The best example of environmental big data is that of weather forecasting, as discussed in the video on futurelearn. The use of drones to monitor and measure atmospheric pollutants is another form of environmental big data. This can all be used to reduce carbon footprint by making use of the data to reduce or introduce more efficient transport in areas with high levels of pollution.
As with all things there will always come limitations to data analysis due to the fact that it is created by humans and is subsequently subject to human error. Some of the limitations that you may come across would be that the data may be incomplete, whether it be missing values, or lack of a section of necessary data. This could severely limit the data's usability. Survey data can also be scrutinised due to the human component. People do not always provide accurate information through surveys and many are likely to not answer truthfully. For example if a person were asked how much alcohol they consume within a week they are likely to say less than their actual intake.
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