Scale is a very important component of studies in physical geography. Data is usually collected from sample areas or study areas. During analysis the data is extrapolated over the entire study area using some statistical analysis. This is scaling up of the data. The point data is blown out and used to represent a larger area.
Since the original data is usually point data; X and Y coordinates it is very important to know exactly where that point is located. This is achieved through the use of GIS software. The display of point data in the GIS software enables the observer or the analyst to make better assumptions, interpretations and conclusions of the data. For example, if one is looking at fire occurrences in a particular area it would be interesting to overlay the fire data with roads, rivers and settlements to see how they are related.
One of the most useful tools of data visualization is time series analysis. This technique enables us to follow a particular event over a long period. In so doing one can investigate the many reasons why that event is happening. The following are some of the events that can be investigated using the time series analysis.
Fire frequency outbreaks
Floods occurrences
Land cover/land use change
By overlaying different types of related datasets for different time events can help in understanding the causes of such events. For example; fire data time analysis may show that fire outbreaks are common in winter, and occur mostly near settlements. With this kind of information it would be easier to come up wit early warning system, and be prepared in advance before the fire seasons.
Similarly the same thing applies to the land cover/land use changes. Time series analysis is the best tool to show how the changes have occurred.
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