Effect of Climate Change on NDVI and Crop Yield Association for Index Insurance Askar Choudhury, James Jones, John Kostelnick, Frank Danquah, Raquiba (Lena) Choudhury, Aslihan Spaulding Illinois State University, USA Presented at the Western Risk and Insurance Association Annual Meeting Maui, Hawaii January 5, 2016

Objectives: Establish associations between index and crop yield through associative modeling taking into account variations in climatic factors. Purpose: Develop index insurance using NDVI

Need for Protecting Farmers Drought can destroy crops Climate change is making droughts more frequent Farmers have difficulty getting loans without insurance

How Do We Help Farmers? Index Insurance may be a viable alternative to traditional insurance, specifically for developing countries

Index Insurance Payout occurs when pre-specified trigger is activated Implementation is faster and simpler Reduces administrative and other costs. Reduces moral hazard associated with traditional insurance

Data: 2011 and 2012 Crop (Corn) yield (bushels per acre) data were obtained from Soy Capital in McLean county, Illinois Normalized Difference Vegetation Index (NDVI) data were obtained using MODIS satellite system 2011: Normal year for crop yield (average yield year) 2012: Drought year for crop yield (poor yield year)

Fields selected from McLean County

What is NDVI? Normalized Difference Vegetation Index (NDVI) is an index of plant “greenness”. It measures the density of green vegetation. Calculated from the red and near infrared (NIR) bands of remotely sensed satellite imagery Useful to study vegetation dynamics or plant phenological changes over time.

NDVI derived from MODIS satellite imagery for two different dates

Table1: Correlation of NDVI and Yield Year NDVI May_9 NDVI May_25 NDVI Jun_10 NDVI Jun_26 NDVI Jul_12 NDVI Jul_28 NDVI Aug_13 NDVI Aug_29 2011 0.2610 0.5419 0.5326 0.17464 0.43174 0.51263 0.64429 0.6739 2012 -0.03161 0.48644 0.53129 0.60138 0.86156 0.83643 0.82317 0.69939

Table2: Average NDVI and Yield Year NDVI May_9 NDVI May_25 NDVI Jun_10 NDVI Jun_26 NDVI Jul_12 NDVI Jul_28 NDVI Aug_13 NDVI Aug_29 Yield 2011 3387.5 3719.33 6222.9 8586.11 8635.34 8940.99 8345.57 7869.04 182.95 2012 3783.02 5952.96 7601.7 7950.31 7969.45 7674.24 7367.54 7078.61 116.62

NDVI and Climate factor We investigated further to see if broader climatic factor such as, Sea Surface Temperature (SST) shows any lag effect on NDVI

SST, Precipitation, and NDVI Sea surface temperature (SST) variations is likely associated with deviations in precipitation One of the major weather factor that have impact on NDVI is precipitation Therefore, variations in NDVI is likely due to global atmospheric and sea surface temperature (SST) change

Fig1: SST Plot: February – May

Fig2: SST Plot: May - August

Fig3: Average NDVI Plot: May – August

Climate Change One of the environmental anomalies that influence SST variations is El Niño El Niño is a naturally occurring phenomenon that influences SST and the wind pattern

Climate Change El Niño episodes varies in their intensities and are labeled as normal/moderate and extreme/super During normal El Niño episode, the usual average rise of SST of the tropical Pacific Ocean is 0.5 °C During an extreme El Niño episode, the average rise of SST is 0.9 °C

Climate Change Monthly Mean SST During a Normal El Niño Year Monthly Mean SST During a Super El Niño Year

High and Dry: How the 2012 Drought Affected Illinois Agriculture Transportation was jeopardized when Mississippi River dropped significantly Livestock producers were impacted

Associative model We develop associative model for index insurance using NDVI and incorporate differential climate effect.  

TABLE 3: Model’s results of NDVI on Yield Variable DF Parameter Estimate Standard Error t Value Pr > |t| Intercept 1 -415.72304 35.83087 -11.60 <.0001 Climate-Effect (year-dummy) -63.13275 8.32869 -7.58 May_25 0.01370 0.00261 5.24 Jun_10 0.01107 0.00301 3.68 0.0004 Jul_12 0.02043 0.00665 3.07 0.0028 Aug_13 0.03624 0.00519 6.98 R-Square 0.8899

Insurance Payment Structure

CONCLUSIONS:   We observe that climate change impacts NDVI and thus crop yield Proper modeling of association of crop yield can provide feasible index insurance

Thank You!