We are very happy and proud to announce that Olha Nahorna successfully defended her PhD within SmartForest on
“Assessing the importance of improved forest data for decision-making processes”
🎉 Congratulations, Olha! 🎉
The availability and quality of forest inventory data are critical for ensuring effective planning decisions. The errors in the inventory data could propagate through simulation and optimization models, leading to suboptimal planning decisions and potential economic and ecological losses. While improved data acquisition and processing approaches are continually being developed, the key question remains: how useful are these improvements for the decision-making? This thesis addresses this question though the value of information (Vol) assessment, with a focus on extending existing Vol frameworks to account for multiple planning objectives, decision-makers’ preferences, and uncertainty in the inventory data.
Typical Vol assessments focus on a single economic criterion, such as net present value. This thesis expands that framework by exploring multi-objective Vol using different formulations of the optimization models. To explore how Vol can change with the decision-makers’ preference information, various approaches to integrate preferences were assessed. This included simple preference parameters, explicit numerical targets, or relative distance to the ideal values. In two studies, the uncertainty in both the studied and reference data were accounted for through the use of stochastic programming. The concept of value of improved information (VoIl) was introduced to capture that reference data does not need to provide perfect information.
Overall, the findings highlight that the Vol is context-dependent, shaped by planning objectives, uncertainty, and decision-makers’ preferences. High-quality data may lead to significantly improved decisions in some cases, while offering little to no added value in others. Vol assessment proves to be an effective tool for comparing and evaluating different data acquisition or processing strategies. This set of studies recommends decision-makers to integrate VoI assessment, expanded to a multi-objective and uncertainty-aware framework, into the process or especially when evaluating new data acquisition and processing approaches.
👉 read the already published articles from Olha’s thesis here:
Assessing the importance of detailed forest inventory information using stochastic programming
📸 Marie-Claude Jutras-Perreault