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Lindorm:Spatio-temporal raster

Last Updated:Sep 02, 2022

What is a spatio-temporal raster?

A raster is a grid that consists of a matrix of cells (or pixels) that are organized into rows and columns. Each cell contains attribute values that represent the information about the area within the cell. These values are also known as raster data.

Raster data can be classified into two types: thematic data and image data.
  • Thematic data: The value of each cell represents a measurement or a classification to describe the information, such as the pollutant concentration, rainfall, land ownership types, or vegetation types.

  • Image data: Image data is also called remote sensing image. It refers to a film or an image taken by using ground remote sensing, aerial remote sensing, or aerospace remote sensing technologies to record the electromagnetic wave size of various ground objects. Image data includes both aerial images and remote sensing satellite images.

A raster is also called a spatio-temporal raster because raster data contains both spatial and temporal attributes. In terms of time, spatio-temporal raster data can also be used to manage time series.

Spatio-temporal raster solution of Lindorm and DLA Ganos

Lindorm allows you to store and retrieve spatio-temporal raster data. Lindorm can be used with Data Lake Analytics (DLA) Ganos to provide a complete solution of processing spatio-temporal raster data in a large number of complex scenarios such as spatio-temporal raster computing.

For more information, see Terms.