)*C + Pt

IMD Criterion Categorization of Rainy days

Light Rainy Day (LR) ‐ Rainfall is less than 7.4mm Moderate Rainy Day (MR)  ‐ Rainfall is fro, 7.5mm to 34.4mm Heavy Rainy Day (HR) ‐ Rainfall is above 34.5mm

Monsoon distribution

Isolated (I)  ‐ No of sites recording rainfall of 2.5mm and above should of 25% of  total number of sites.

Scattered (S) ‐ No of sites recording rainfall of 2.5mm and above should of 25% to 50%of total number of sites.

Fairly wide spread (F)‐ No of sites recording rainfall of 2.5mm and above should of 50% to 75%of total number of sites.

Wide spread (W) ‐ No of sites recording rainfall of 2.5mm and above should of above 75% of total number of sites.

IMD Criterion • Monsoon activity

Weak (W) ‐ Actual rainfall should be below one and half of the normal

Normal (N)  ‐ Actual rainfall should be half and one and half of the normal

Active (A) ‐ Actual rainfall should be one and half to four times of thenormal. At least two places should get rain above 30mmrainfall and rainfall distribution should be fairly wide spread.

Vigorous (V) ‐ Actual rainfall should be above four times the normal. At least two places should get rainfall above 50mm and rainfall distribution should be fairly wide spread to wide spread.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-15

-12

-9

-6

-3

0

3

6

9

12

15

18o)Yellapur - UK

Ano

mal

y

Year

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-15

-12

-9

-6

-3

0

3

6

9

12

15l) Honnavar - UK

Ano

mal

y

Year

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-18

-15

-12

-9

-6

-3

0

3

6

9

12h) Karkala - Udupi

Ano

mal

y

Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-12

-9

-6

-3

0

3

6

9

12m) Karwar - UK

Ano

mal

y

Year

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-15

-12

-9

-6

-3

0

3

6

9 j) Kundapur - Udupi

Ano

mal

y

Year2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-9

-6

-3

0

3

6

9

12

Ano

mal

y

Year

a) Madikeri - Kodagu

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-12

-9

-6

-3

0

3

6

9

12

e) Mangalore - DK

Ano

mal

y

Year

Interannual Variability of NDVI

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-18

-15

-12

-9

-6

-3

0

3

6

9

12

15g) Sulya - DK

Ano

mal

y

Year

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-9

-6

-3

0

3

6

9 b) Somwarpet - Kodagu

Ano

mal

y

Year

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

-10

-5

0

5

10An

omal

y

Year

WESTERN GHATS AS WHOLE

SLOPE  = 0.71

Monthly NDVI

vsRainfall

Rainfall Anomalies Rainfall Anomaly

Year June  July August September October

2000 26 ‐26 ‐10 ‐25 ‐7

2001 28 ‐12 ‐50 ‐6 3

2002 ‐6 ‐53 ‐32 ‐53 143

2003 35 ‐17 ‐31 ‐22 ‐5

2004 8 ‐24 ‐23 ‐26 ‐21

2005 11 17 ‐46 5 ‐9

2006 8 ‐23 ‐33 92 27

2007 51 ‐11 2 46 ‐9

2008 10 ‐42 ‐21 13 ‐25

2009 ‐8 25 ‐27 51 24

2010 ‐14 3 ‐33 55 57

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0

500

1000

1500

2000

2500

3000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

NDVIAP

I

Week

Weekly Mean NDVI vs API

API NDVI Wkly Mean

Year Correlation (API & NDVI)

2001 0.242002 0.402003 0.892004 0.252005 0.542006 0.512007 0.522008 0.222009 0.242010 0.53

Mean of WeakyNDVI & RF(API)

0.48

NDVI vs %of Light, Moderate and Heavy Rainy Events

Year No. Of Rain Events Monsoon Distribution Monsoon ActivityNDVI LR MR HR I S FWS WS MW MN MA MV

2000 0.319 17 40 26 23 15 18 66 49 45 7 212001 0.270 20 42 24 23 7 18 74 49 55 3 142002 0.348 20 40 16 26 10 27 59 66 40 4 112003 0.287 21 46 22 17 12 17 76 42 64 4 122004 0.341 18 41 22 26 9 22 65 47 62 1 122005 0.289 17 44 26 20 13 16 73 39 63 5 152006 0.311 16 46 25 23 13 12 74 46 59 3 132007 0.235 18 42 34 10 11 25 76 27 68 11 152008 0.193 19 39 22 21 22 21 58 63 39 7 132009 0.330 20 40 26 16 15 29 62 53 46 4 192010 0.356 22 48 26 9 13 19 81 44 55 10 12

Test Site CorrelationLR MR HR

Madikeri 0.10 0.11 ‐0.36Somwarpet ‐0.39 0.41 0.30Virajpet 0.07 0.05 ‐0.41Bantwal 0.07 ‐0.04 ‐0.25Mangalore ‐0.06 ‐0.03 ‐0.02Puttur 0.38 0.10 ‐0.24Sulya ‐0.35 0.45 ‐0.62Karkala ‐0.50 ‐0.03 0.08Kundhapur ‐0.14 0.28 ‐0.57Udipi 0.55 0.13 ‐0.34Haliyal ‐0.14 0.14 ‐0.39Honnavar 0.70 0.03 ‐0.60Karwar ‐0.30 0.56 ‐0.18Kumta ‐0.33 0.56 ‐0.63Supa 0.30 0.06 0.09Yellapur ‐0.02 ‐0.18 0.43

LR = Light Rainy Days; MR = Moderate Rainy Days & HR = Heavy Rainy Days

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100

10203040506070

Monsoon Distribution

Perc

enta

ge(%

)

Year

I S FWS WS

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100

10

20

30

40

50

60

Monsoon Activity

MW MN MA MV

YEARCorrelation

Monsoon Distribution Monsoon ActivityI S F W W N A V

2000 0.3 0.3 0.1 ‐0.2 0.1 0.1 0.3 ‐0.3

2001 0.5 0.4 0.2 ‐0.3 0.2 ‐0.1 0.4 ‐0.5

2002 0.6 0.1 ‐0.1 ‐0.3 0.1 0.0 ‐0.3 ‐0.4

2003 0.3 0.6 0.1 ‐0.2 0.1 0.0 ‐0.3 ‐0.3

2004 0.5 0.3 ‐0.1 ‐0.2 0.2 ‐0.1 ‐0.2 ‐0.4

2005 0.3 0.2 0.0 ‐0.1 0.1 0.0 0.0 ‐0.2

2006 0.4 0.2 0.2 ‐0.2 0.1 ‐0.1 0.5 ‐0.2

2007 0.3 0.0 0.2 ‐0.1 ‐0.2 0.0 0.6 ‐0.2

2008 0.0 0.0 0.2 ‐0.1 0.0 0.0 0.3 ‐0.4

2009 0.4 0.4 0.1 ‐0.3 0.1 0.1 0.7 ‐0.5

2010 0.4 ‐0.1 0.2 ‐0.1 ‐0.1 0.1 0.4 ‐0.4

I    = IsolatedS   = ScatteredF   = Fairly Wide spreadW = Wide spread

W  = WeakN   = NormalA  = ActiveV  = Vigorous

Crop Phenology

Western Ghats

Conclusions

I. NDVI showed an increasing trend with high interannual variability overWestern Ghats

II. NDVI, Rainfall correlation is poor in the cases of accumulation and one‐twomonth lags.

III. NDVI, Antecedent Precipitation Index (API) are in good agreementthroughout the monsoon which is evidenced by correlation as well as byMorlett Wavelet Analysis

IV. NDVI maintained good correlation with no of LR and MR alternatively butnot with no of HR days.

V. The relation of NDVI with Isolated, Scattered distributions and active monsoons is substantial.

VI. The graph of phenological stages inferred that Rate of Green Up started in 1st Week of August over Western Ghats

Acknowledgements

• This work is partly supported by DST FASTTRACK YoungScientist Scheme.

• Thanks to Karnataka State Natural Disaster MonitoringCentre (KSNDMC), Bangalore for supplying Rainfalldata.

• Thanks to Prof. D. John Thiruvadigal, Head, Dept ofPhysics.

• Thanks to Prof. D. Narayana Rao, Director – Research,SRM University

Thank you for your patience