This weeks lab we learned how to do Spatial Statics within ArcMap. Spatial Statics is useful in determining how to analyze your data for certain outcomes for using and displaying data. We created a map of weather monitoring stations for Western Europe and applied spatial statistical tools to see how the data is distributed.
We used a training module from ESRI's online classrooms. We downloaded data from the module and applied a method of spatial analysis as seen in my map above. We used an mxd file, contained within the training module data, which had an ESRI topo base map saved and centered mainly on Western Europe. There was also a layer for weather monitoring stations, containing a record of temperature and other weather data for a each station.
Next we needed to visually understand how our data is spatial distributed. The first step in spatial analysis is find the middle or the center of the data. There are two methods we used in locating the center, both of which can differ locations depending on the spatial quality of the data. The first method is the Mean Center which represents the average x and y coordinates of all values. The second method is the Median Center which takes the middle value of the data when it's ordered by rank. ArcMap has separate tools that do find the median and mean center and we located the tool by simply searching for it. The tools are very similar and we kept defaults the same to calculated the mean and median center. The red and green dots in the center of the map above is my median a mean center.
Now that we have the center located, we calculated the directional distribution of the data in order see in which direction the data is spatially located. We did this by using a tool found in the Spatial Statistics toolbox, then expanded the Measuring Geographic Distributions tool set and the tool name is called the Directional Distribution (Standard Deviational Ellipse) tool. Using the Temperatures layer, this tool creates an Ellipse. This tells us the general orientation of our data. So in the map above you can most of our data is concentrated in an east/west direction.
Having done these first steps in visually understanding how our data is spatially located you can start to understand where features are arranged within the map. Now you can start to run other spatial analysis tools such as a Histogram, QQPlot or a Voronoi Map. But the fist step in understanding spatial analysis is to visually look at how the data is arranged and then start to ask questions or run analysis on the data.
We used a training module from ESRI's online classrooms. We downloaded data from the module and applied a method of spatial analysis as seen in my map above. We used an mxd file, contained within the training module data, which had an ESRI topo base map saved and centered mainly on Western Europe. There was also a layer for weather monitoring stations, containing a record of temperature and other weather data for a each station.
Next we needed to visually understand how our data is spatial distributed. The first step in spatial analysis is find the middle or the center of the data. There are two methods we used in locating the center, both of which can differ locations depending on the spatial quality of the data. The first method is the Mean Center which represents the average x and y coordinates of all values. The second method is the Median Center which takes the middle value of the data when it's ordered by rank. ArcMap has separate tools that do find the median and mean center and we located the tool by simply searching for it. The tools are very similar and we kept defaults the same to calculated the mean and median center. The red and green dots in the center of the map above is my median a mean center.
Now that we have the center located, we calculated the directional distribution of the data in order see in which direction the data is spatially located. We did this by using a tool found in the Spatial Statistics toolbox, then expanded the Measuring Geographic Distributions tool set and the tool name is called the Directional Distribution (Standard Deviational Ellipse) tool. Using the Temperatures layer, this tool creates an Ellipse. This tells us the general orientation of our data. So in the map above you can most of our data is concentrated in an east/west direction.
Having done these first steps in visually understanding how our data is spatially located you can start to understand where features are arranged within the map. Now you can start to run other spatial analysis tools such as a Histogram, QQPlot or a Voronoi Map. But the fist step in understanding spatial analysis is to visually look at how the data is arranged and then start to ask questions or run analysis on the data.
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