Spatial Data: Definition and Types

Spatial data, also known as geospatial data, has become a crucial component in many industries. It helps businesses gain insights into geographic context, identify patterns, and understand relationships between different factors. With spatial data, industries can explore opportunities related to location, track climate change, monitor the spread of diseases, and much more.

In this article, we’ll take a deep dive into spatial data, covering everything from its definition to the different types.

What is Data Spatial?

Spatial data refers to information that captures the details of specific geographic locations and characteristics on the Earth’s surface. This data includes location coordinates, regional boundaries, and other geographic patterns that describe a particular area.

Typically, GIS spatial data is represented using a Cartesian coordinate system (x, y) on a two-dimensional map, although it can also include altitude (z) in three-dimensional maps in some cases.

Geospatial data can be visualized using different geometric shapes. For instance, lines are used to represent linear features like roads or rivers, polygons show boundaries such as land use zones or administrative borders, and points mark specific locations like GPS coordinates. Additionally, geospatial data can also be displayed in a grid format.

Spatial data is collected through various methods, including satellite imagery, GPS surveys, or even manual surveys, where locations are traced and visited directly.

By analyzing spatial data, businesses can gain a deeper understanding of how geographic factors influence communities, populations, and individuals in a given area. For example, spatial data can help identify population distribution patterns and assess access to services like transportation or public facilities.

Types of Spatial Data 

Spatial data is categorized into four main types: vector data, raster data, attribute data, and temporal data. Here’s an explanation of each type:

Vector Data 

Vector data is used to describe specific geographic features through points, lines, and polygons.

• Point: A point is the simplest form of vector data. It represents a specific location identified by a single pair of coordinates (usually in x and y format). Examples include ATM locations or earthquake epicenters.
• Line: Lines represent linear geographic features like roads or rivers. They are defined by two or more connected points, where each point along the line marks a position along the path.
• Polygon: A polygon is a geometric shape formed by lines surrounding an area. It is typically used to describe areas with clear boundaries, such as buildings, lakes, neighborhoods, or commercial zones.

Common file formats for vector data include GeoJSON, GML, KML, and Shapefiles (.shp).

Raster Data

Raster data is a type of spatial data represented in pixels, where each pixel holds information about a specific geographic area, such as altitude or temperature. Raster data is particularly useful for analyzing continuous changes across space, like mapping weather patterns.

There are several types of raster data, each serving different purposes for analysis and mapping. Here are some commonly used ones:

• Digital Elevation Model (DEM): DEM data is used to represent the height of the Earth’s surface or the depth of oceans. It’s essential for topographic analysis 
• Satellite Imagery: Satellite images are effective for land mapping, tracking environmental changes, and analyzing natural disasters like wildfires or floods. These images provide a clear picture of the Earth’s surface.
• Temperature Mapping: This type of raster data is used to track temperature changes, model climate patterns, and predict weather. It helps in understanding global and local temperature shifts and forecasting extreme weather events.
• Land Use Mapping: Land use mapping divides a region into cells, with each cell representing a specific land use type, such as agriculture, forests, or urban areas. This data is crucial for spatial planning, managing natural resources, and assessing environmental impacts.

Each type of raster data is used based on the specific analysis requirements and the goals of mapping.

Attribute Data 

Attribute data provides additional details that describe the characteristics of spatial features. 

For example, in vector data, a point may represent the location of a school. The attribute data for this point might include key information such as the school’s name, the number of students, and the grade levels it offers (e.g., elementary, middle, high school, or university).

Temporal Data 

Temporal data refers to spatial data that is associated with time—either a specific timestamp or a range of time.

For instance, satellite imagery often includes a timestamp showing when the image was captured. This allows us to track changes in the Earth’s surface, such as shifts in land cover or the effects of natural disasters, over time. Another example is GPS tracking, which records the movements of vehicles or individuals at specific locations.

Get Accurate and Complete Spatial Data from LOKASI Intelligence

LOKASI Intelligence is a geospatial analysis platform that integrates location intelligence technology. With LOKASI, businesses can identify and optimize potential business locations. It comes with comprehensive location data, including demographics, socio-economic status, disaster data, Point of Interest (POI) data, foot traffic, and more.

Additionally, LOKASI allows businesses to visualize this data, making it easier to spot patterns, relationships, and insights that can help improve business operations.

To learn more about how LOKASI Intelligence can support your business, get in touch with us via: Email: [email protected]   WhatsApp: 087779077750

FAQs  

What is spatial data?  

Spatial data refers to information that provides details about the location and geographic features of an area on the Earth’s surface. This includes key elements like coordinates, boundaries, natural features, and man-made structures within the area.  

What are the sources of spatial data?  

Spatial data can be sourced from satellite imagery, ground surveys, aerial photography, and other methods of geographic data collection.  

Why is spatial data important? 

Spatial data is crucial because it helps businesses gain a comprehensive understanding of a location. By analyzing geographic aspects like market potential and accessibility, businesses can make informed decisions and optimize their strategies.