The organisation
A non-profit research initiative built on the belief that high-resolution atmospheric data should be accessible to everyone — not locked behind institutional paywalls or commercial interests.
Mission
The lower atmosphere — the layer of air closest to the Earth's surface — is where weather forms, pollutants disperse, and human activity has its most immediate climatic impact. Yet it remains chronically under-characterised. Fixed weather stations provide point measurements; satellites lack vertical resolution; balloon sondes are infrequent and expensive.
LADAR was founded to close this gap. By deploying modular, drone-based sensing platforms, we can conduct high-resolution three-dimensional profiling of temperature, humidity, airflow, and pollutants at spatial and temporal scales that were previously impractical.
As a non-profit, we are not beholden to commercial or institutional interests. Our data is open. Our methods are transparent. Our research is freely published.
Open by default
All datasets, reconstructed fields, and research outputs are published under open licences. Data collection is publicly logged.
Non-profit structure
LADAR operates without commercial incentive. Research priorities are driven by scientific value, not funding pressures.
Reproducible methods
Sensor configurations, flight protocols, and reconstruction algorithms are fully documented and available for independent replication.
Objectives
A modular platform that can be progressively expanded with additional instruments and research objectives without compromising flight performance or reliability.
Thermal profiling, turbulence analysis, pollutant dispersion mapping, and surface–atmosphere interaction across multiple temporal and spatial scales.
Combining physics-based models with machine learning reconstruction to generate continuous volumetric representations from sparse in-situ measurements.
Real-time gradient detection, anomaly identification, and dynamic sampling to efficiently capture transient or extreme atmospheric events.
Suitable for fundamental atmospheric physics investigations and applied environmental studies, including urban climate assessment and numerical model validation.
All research outputs — datasets, reports, and papers — freely available to researchers, institutions, and the public without restriction.
Roadmap
ATLAS is designed to be progressively scalable. Development begins with a lightweight Core Atmospheric Profiling Configuration, establishing baseline data collection and system reliability before any subsequent expansion.
Design, build, and validate Stack 1. Establish flight protocols, data logging pipelines, and initial field reconstruction methods.
Introduce Stack 2 air quality sensors following successful Stack 1 validation. Begin pollutant dispersion datasets.
Integrate Stacks 3 and 4 for direct wind vector measurement and thermal surface mapping.
Stack 5 onboard edge computing enabling autonomous anomaly detection, adaptive sampling, and ML-informed path optimisation.
Our commitments