MindMap Gallery Data structure of geographic information system
Data structure mind map of geographic information system: including the first section of geographical space and its expression, the second section of geographical spatial data and its characteristics, the third section of types of spatial data structures, the fourth section of the establishment of spatial data structures, etc.
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The ice hockey schedule for the Milano Cortina 2026 Winter Olympics, featuring preliminary rounds, quarterfinals, and medal matches for both men's and women's tournaments from February 5–22. All game times are listed in Eastern Standard Time (EST).
This Valentine's Day brand marketing handbook provides businesses with five practical models, covering everything from creating offline experiences to driving online engagement. Whether you're a shopping mall, restaurant, or online brand, you'll find a suitable strategy: each model includes clear objectives and industry-specific guidelines, helping brands transform traffic into real sales and lasting emotional connections during this romantic season.
This Valentine's Day map illustrates love through 30 romantic possibilities, from the vintage charm of "handwritten love letters" to the urban landscape of "rooftop sunsets," from the tactile experience of a "pottery workshop" to the leisurely moments of "wine tasting at a vineyard"—offering a unique sense of occasion for every couple. Whether it's cozy, experiential, or luxurious, love always finds the most fitting expression. May you all find the perfect atmosphere for your love story.
The ice hockey schedule for the Milano Cortina 2026 Winter Olympics, featuring preliminary rounds, quarterfinals, and medal matches for both men's and women's tournaments from February 5–22. All game times are listed in Eastern Standard Time (EST).
Chapter 2 Data Structure of Geographic Information System
Section 1 Geographical space and its expression
1.1 Concept
The geographical space covers a wide range from the ionosphere of the atmosphere to the Moho surface of the mantle. But generally geographical space refers to the surface of the earth, and its benchmarks are the land surface and the ocean surface. It is an area where human activities occur frequently, and it is an area where the relationship between man and earth is the most complex and close.
1.2 Positioning framework
Geodetic control system, namely plane control network and elevation control network
1.3 Expression of spatial entities
Spatial entities refer to the smallest abstract unit of geographical entities in the real world, mainly including three types: points, lines and surfaces.
Section 2 Geospatial Data and Its Characteristics
2.1 Definition of spatial data
Data describing the location, shape, size, distribution and other information of geographical elements and geographical phenomena, including spatial location, topological relationships and attributes.
2.2 Basic characteristics of spatial data
① Spatial features: represent the spatial position of entities or the spatial relationships between entities. Spatial positions are generally represented by coordinate data, called positioning features or positioning data; spatial relationships are called topological features or topological data.
②Attribute characteristics: Represents the characteristics of entities. Such as name, classification, qualitative characteristics and quantitative characteristics, etc.
③Time characteristics: Describe the changes of entities over time. The cycles of changes include ultra-short period, short-term, medium-term and long-term.
2.3 Types of spatial data
1. Classification according to the geometric characteristics of the data: points, lines, surfaces, surfaces, and volumes
2. Classify according to the content of the display - corresponding to the basic information
1) Attribute data
2) Geometric data
3) Relational data
3. Classification by representation object (basis of coding): (1) Type data (2) Area data (3) Network data (4) Sample data (5) Surface data (6) Text data (7) Symbol data
4. According to data source: map data, image data, text data.
5. According to data structure: vector data, raster data.
6. According to data characteristics: spatial data, non-spatial attribute data.
7. According to the data release format: digital line drawing (DLG), digital raster map (DRG), digital elevation model (DEM), digital orthophoto map (DOM).
2.4 Topological relationship of spatial data
(1) Topological adjacency: refers to the topological relationship between elements of the same type that exist in spatial graphics
(2) Topological association: refers to the topological relationship that exists between different types of space elements
(3) Topological inclusion: refers to the topological relationship between elements of the same type but different levels that exist in spatial graphics
2.5 Computer representation method of spatial data
1) Spatial framing
2) Attribute layering
3) Time segmentation
Section 4 Establishment of Spatial Data Structure
4.1 Relationship between system functions and data
Determine data projects based on user needs
4.2 Data classification
1. Classification of attribute data
2. Classification of spatial data
4.3 Data encoding
1. Concept: Coding is to artificially establish a combination of numbers or symbols to communicate between people and computers and to express a specific thing.
2. Code bits, code segments and their relationship with coding: Code bit is the smallest unit of encoding, and code segment is the basic unit of encoding.
3. Encoding content
Registration part (identification code)
Classification part (classification code)
Control section
4. Encoding method
1) Hierarchical classification coding method
2)Multi-source classification coding method
5. The following principles must be followed when formulating codes:
(1) Systematic and scientific (2) Uniqueness (3) Standardization (4) Simplicity 4-7 bytes (5) Applicability (6) Extensibility
Section 3 Types of Spatial Data Structures
3.1 Raster data structure
Concept: Raster data structure is the simplest and most direct spatial data structure. It refers to dividing space into grid arrays of uniform size and close adjacent. Each grid gives corresponding attribute values to represent geographical entities. Data organization form.
2) Features
①The position is implicit and the attributes are obvious
②Discrete quantized raster values represent spatial objects
③The data structure is simple and easy to combine with remote sensing data
④Geometric and attribute deviations
3) Value method
Percentage method, importance method, center point method, area dominance method, length dominance method
4) Encoding method
① Direct raster coding: record code data row by row (or column by column)
Features: Easy handling, but no compression
②Compression encoding
a. Run length encoding
b. Block coding
c. Quadtree encoding
d.Chain code
3.2 Vector data structure
1) Concept
The vector data structure is a data organization method that uses points, lines, surfaces and their combinations in Euclidean geometry to represent the spatial distribution of geographical entities by recording coordinates.
2) Features
①Obvious positioning and implicit attributes
② Use discrete points to describe spatial objects and features
③Have topological relationships of spatial entities to facilitate in-depth analysis
④High data accuracy and low redundancy
⑤ Difficult to combine with image data such as remote sensing
3) Data acquisition
Obtained from field measurements
Obtained from raster data conversion
Obtained by trace digitization/scan vectorization
4) The two most basic structures
simple data structure
topological data structure
subtopic
3.3 Vector-gate comparison and vector-gate integrated data structure
Comparison of advantages and disadvantages
Raster data structure: small data volume, high graphics accuracy, complex and efficient graphics operations, inconsistent remote sensing image formats, expensive output representation abstraction, difficult data sharing, and easy implementation of topology and network analysis
Vector data structure: large amount of data, low graphics accuracy, simple and inefficient graphics operations, close or consistent remote sensing image formats, intuitive and cheap output representation, easy data sharing, and difficult to implement topology and network analysis
Selection of vector and raster data structures
In general: the data collection stage uses vector data format, and the spatial analysis stage mainly uses raster data format.