Fusion of Multiscaled Spatial and Temporal Data: Techniques and Issues

Authored by: Dale A. Quattrochi , Elizabeth A. Wentz , Nina Siu-Ngan Lam , Charles W. Emerson , Bandana Kar , Edwin Chow

Integrating Scale in Remote Sensing and GIS

Print publication date:  January  2017
Online publication date:  January  2017

Print ISBN: 9781482218268
eBook ISBN: 9781315373720
Adobe ISBN:

10.1201/9781315373720-5

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Abstract

Whereas spatial data sets correspond to a specific 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 specific 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 field-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-first 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).

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