Deep learning approach for automated geospatial data collection - Al-Azizi, Jalal Ibrahim (2020)
Geospatial data collection and mapping are considered to be one of the key tasks for many users of spatial information. Traditionally, data collection and mapping can be done using a variety of methods, such as mobile mapping, remote sensing and conventional survey methods. Each method has its advantages, accuracy, costs and limitations. It is therefore essential to assess the requirements of the project in order to ensure that the relevant data quality is acquired at the lowest possible cost. However, one of the greatest barriers is the availability of digital spatial data and attributes. Often this problem arises because these methods are considered costly and require considerable effort and time.