Development of an intelligent environmental knowledge recommendation system for sustainable water resource management using modis satellite imagery

With the global availability and accessibility of environmental data sources it is possible to address the water related problems. Locally, in the Australian context, the water industry is in a unique position due to the extremes with a vast experience of drought and flood conditions. Water in Australia is a national priority and there is a need to develop an accurate and timely decision support system regarding efficient and optimal water usage. To address this issue, in this paper, we proposed an integrated environmental knowledge recommendation system based on large scale dynamic web data mining and contextual knowledge integration to provide an expert water resource management solution. We integrated five different environmental data sources namely SILO, AWAP, ASRIS, CosmOz, and MODIS imagery to develop and test the proposed knowledge recommendation framework called intelligent Environmental knowledgebase (i-Ekbase). The developed system was tested for its robustness and applicability.