The Central Element can be used to calculate the centermost feature of a point, line, or area feature.
Principles of analysis
During the analysis, the cumulative distance between each feature centroid and other feature centroids is calculated, and the feature with the smallest cumulative distance is the most central feature. If a Weight Field is specified, the Central Element is the element with the smallest cumulative distance after weighting.
Application case
- If you want to build a new large-scale sports venue in the urban area, you can find the Central Element from all the blocks, and calculate it according to the population weight, then you can get the location with the lowest traffic cost from all other blocks as the candidate address.
- A supermarket chain has several warehouses in the city. Now there is a batch of materials that have just arrived and need to be distributed to each warehouse. In order to save transportation costs, find out the central warehouse and distribute the materials according to Shortest Path.
Function entrance
- Spatial Statistical Analysis tab-> Measuring Geographic Distributions-> Central Element. （iDesktopX）
- Toolbox-> Spatial Statistical Analysis-> Measuring Geographic Distributions-> Central Element. （iDesktopX）
Main parameters
- Source Data: Set the Vector Dataset to be analyzed, which supports three types of Dataset: point, line and surface. If it is a line or a face, the centroid of the object is taken for calculation, the weight of the point is 1, the weight of the line is the length of the line, and the weight of the face is the area.
- Group Field: a field for classifying analysis elements. After classification, each group of objects will have a Central Element. Group Field can be integer, date or character. If the field value in the Group Field is blank, the element is excluded from the analysis.
- Weight Field: calculate the distance from each element to other elements and weight them. The distance after setting Weight Field is D = W1 X d, where W1 is the weight value and d is the distance between two elements.
- Self Weight Field: refers to the self cost of the element to other elements. After the self weight is set, the distance is D = W1 X d + W2, where W1 is the weight value, d is the distance between two elements, and W2 is the self weight value.
- Measure Distance Method: The Measure Distance method uses Euclidean distance and Manhattan distance. Detail Description for Euclidean Distance and Manhattan Distance. Refer to the Basic Vocabulary of Spatial Statistical Analysis .
- Mean Center: Set Reserved Fields of Result Data and Statistics Type of field value in the field list box.
- Result Settings: Set the Datasource and Dataset Name where the Result Data will be saved.
The blue dots in the figure below are the distribution locations of chain supermarkets. According to different types of chain supermarkets, you need to select the central warehouse location of each chain supermarket, that is, the cumulative Min Distance from the central warehouse to all supermarkets. The red point is the central warehouse of each chain supermarket. This point is the Min Distance of the central warehouse transportation, and the cost is the least.
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