An Evaluation of Various Vegetation Indexes for Predicting Wild Blueberry Yield

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Wagner Forest NS Ltd. is a forest management company with a core commitment to the practice of sustainable forestry. Wagner manages approximately 500,000 acres of forest land in Nova Scotia and 845,000 acres in Ontario. For the past seven years, Wagner has been investing both time and money into developing cutover forest land into blueberry fields. The company will have approximately 1000 acres developed by the end of 2019. Wagner would like to collaborate with NSCC's Centre of Geographic Sciences (COGS) Applied Research team to investigate the feasibility of utilizing remote sensing and spatial analytics to monitor plant health and predict wild blueberry yields.Several UAV surveys will be conducted during the growing season using a multispectral sensor. From this imagery, various vegetation indices will be calculated to assist with measuring plant health. Following the harvest the various vegetation indices will be correleated with the blueberry harvest to determine the best index for predicting harvest yield.The Applied Research team at COGS will lead the project, assist in survey design and methodology, conduct aerial image collection, and perform post processing of images. The goal of the project is to determine the best vegetation index and the optimal time to collect imagery to best predict wild blueberry yield.