Raster Data
Raster data is a type of geospatial data structure that represents geographic information as a grid of cells or pixels, where each cell contains a value representing a specific attribute, such as elevation, temperature, or land cover. It is commonly used in geographic information systems (GIS), remote sensing, and image processing to model continuous phenomena like terrain, satellite imagery, and climate data. The structure allows for efficient storage and analysis of spatially continuous variables across large areas.
Developers should learn about raster data when working on projects involving spatial analysis, environmental modeling, or image-based applications, such as mapping services, agricultural monitoring, or disaster response systems. It is essential for tasks like terrain analysis, vegetation indexing, and weather forecasting, where data varies continuously across space. Understanding raster data enables efficient handling of large datasets, such as satellite imagery or digital elevation models, in tools like GDAL, ArcGIS, or Python libraries like Rasterio.