This study was designed to investigate the relationships between spectral properties of cottonwood plantations and defoliation by the cottonwood leaf beetle (CLB), Chrysomela scripta F., as well as to develop and analyze the spatial structure of CLB and associated defoliation using geospatial information technology. Multispectral imagery data from airborne platforms were acquired using three remote sensing systems: (1) GeoVantage remote sensing system with 450 nm, 550 nm, 650 nm and 850 nm wavelengths; (2) RDACS (real time digital airborne camera system) with 540 nm, 675 nm, 695 nm and 840 nm wavelengths; and (3) Kodak DCS420 digital camera with the 500-810 nm wavelengths (red, green and near infrared). In addition, multispectral and hyperspectral radiometric data were collected using spectroradiometer. Analyzing reflectance values for simulated CLB defoliation indicated that the 0% and 25% defoliation could be differentiated from the 75% defoliation in the near infrared (NIR). Utilizing normalized difference vegetation index and a simple vegetation index, 0% and 25% defoliation could also be separated from 50% and 75% defoliation. Reflectance values for natural defoliation by CLB and various ground covers indicated that NIR was the best indicator for distinguishing different ground cover types. Heavy feeding by CLB could be detected but light or no feeding could not be discriminated from each other using these systems mentioned above. Spectral spatial analysis of a first year rising cottonwood plantation indicated that a wave (hole-effect) variogram model could be used to describe the spatial structure at omnidirection. Within the 1.90 - 2.48 m range, there is a significant spatial autocorrelation of reflectance. Spatial structure of adult and larval populations indicated that spatial dependence varied among dates and directions. Spherical and Gaussian functions provided the best statistical fit for CLB adult and larval spatial distributions, which were aggregated. The signature analysis for hyperspectral data indicated that when comparing the 0% defoliation to the 25, 50 and 75% defoliation, maximum reflectance differences were found near 294 nm in the ultraviolet, 550 nm in the visible spectrum and 764 nm in the near infrared spectrum. The highest reflectance sensitivity occurred between 528-557 nm in the visible spectrum. High sensitivities were also found between 730-740 nm and 930-940 nm in the infrared spectrum. Bands from 892-894 nm were best for separating various defoliation levels. This study has first demonstrated the application of remote sensing combined with GPS and geostatistics to CLB defoliation of cottonwood. The defoliation level of cottonwood can be detected and assessed using different remote sensing systems. Spatial models can be used to map CLB population densities and defoliation rates in landscapes. These maps can be used for site specific CLB management.