What are the common methods of spatial data processing?

The common methods of spatial data processing are manual processing, mechanical processing and electronic processing.

The basic purpose of data processing is to extract and derive valuable and meaningful data from a large number of chaotic data.

Detailed introduction:

Data is the expression of facts, concepts or instructions, which can be processed by manual or automatic equipment. After data is interpreted and given a certain meaning, it becomes information. Data processing is the collection, storage, retrieval, processing, conversion and transmission of data.

The basic purpose of data processing is to extract and infer valuable and meaningful data from a large number of data that may be chaotic and difficult to understand.

Data processing is the basic link of system engineering and automatic control. Data processing runs through all fields of social production and social life. The development of data processing technology and the breadth and depth of its application have greatly affected the development of human society.

Spatial data refers to the data used to express the position, shape, size and distribution characteristics of spatial entities. It can be used to describe the goals in the real world, and has the characteristics of localization, qualitative, time-space relationship and so on.

Spatial data has three basic characteristics: spatial characteristics (location), attribute characteristics (non-location) and time characteristics (time scale). In the process of building basic geographic information database, spatial data is always the most basic, important and important part of GIS, and it is also the part with the largest investment.

In GIS, people abstract spatial data, and digital expression can be divided into four categories: digital line drawing data, image data, digital elevation model and ground object attribute data.

Spatial data processing has two meanings: one is to process the original collected data or data that do not meet the quality requirements of GIS to meet the data quality requirements of GIS; The other is to process the data already stored in GIS to obtain other information, such as further spatial relationship information, or to convert one type of data into another.