In pursuit of global sustainability, forestry has witnessed significant shifts in practices and the development of new technologies and ideas. Primary and secondary processing industries have made substantial efforts to increase wood utilization rates, improve occupational safety and the working environment for humans, and have exhibited interest in procuring raw materials from certified sources. In the land management sector, sustainable forestry practices have motivated the inclusion of management objectives that appeal to a diverse set of interests regarding water and soil quality, wildlife habitat, aesthetics, economics and socio-cultural factors. Multi-objective management regimes, manifested in complex silvicultural systems characterized by elaborate site-specific treatment prescriptions, have a direct impact on harvesting operations. In contrast to traditional clearcutting practices, alternative silvicultural methods are, in general, more costly to implement due to the increase of time and personnel invested to layout prescriptions, the reduction in harvesting productivity, and the increased level of administration and monitoring needed to ensure environmentally compliant operations and desirable future conditions. Furthermore, alternative silvicultural prescriptions might not include an adequate economic component to help offset the cost of implementation. This dissertation is concerned with reducing the cost of these treatments. It is our conviction that increasing the level of automation in forest operations can create a foundation for integrating harvest layout with the harvesting system while simultaneously maintaining a high degree of trust between the landowner and harvesting contractors. We present a vision-based automatic tree measurement and mapping system that is intended to eliminate the need for individual tree marking by providing equipment operators with data regarding prescription compliance in real time. We made significant efforts to develop a low-cost system to encourage adoption and we have generalized this technology to motivate its use in forestry applications other
than harvesting. We believe the work presented in this dissertation to be a significant contribution to forest operations and a tool to aid in the pursuit of sustainable forest management.