Definition
Georeferenced ground measurements for attributes of interest and a host of remotely sensed variables are coupled within a Bayesian spatial regression model to provide predictions across the domain of interest. As the name suggests, multisource refers to multiple sources of data which share a common coordinate system and can be linked to form sets of regressands or response variables, y(s), and regressors or covariates, x(s), where the s denotes a known location in \(\mathbb{R}^{2}\)(e.g., easting-northing or latitude-longitude). Interest here is in producing spatially explicit predictions of the response variables using the set of covariates. Typically, the covariates can be measured at any location across the domain of interest and help explain the variation in the set of response variables. Within a multisource setting, covariates commonly include multitemporal spectral components from...
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Finley, A.O., Banerjee, S. (2016). Bayesian Spatial Regression for Multisource Predictive Mapping. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-23519-6_97-2
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DOI: https://doi.org/10.1007/978-3-319-23519-6_97-2
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