Source of this article: Public Account of GIS Research Laboratory
1
data to introduce
The data used in this tutorial are: point coordinates of each community (source Fangtianxia, coordinates are CGCS2000); POI coordinates of basic education facilities, commercial service facilities, financial insurance facilities, medical and health facilities (source Amap, coordinates are CGCS2000 )
2
buffer generation
First generate a 1KM buffer map of each small point, the specific operation method is: load the small point data - open ArcToolbox - analysis tool - buffer
figure 1
In the "Input Features" we choose the point data of house prices, and the "Output Feature Class" chooses the output location of our buffer data. Enter 1000 meters under Linear Units. "Method" select PLANAR (this method has the effect that if the input features are in a projected coordinate system, a Euclidean buffer will be created. If the input features are in a geographic coordinate system and the buffer distances are in linear units (meters, feet etc., rather than angular units such as degrees), a geodesic buffer is created). "Fusion type" selects NONE (this method does not consider overlap, and maintains an independent buffer for each element)
figure 2
After clicking OK, the buffer map of each point can be generated (although it is a bit messy, but we are not looking at the picture, but to count the number of points in the buffer zone, so let’s just do it!)
image 3
In the next step, load the POI point data you need to count to the layer ( WARN: students with intensive phobia, get out of the way! )
Figure 4
3
Spatial join of point data
This step is very critical, everyone listen carefully! First, right-click the buffer layer just generated - connection and association - connection.
Figure 5
Then select "Data of another layer based on spatial location", and then select the type of point you need to count, here is "Medical and Sanitation Facilities". In addition, in "How to summarize attributes", there are average value, minimum value, standard deviation, sum, maximum value and variance to choose from, that is to say, the average value, minimum value and standard value of each attribute of all points in each buffer can be calculated. Difference, sum, maximum value, and variance ( provided that this attribute is a numeric type and cannot be a string , I don’t need to check it here), and finally select the output location of the new layer.
Figure 6
Open the attribute table of the generated data, and you can see a Count field, which is the number of interest points in each buffer.
Figure 7
Tree Valley Database Resource Encyclopedia (updated on May 29)