Generating Heat Maps in Simple GIS Client, Desktop GIS Software
Heat Maps provide a way to geographically visualize the concentration or densities of events across an area. Heat maps can be a useful tool to visualize or analyze concentration of events such as crime activity, population, or measurements. Simple GIS generates heat maps by taking an input point or polygon shape file and interpolating the data to a continuous surface. In the case of Simple GIS, this surface is represented as a raster Tiff file. To generate the surface, Simple GIS considers three different parameters. The first parameter is the individual cell sizes in the raster. The raster surface will be made up of square cells of a given width and height. The smaller these cell sizes the smoother the resulting surface but the slower the processing time. Therefore, there is a trade off as to the resolution of the surface versus processing time. The second parameter is the search radius. This determines the area of influence assigned to each point. The greater the search radius, the more generalized the density patterns will be on the resulting surface. The smaller the search radius the density patterns may become too restricted to interpret significant patterns. The third parameter involves the type of calculation to use to interpret cell values. There are two distinct ways Simple GIS interpolates this data. The first is to use a kernel density function which uses a quartic probability density function to calculate the density distribution across the surface. The kernel density function is best for data that may not exist across the entire surface. For example, population data. There would likely be areas across your surface where it may be reasonable and likely to have no population. Areas covered by seas, deserts, or other uninhabitable areas for instance. The second calculation Simple GIS can use is the inverse distance weighted function. This method is best for data or measurements you would expect to find across the entire surface. Temperature data for instance would be a good example as every area covered by the surface would have a temperature value. This video tutorial will demonstrate creating heatmaps using both methods. For more information, please visit https://simplegissoftware.com/simple-....