Data Driven Analysis of Algal Bloom Activity for Effective Water Sustainability

2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom)(2016)

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摘要
In this paper, we study an important issue of water sustainability viz harmful algal blooms (HABs). Algal blooms produce toxins that has serious impacts on all forms of acquatic, animal and human health. In a recent public report, the National Wildlife Federation noted that HABs are becoming increasingly common across the U.S, with 21 states reporting blooms at 147 locations between May and September 2013. In this research, we focus on studying the environmental and human activity factors that influences the growth of algal blooms. We detail the process to extract Chlorophyll-a concentration (a proxy for HABs) and important physical parameters which help in the growth of HABs viz Land Usage Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), Palmer Drought Severity Index (PDSI) data for 35 lakes in Georgia, USA. We also derive the lakes which have same behavior with respect to Chlorophyll-a concentration. Our study suggests that the drought has strong correlation with algal bloom.
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关键词
water sustainability,algal bloom
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