Raster data in Geographic Information System (GIS)
Raster data is a type of spatial data that is represented by a grid of cells or pixels. Each cell in the grid contains a value that represents a specific attribute or attribute combination, such as elevation, temperature, land cover, or population density. Raster data is commonly used in GIS applications to represent continuous phenomena, such as topography or satellite imagery. Here are the features of raster data in GIS:

1. Grid-based representation:
Raster data is represented by a regular grid of cells or pixels, where each cell has a unique value or set of values. This grid structure allows for the efficient storage and processing of large datasets.

2. Continuous data representation:
Raster data is well-suited for representing continuous phenomena because it can capture the variation of attributes across space. For example, a raster dataset of temperature can show the temperature values at each cell, allowing for the analysis of temperature patterns across a region.

3. Resolution:
Raster data can have different spatial resolutions, which refer to the size of each cell in the grid. Higher resolutions provide more detailed information, but also require more storage space and computational resources. The choice of resolution depends on the specific application and the level of detail required.

4. Data storage:
Raster data is typically stored as a grid of values in a raster file format, such as GeoTIFF or ERDAS Imagine. These file formats allow for the efficient storage and retrieval of raster datasets, as well as the preservation of georeferencing information.

5. Data processing:
Raster data can be processed using various GIS operations, such as overlay analysis, interpolation, and raster algebra. These operations allow for the extraction of information, the creation of derived datasets, and the analysis of spatial patterns.

6. Visualization:
Raster data can be visualized as maps or images, where the values of the cells are represented by colors or shades. This visualization helps in understanding the spatial patterns and relationships within the data.

7. Data analysis:
Raster data allows for various types of spatial analysis, such as suitability modeling, terrain analysis, and change detection. These analyses can provide valuable insights for decision-making in fields such as urban planning, agriculture, and environmental management.

Vector data in Geographic Information System (GIS)
Vector data is another type of spatial data used in GIS. Unlike raster data, which represents attributes as values in a grid, vector data represents attributes as discrete objects with geometric shapes. Here are the features of vector data in GIS:

1. Point, line, and polygon objects:
Vector data is composed of three types of geometric objects: points, lines, and polygons. Points represent discrete locations, such as the location of a city or a sampling site. Lines represent linear features, such as roads or rivers. Polygons represent areas, such as land parcels or administrative boundaries.

2. Topological relationships:
Vector data stores not only the geometry of the objects but also their topological relationships. Topology refers to the spatial relationships between objects, such as adjacency, connectivity, and containment. This topological information allows for more advanced spatial analyses, such as network analysis or spatial queries.

3. Attribute data:
Vector data stores attribute data associated with each object. Attributes can represent various types of information,