TrueBranch: Metric Learning-based Verification of Forest Conservation Projects

04/21/2020
by   Simona Santamaria, et al.
1

International stakeholders increasingly invest in offsetting carbon emissions, for example, via issuing Payments for Ecosystem Services (PES) to forest conservation projects. Issuing trusted payments requires a transparent monitoring, reporting, and verification (MRV) process of the ecosystem services (e.g., carbon stored in forests). The current MRV process, however, is either too expensive (on-ground inspection of forest) or inaccurate (satellite). Recent works propose low-cost and accurate MRV via automatically determining forest carbon from drone imagery, collected by the landowners. The automation of MRV, however, opens up the possibility that landowners report untruthful drone imagery. To be robust against untruthful reporting, we propose TrueBranch, a metric learning-based algorithm that verifies the truthfulness of drone imagery from forest conservation projects. TrueBranch aims to detect untruthfully reported drone imagery by matching it with public satellite imagery. Preliminary results suggest that nominal distance metrics are not sufficient to reliably detect untruthfully reported imagery. TrueBranch leverages metric learning to create a feature embedding in which truthfully and untruthfully collected imagery is easily distinguishable by distance thresholding.

READ FULL TEXT

page 2

page 6

research
12/17/2019

Machine Learning-based Estimation of Forest Carbon Stocks to increase Transparency of Forest Preservation Efforts

An increasing amount of companies and cities plan to become CO2-neutral,...
research
11/11/2020

ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery

Characterizing the processes leading to deforestation is critical to the...
research
10/16/2021

Automated Remote Sensing Forest Inventory Using Satelite Imagery

For many countries like Russia, Canada, or the USA, a robust and detaile...
research
09/04/2023

Accuracy and Consistency of Space-based Vegetation Height Maps for Forest Dynamics in Alpine Terrain

Monitoring and understanding forest dynamics is essential for environmen...
research
10/10/2022

Deep object detection for waterbird monitoring using aerial imagery

Monitoring of colonial waterbird nesting islands is essential to trackin...
research
06/22/2020

Leveraging traditional ecological knowledge in ecosystem restoration projects utilizing machine learning

Ecosystem restoration has been recognized to be critical to achieving ac...
research
05/14/2023

Optimizing Forest Fire Prevention: Intelligent Scheduling Algorithms for Drone-Based Surveillance System

Given the importance of forests and their role in maintaining the ecolog...

Please sign up or login with your details

Forgot password? Click here to reset