Variability in Normalized Difference Vegetation Index (NDVI) in relation to south west monsoon, western ghats,

T.V. Lakshmi Kumar, R. Uma, Humberto Barbosa & K. Koteswara Rao Atmospheric Science Research Laboratory, Dept of Physics Faculty of Engineering & Technology SRM University

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

• 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. 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 Index to study the ground vegetal cover.

• The Normalized Difference Vegetation Index (NDVI) is used to measure and monitor plant growth , vegetation cover and biomass production 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 visible light that hits it, and reflects a large portion of the nearinfrared light.

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

• NDVI valves from ‐1 to +1. NDVI < 0 ‐‐‐ Water Bodies 0 < NDVI < 0.2 ‐‐‐ Less Vegetation 0.2 < NDVI < 0.4 ‐‐‐ Medium Vegetation 0.4 < NDVI < 0.8 ‐‐‐ High Vegetation NDVI > 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

NON – MODIS DATA STATISTICAL AGRICULTURAL DOWNLOADING EXTRACTION AREA MASKING

GEOMETRIC NDVI MAP NDVI CORRECTION GENERATION CALCULATION

CLOUD RESAMPLING MASKING Study Area

Western Ghats ‐ Test sites

•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% Name of Test site Latitude (N) Longitude(E) Madikeri 12.42 75.73 Somwarpet 12.59 75.84 Virajpet 12.20 75.80 Bantwal 12.89 75.03 12.91 74.85 Puttur 12.75 75.19 Sulya 12.55 75.38 13.21 75.00 13.33 74.76 17.46 78.35 Haliyal 15.32 74.75 Honnavar 14.28 74.45 14.81 74.13 Kumta 14.42 74.41 Supa 15.16 74.30 Yellapur 14.96 74.70 No of Rain Rainfall Events Amount

Vegetation (NDVI)

Monsoon Monsoon Distribution Activity Antecedent Precipitation Index (API)

API (j) = API (j‐1)*C + Pt

Where . j ‐ current week . j‐1 ‐ previous week t . C = (Pt/Po) Where th • Pt ‐ t week rainfall

• Po ‐initial rainfall 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 the normal. At least two places should get rain above 30mm rainfall 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. Interannual Variability of NDVI 15 18 g) Sulya - DK o)Yellapur - UK 12 15 l) Honnavar - UK 15 9 12 12 6 9 9 3 6 6 0 3 3 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 0 -3 Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Anomaly -6 -3 Anomaly

Anomaly -3 Year Year -6 -9 -6

-9 -12 -9 -12 -15 -12 -15 -18 -15

12 12 m) Karwar - UK h) Karkala - Udupi 9 b) Somwarpet - Kodagu 9 9 6 6 6 3 3 3 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 -3 0 Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 -6 -3 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Anomaly Anomaly Year

-9 Anomaly -3 Year -6 -12 -6 -15 -9 -18 -12 -9

12 j) Kundapur - Udupi 12 9 a) Madikeri - Kodagu 9 9 e) Mangalore - DK 6 6 6 3 3 0 3 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 0 -3 Year 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Anomaly -3

-6 Anomaly Year

-3 Year Anomaly -6 -9 -6 -9 -12

-15 -9 -12 WESTERN GHATS AS WHOLE

10

5

0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Anomaly -5

-10

SLOPE = 0.71 Monthly NDVI vs Rainfall Rainfall Anomalies

Rainfall Anomaly Year June July August September October

2000 26 ‐26 ‐10 ‐25 ‐7 2001 28 ‐12 ‐50 ‐63 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 ‐825 ‐27 51 24 2010 ‐14 3 ‐33 55 57 Weekly Mean NDVI vs API Year Correlation (API & 3000 0.600 NDVI) 2001 0.24 2500 0.500 2002 0.40 2000 0.400 NDVI 2003 0.89 1500 0.300 API 2004 0.25 1000 0.200 2005 0.54 500 0.100 2006 0.51 0 0.000 2007 0.52 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 2008 0.22 Week 2009 0.24 API NDVI Wkly Mean 2010 0.53 Mean of Weaky 0.48 NDVI & RF(API) NDVI vs %of Light, Moderate and Heavy Rainy Events Year No. Of Rain Events Monsoon Distribution Monsoon Activity NDVI LR MR HR I S FWS WS MW MN MA MV

2000 0.319 17 40 26 23 15 18 66 49 45 7 21 2001 0.270 20 42 24 23 7 18 74 49 55 3 14 2002 0.348 20 40 16 26 10 27 59 66 40 4 11 2003 0.287 21 46 22 17 12 17 76 42 64 4 12 2004 0.341 18 41 22 26 9 22 65 47 62 1 12 2005 0.289 17 44 26 20 13 16 73 39 63 5 15 2006 0.311 16 46 25 23 13 12 74 46 59 3 13 2007 0.235 18 42 34 10 11 25 76 27 68 11 15 2008 0.193 19 39 22 21 22 21 58 63 39 7 13 2009 0.330 20 40 26 16 15 29 62 53 46 4 19 2010 0.356 224826913198144551012 Correlation Test Site LR MR HR Madikeri 0.10 0.11 ‐0.36 Somwarpet ‐0.39 0.41 0.30 Virajpet 0.07 0.05 ‐0.41 Bantwal 0.07 ‐0.04 ‐0.25 Mangalore ‐0.06 ‐0.03 ‐0.02 Puttur 0.38 0.10 ‐0.24 Sulya ‐0.35 0.45 ‐0.62 Karkala ‐0.50 ‐0.03 0.08 Kundhapur ‐0.14 0.28 ‐0.57 Udipi 0.55 0.13 ‐0.34 Haliyal ‐0.14 0.14 ‐0.39 Honnavar 0.70 0.03 ‐0.60 Karwar ‐0.30 0.56 ‐0.18 Kumta ‐0.33 0.56 ‐0.63 Supa 0.30 0.06 0.09 Yellapur ‐0.02 ‐0.18 0.43

LR = Light Rainy Days; MR = Moderate Rainy Days & HR = Heavy Rainy Days Monsoon Activity 60 50 40 30

20 10 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 MW MN MA MV Monsoon Distribution 70

Percentage(%) 60 50 40 Correlation 30 20 YEAR 10 Monsoon Distribution Monsoon Activity 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 IS F W W N A V I S FWS WS Year 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 I = Isolated 2003 0.3 0.6 0.1 ‐0.2 0.1 0.0 ‐0.3 ‐0.3 S = Scattered 2004 0.5 0.3 ‐0.1 ‐0.2 0.2 ‐0.1 ‐0.2 ‐0.4 F = Fairly Wide spread 2005 0.3 0.2 0.0 ‐0.1 0.1 0.0 0.0 ‐0.2 W = Wide spread 2006 0.4 0.2 0.2 ‐0.2 0.1 ‐0.1 0.5 ‐0.2 W = Weak 2007 0.3 0.0 0.2 ‐0.1 ‐0.2 0.0 0.6 ‐0.2 N = Normal 2008 0.0 0.0 0.2 ‐0.1 0.0 0.0 0.3 ‐0.4 A = Active 2009 0.4 0.4 0.1 ‐0.3 0.1 0.1 0.7 ‐0.5 V = Vigorous 2010 0.4 ‐0.1 0.2 ‐0.1 ‐0.1 0.1 0.4 ‐0.4 Crop Phenology Western Ghats Conclusions

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

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

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

IV. NDVI maintained good correlation with no of LR and MR alternatively but not 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 Young Scientist Scheme. • Thanks to State Natural Disaster Monitoring Centre (KSNDMC), Bangalore for supplying Rainfall data. • Thanks to Prof. D. John Thiruvadigal, Head, Dept of Physics. • Thanks to Prof. D. Narayana Rao, Director – Research, SRM University Thank you for your patience