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The Geographic Information Systems (GIS) is a domain-specific information system that deals with the information related to geographical objects. Such a system allows to store, query and manage the geographical context of things in a database. In such scenarios, the geographical objects are uniquely identified with their location information, including longitude, latitude, and timestamp related to a physical object. Examples of objects include static things like buildings, trees, pathways, or dynamic objects such as rivers, vehicles, etc.
Such systems provide rich and expressive query language that use spatial information to retrieve data from the stored system. In addition to querying, a GIS offers different functionalities such as:
(1)digitizing a hard copy of a map or survey,
(2) tracing geographic data on aerial imagery,
(3) relating information acquired from two different sources by matching their location ID
(4)Converting a raster image into a vector image and other similar functions.
Entering geographical data in GIS is a tedious and challenging task. GIS provides multiple ways to simplify data entry. Some of the commonly used methods to enter data in a GIS are: (1) The existing map data printed on paper can be digitized through scanning and tracing. The converted data is either stored in vector format or raster format. (2) Data can be directly collected using surveying instruments and recorded in GIS. (3) Another web-based data collection method called web-mining is also used, which depends on a crawler program to collect an object's geo-locations from different websites.
Remote sensing is another sophisticated way of collected geographical data. In this method, geographical object sensors such as cameras, digital scanners, and lidar are mounted on aerial platforms. Examples of aerial platform are satellite, aircraft, unmanned aerial vehicles (UAV), and drones. The data collected through satellite remote sensing are ordinarily available in the raster format, identifying land cover and scene identification changes on Earth.
Commercial and open-source GIS software products are available. The ArcGIS, QGIS and Google Earth Engine are few examples of such software products.
Geospatial data analysis is an emerging discipline that use machine learning and deep-learning techniques to analyze geographical data. It is becoming easier to detect land cover changes, forest land, and environmental degradation through such analysis. Due to its analytical power, the GIS is becoming an important tool to monitor sustainable development sectors and evaluate the impact of developmental actions.
