Index-insurance is becoming increasingly popular because of its ability to provide low-cost, relatively easy to implement agricultural insurance for vegetation types whose productivity has been notoriously difficult to measure and to farmers in less-developed nations where traditional crop insurance schemes are not reasonable to implement. This study examines if the remotely sensed Normalized Difference Vegetation Index (NDVI) can be an effective basis for index-based crop insurance over a diverse set of locations. To do this I compare AVHRR-NDVI values to cumulative precipitation, extreme heat, and crop yields for sixty locations across the United States for the years 1982-2003. I use simple OLS quadratic equations to explore these relationships. My findings suggest that the relationship between NDVI, precipitation, extreme heat, and crop yields is highly variable and dependent on location-specific characteristics. Without site-specific calibration, NDVI should not be widely applied to index-based insurance product design. However, NDVI may still be a useful tool in insurance design under certain circumstances. Further research is needed to better characterize the factors affecting NDVI values and their relationships to crop yield.