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Container Aedes mosquitoes are responsible for the transmission of anthroponotic and zoonotic viruses to people. The surveillance and control of these mosquitoes is an important part of public health protection and prevention of mosquito-borne disease. In this study, we surveyed 327 sites over 2 weeks in late June and early July in 2017 in North Carolina, USA for the presence and abundance of Aedes spp. eggs in an effort to better target potential Ae. aegypti collections. We examined the ability of 2 types of landscape data, Light Detection And Ranging (LIDAR) and National Land Cover Database (NLCD) to explain the presence and abundance of eggs using principal component analysis to deal with collinearity, followed by generalized linear regression. We explained variation of both egg presence and abundance for Aedes albopictus (Skuse) and Aedes triseriatus (Say) using both NLCD and LIDAR data. However, the ability to make robust predictions was limited by variation in the data. Increased sampling time and better landscape data would likely improve the predictive ability of our models, as would a better understanding of oviposition behavior.