Work

Multi-objective value of information assessment using stochastic programming: addressing uncertainty in site index determination

Year: 2025

Type: article

Abstract: Assessing the value of information (VoI) plays a critical role in determining the usefulness of data for informed decision-making. The evaluation of VoI should reflect the specific forest planning goals and allow for the inclusion of multiple objectives. We present a method that quantifies multi-objective VoI using stochastic programming optimization, enabling the integration of data uncertainty into the planning process. The developed optimization model includes economic and ecological criteria and integrates the decision-maker’s targets through the use of an achievement-scalarizing function. The VoI reflects how well data will help to meet the defined targets by comparing the outcomes of using the data of varying quality. We demonstrate the VoI assessment method through a case study that incorporates the uncertainty in forest productivity, represented by the site index (SI). Erroneous estimates of SI will lead to cumulative errors when forecasting forest development and subsequent sub-optimal management decisions. We compared the VoI of the direct and height differential approaches for SI determination using either bi-temporal airborne laser scanning (ALS) data or ALS and subsequent digital aerial photogrammetry (DAP) data. To compute the VoI, we used field-measured SI as the reference SI. The results demonstrated that the height differential approach outperformed the direct approach and indicated that a combination of ALS and subsequent DAP data could be a good alternative to bi-temporal ALS data for SI determination. However, the results are case-specific and depend on the decision-maker’s individual preferences and objectives. The proposed VoI assessment method is easily adaptable to various preference information and can be applied to different data acquisition approaches.

Source: Forestry An International Journal of Forest Research

DOI: 10.1093/forestry/cpaf021

Authors: Olha Nahorna, Maria Åsnes Moan, Lennart Noordermeer, Terje Gobakken, Ole Martin Bollandsås, Kyle Eyvindson

Institutions: Norwegian University of Life Sciences, Natural Resources Institute Finland

Language: English

Topic: Remote Sensing and LiDAR Applications

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Life on land

Open Access status: hybrid

Estimated APC paid: $3,810