Addressing environmental and atmospheric challenges for capturing high-precision thermal infrared data in the field of astro-ecology

TL;DR

This paper explores the use of thermal infrared drone imaging, combined with astrophysics techniques, to detect endangered species and poachers, highlighting environmental challenges and potential solutions for conservation efforts.

Contribution

It introduces an automated pipeline for thermal infrared data analysis in conservation ecology, adapting astrophysics methods and testing detection capabilities in field conditions.

Findings

Partial success in detecting humans in some terrains

Environmental factors like ground heat and vegetation hinder detection

Discussion of potential solutions for improved accuracy

Abstract

Using thermal infrared detectors mounted on drones, and applying techniques from astrophysics, we hope to support the field of conservation ecology by creating an automated pipeline for the detection and identification of certain endangered species and poachers from thermal infrared data. We test part of our system by attempting to detect simulated poachers in the field. Whilst we find that we can detect humans hiding in the field in some types of terrain, we also find several environmental factors that prevent accurate detection, such as ambient heat from the ground, absorption of infrared emission by the atmosphere, obscuring vegetation and spurious sources from the terrain. We discuss the effect of these issues, and potential solutions which will be required for our future vision for a fully automated drone-based global conservation monitoring system.