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
Arable Crop Intelligence Systems
Integrated crop monitoring platforms (Arable Mark 3) that capture weather, plant, soil, and irrigation data along with daily crop imagery. These systems provide comprehensive environmental sensing at the field scale, combining multiple measurement modalities in a single integrated device.
Used across our field research sites to monitor soil moisture, temperature, weather conditions, and vegetation status. The integrated camera enables visual crop phenology monitoring alongside precise environmental measurements.
Multi-Modal Sensing
Combines soil, weather, plant, and imagery data in integrated platforms
Autonomous Robotics
Robotic systems for automated, high-frequency spatial measurements
Fluxbot: Automated Soil Carbon Flux Measurement
Autonomous robotic soil carbon flux chambers that enable high-frequency, spatially distributed measurement of soil respiration and carbon cycling. Fluxbots can be deployed as arrays to capture soil process heterogeneity at centimeter to meter scales.
Our fluxbot arrays deployed in East African savanna ecosystems enable novel insights into ecosystem carbon dynamics and heterogeneity. The open-source, wireless design makes this technology accessible for collaborative research globally.
Unmanned Aerial Vehicle (UAV) Remote Sensing
Drone-based platforms for high-resolution aerial surveys, including thermal imaging, multispectral photography, and structure-from-motion photogrammetry. UAVs enable spatial resolution and revisit frequency that bridge ground sensors and satellite platforms.
We use UAVs for vegetation mapping, water stress assessment, thermal remote sensing of riparian systems, and landscape-scale environmental monitoring. UAV data is integrated with ground-based measurements to provide multi-scale understanding of ecohydrological processes.
Multi-Scale Integration
UAV data bridges ground sensors and satellite observations for comprehensive monitoring
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.