Spatial data can be obtained from various soures.The collection of spatial data can be done from scratch by direct spatial-data acquisition techniques or indirectly, by making use of data collected by others already. This learning path will introduce you to these sources:
One major source of collecting spatial data is Aerial photographs and satellite remote sensing to map relatively large areas which is the next concept of our discussion.
Spatial data can also be collected through Terrestrial surveys which are used to supplement, update of existing data and for verification of data from aerial surveys and by satellite remote sensing.
Field surveys are a major source of collecting spatial data to check and collect supplementary information from field(s), which comes as our next concept of discussion.
The next major source of collecting spatial data for our discussion is Mobile GIS which provides the platform for integration of mapping, GIS and positioning to field users via the use of devices: hand-held and mobile devices.
The next concept is metadata which is three type as Discovery Metadata; Exploration Metadata; and Exploitation Metadata.
Digitizing as a source of obtaining spatial data can be done by various techniques is the next item for our discussion and these techniques include: On-tablet digitizing and On-screen digitizing.
The process of Scanning can be a source of collecting spatial data which may help us to give an improvement to images through various images processing.
The next concept of the learning path for our consideration is Vectorization which looks at the process of distilling points, lines and polygons from scanned images.
This now takes us to data checks and repairs as part of data preparation to make acquired spatial data fit for use.
The final concept to be considered in this learning path is "Combining Data from multiple sources" or "Integrating Data sets from different sources". As GIS project normally involves multiple data sets, this part of the learning path addresses how such multiple data sets relate to each other.