Animal Wildlife Population Estimation Using Social Media Images Collections

TL;DR

This paper introduces a novel framework for estimating wildlife populations using social media images, addressing the bias inherent in such data sources and demonstrating that this bias can be learned and mitigated.

Contribution

The paper presents a new method to account for social media bias in wildlife image data, enabling more accurate population estimates from social media sources.

Findings

Bias in social media wildlife images can be learned and corrected.

The proposed framework improves population size estimates.

Social media images are a viable data source for wildlife monitoring.

Abstract

We are losing biodiversity at an unprecedented scale and in many cases, we do not even know the basic data for the species. Traditional methods for wildlife monitoring are inadequate. Development of new computer vision tools enables the use of images as the source of information about wildlife. Social media is the rich source of wildlife images, which come with a huge bias, thus thwarting traditional population size estimate approaches. Here, we present a new framework to take into account the social media bias when using this data source to provide wildlife population size estimates. We show that, surprisingly, this is a learnable and potentially solvable problem.