TITLE:
Adjusting Second Moment Bias in Eigenspace Using Bayesian Empirical Estimators, Dirichlet Tessellations and Worldview I Data for Predicting Culex quinquefasciatus Habitats in Trinidad
AUTHORS:
Benjamin G. Jacob, Dave D. Chadee, Robert J. Novak
KEYWORDS:
Culex quinquefasciatus, Trinidad, West Nile Virus, Worldview 1, ArcGIS®
JOURNAL NAME:
Journal of Geographic Information System,
Vol.3 No.1,
January
28,
2011
ABSTRACT: Temporally weighted regression models with a spatial autoregressive component may estimate nonlinearities in spatiotemporal-sampled data of Culex quinquefasciatus, a major vector of West Nile Virus (WNV) which can help implement control strategies by determining optimal predictors associated to prolific habitats. The design of this kind of mixed model can specifically incorporate spatial autocorrelation whilst including the influence of other aspatial predictor variables. Currently, the lack of an estimation theory that allows for het- eroscedasticity and corresponding joint hypothesis testing in the presence of spatial dependence in georefer- enced Cx. quinquefasciatus habitat data is a serious shortcoming in WNV research. In this paper we used spatially lagged and simultaneous autoregressive models based on multiple predictor variables of immature Cx. quinquefasciatus and Worldview 1 (WV-1) data to help implant a remote habitat-based surveillance sys- tem in Trinidad. Initially, we used Geomatica Ortho Engine® v. 10.2 for extracting a Digital Elevation Model (DEM) from the WV-1 raw imagery. Results of the DEM analyses indicated a statistically significant inverse linear relationship between total sampled Cx. quinquefasciatus data and elevation (m) (R2 = -0.439; p