3D Analyst Tools ArcToolbox

How to distribute the patterns of a set of points and what is the importance of that???

• Geographical phenomena or geographical features and features that make up any layer within ArcGIS programs called Shapefile or Feature Class are represented in three ways

1. polygon and it has an area, meaning that it consists of a group of points representing borders or vertices connected to each other, giving us a polygon shape like the borders of plots of land.
2. Line, which are lines that have lengths and consist of a group of points that are connected and a line appears, such as electricity lines or streets.
3. point that is distinguished by X,Y coordinates, and a set of points can be created under one name, and the point representation is the focus of this article.

Points we use to represent many geographical phenomena and features. A layer of trees can be represented in the form of points or a group of points can be taken that give us the heights of the earth’s surface for a region. We can also convert a layer of a polygon or line type into a set of points.

Therefore, when studying and analyzing a set of points, we have to understand the method of distribution. To understand this method, we conduct an analysis that shows the pattern of distribution of these points, so it is easy for us to discover many things that help us in making any decision or support us when conducting a study or university scientific research.

The spatial distribution pattern of a group of points is a form that gives us or shows us the method of distributing these points. From here,

the method of distribution is divided into three sections:

1. Clustered Distribution, so that the distribution of a set of points is close to each other, for example, a planting area. All trees or plants were represented, surveyed, and then converted into a point layer within ArcGIS programs.
   An analysis of distribution patterns was carried out, and we found that these trees are close to each other There are no odd trees far away.
2. Uniform Distribution, whereby the distribution of a set of points came in a beautiful regular fashion that gives us an indication of an aesthetic landscape that we are interested in, for example, the representation of buildings in a specific geographical area and then transformed into a point layer,
   so that a point layer appears for each point representing a building after conducting an analysis of the distribution patterns It was found that the distances between the buildings are regular,
   and this indicates that the residential neighbourhood is very regular and the residential buildings are similar in size and shape.
3. Random distribution so that the distribution of a set of points randomly is very far from the regular distances between the points. For example, we have a point layer representing the electricity charging stores in a rather large city.
   After conducting an analysis of the distribution patterns, it was found that there is randomness in the distribution of electricity charging stores To the extent that there are some residential neighbourhoods that are far from electricity charging stations and other residential neighbourhoods nearby, as a result, there is no justice in distributing this service in this city.