ABSTRACT
Whereas spatial data sets correspond to a specic location on the Earth, temporal data capture the temporal dynamics of processes and systems. Because physical and social processes occur at a location at a specic time, spatial and temporal data are extensively used to represent and manage features corresponding to physical and social environments and to understand the interaction between these environments. Traditionally, spatial data sets are collected via remote sensing (imagery and data are collected from air and space using airborne cameras, satellites, and sensors), Global Positioning System (GPS) (a network of satellites that provide precise coordinate locations), and eld-based methods (e.g., total station instruments are used to collect spatial data and questionnaire surveys are used to collect attribute data). However, in the twenty-rst century, the growth and advancements in geospatial technologies, such as the launch of commercially operated satellites, have enabled the generation of large volumes of remotely sensed data for military and civilian purposes at high spatial, temporal, spectral, and radiometric resolutions. For instance, the WorldView-3 satellite sensor provides multispectral images at a spatial resolution of 0.31 m and a temporal resolution of 1-4.5 days (DigitalGlobe 2015).
