22 Python libraries for Geospatial Data Analysis
22 Python libraries for Geospatial Data Analysis

Spatial data, Geospatial data, GIS data or geodata, are names for numeric data that identifies the geographical location of a physical object such as a building, a street, a town, a city, a country, etc. according to a geographic coordinate system.

From the spatial data, you can find out not only the location but also the length, size, area or shape of any object.

An example of a kind of spatial data that you can get are: coordinates of an object such as latitude, longitude, and elevation.

Geographic Information Systems (GIS) or other specialized software applications can be used to access, visualize, manipulate and analyze geospatial data.

Some examples of geospatial data include:

1. Vectors and Attributes

Points, lines, polygons, and other descriptive information about a location.

Understanding Vector Data

Vector data is a representation of a spatial element through its x and y coordinates. The most basic form of vector data is a point. Two or more points form a line, and three or more lines form a polygon.

The simplest form is to include one or more extra columns in the table that defines its geospatial coordinates. More formal encoding formats such as GeoJSON also come in handy.

GeoJSON, an extension to the JSON data format, contains a geometry feature that can be a Point, LineString, Polygon, MultiPoint, MultiLineString, or MultiPolygon.

There are several other libraries available for representing geospatial data that are all described in the Geospatial Data Abstraction Library (GDAL).

2. Point Clouds

Collected by LiDAR systems, they can be used to create 3D models.

Understanding Point Cloud data from LiDAR systems

3. Raster and Satellite Imagery

Get a birds eye view of what the Earth looks like via high resolution imagery.

Raster data is used when spatial information across an area is observed. It consists of a matrix of rows and columns with some information associated with each cell.

An example of raster data is a satellite image of a nation or a city represented by a matrix that contains the weather information in each of its cells.

There are several ways that you can work with raster data in Python.
['Ishan Jain']
['Geofencing', 'GIS', 'Geopandas', 'Shapely', 'Python']