Scaling up Environmental Governance in Precision Forestry

Abstract

Precision Forestry is an emerging approach that uses digital technologies for data-driven decision-making in environmental management. Traditional methods for assessing tree risk are often subjective and focus on individual trees using mechanical approaches. The #SecureTree model offers an innovative alternative by deploying sensors to measure biophysical parameters like temperature, humidity, and acceleration. Data from these sensors is processed to create a risk assessment map based on the progression of trees' behaviors. This model is non-invasive and objective, addressing risk more effectively than current methods. Field tests validated the model's accuracy and highlighted its potential to identify long-term risk trends, enabling better planning for disruptive events and the development of digital strategies for emergency management.

Keywords: Environmental Informatics; Innovation; Precision Forestry; Risk Assessment; Wireless Sensor Network.