Sensors, Measurements, and Software
Developing novel approaches that illuminate ecohydrological patterns and processes through advanced remote sensing and monitoring technologies
Environmental Sensing Research
Our sensors research focuses on creating innovative measurement techniques, developing open-source software tools, and advancing environmental monitoring capabilities. We design and deploy sensor networks, develop remote sensing applications, and create analytical tools that enable new scientific discoveries.
Research Focus
Environmental monitoring in remote and resource-limited settings requires innovative technological solutions. We develop cost-effective, robust sensor systems that can operate reliably in challenging field conditions.
Our work bridges the gap between technological innovation and scientific application, creating tools that enable new research questions and improve our understanding of environmental processes.
Methodological Approach
We combine hardware development, software engineering, and data science to create integrated monitoring solutions. Our approach emphasizes open-source development and community-driven innovation.
From satellite-based remote sensing to ground-based sensor networks, we work across scales to develop comprehensive monitoring systems for environmental research and management.
Key Research Areas
Our sensors research spans multiple interconnected areas of technology development
Remote Sensing
Satellite and airborne remote sensing of vegetation dynamics, water cycles, and land cover change, including hyperspectral and thermal infrared applications.
Sensor Networks
Wireless sensor networks for environmental monitoring, including soil moisture, weather stations, and plant physiological measurements in remote locations.
IoT Systems
Internet of Things (IoT) applications for agricultural monitoring, including crop sensing, irrigation management, and real-time data transmission from field sites.
Open-Source Software
Development of open-source software tools for environmental data analysis, including R packages, Python libraries, and web-based applications for the research community.
Machine Learning
Machine learning applications for environmental monitoring, including image classification, time series analysis, and predictive modeling for agricultural and ecological systems.
Data Integration
Methods for integrating multi-source environmental data, including sensor fusion, data quality assessment, and creating comprehensive datasets from diverse monitoring systems.
Technology Highlights
Examples of innovative sensing technologies developed by our lab
PulsePod
Low-cost, wireless sensor platform for environmental monitoring in remote locations. Features solar power, cellular connectivity, and modular sensor interfaces for customized deployments.
Used extensively in our field sites across Africa for monitoring soil moisture, weather conditions, and plant physiological responses.
Award Winner
Third place winner at Princeton's Keller Center Innovation Forum
Open Source
All software tools available on GitHub for community use and development
COSMOS Probes
Cosmic-ray soil moisture sensing technology for large-scale, non-invasive monitoring of soil water content across multiple hectares with a single sensor.
Deployed at the Mpala Research Centre in Kenya, providing continuous landscape-scale soil moisture measurements for ecohydrological research.
Recent Sensors Publications
Latest research in environmental sensing and measurement technologies
Explore Our Research
Learn more about our other research themes and discover how sensors and measurements connect with ecohydrology and human systems research.