Introduction to Geospatial Data analysis using Python Geopandas || ARCGIS || PYTHON || GEOPANDAS

Geospatial data is data about objects, events, or phenomena that have a location on the surface of the earth. The location may be static in the short-term (e.g., the location of a road, an earthquake event, children living in poverty), or dynamic (e.g., a moving vehicle or pedestrian, the spread of an infectious disease). Geospatial data combines location information (usually coordinates on the earth), attribute information (the characteristics of the object, event, or phenomena concerned), and often also temporal information (the time or life span at which the location and attributes exist).

Much geospatial data is of general interest to a wide range of users. For example, roads, localities, water bodies, and public amenities are useful as reference information for a number of purposes. For this reason, whether collected by public or private organizations, large amounts of geospatial data are available as open data. This means that it can be accessed freely by users, and is made available through open standards. The development and use of open standards within the geospatial community have been heavily supported because of the wide range of uses to which geospatial data can be applied, and because of the large numbers of agencies both globally and locally that are involved in collecting such data.
Study Area Mapping:
Landuse Land Cover link:
Landslide Assessment video link:
USGS data downloading tutorial video link:
Fire Risk Assessment video link:
Water Delineation Tutorial link:
Georeferencing On ArcMap:

[dr.manojkashyap]

Please make a tutorial related drainage texture, drainage frequency.thank you