This course will introduce students to measurement theory 
(what, when, and how to measure).  Common measurement methods 
will be discussed in details with an emphasis on accuracy, 
precision, variability, and repeatability.  The theoretical 
principles behind common sensors used for environmental 
measurements (light, temperature, humidity, rain, soil water, 
etc.) will be discussed.  Automated methods to control such 
environmental variables will be discussed.  Efficient data 
collection methods, including the use of dataloggers, will be 
discussed.  At the end of the course students will:
- understand measurement principles and common sources of error
- understand how a variety of different sensors work
- be able to use this information to select the correct sensors 
for a particular measurement
- be able to use peripheral equipment to manipulate 
environmental conditions for research purposes.
The overall objective is to assure that graduate students have 
the ability to measure relevant environmental conditions 
correctly.

1. Principles behind measurements: accuracy, precision, 
variability, and repeatability.  Common error sources in 
environmental measurements. How often, and in how many 
different places do you need to measure different parameters?  
Spatial and temporal variability in environmental conditions.

2. Sensors for environmental measurements.  Operating 
principles and common error sources of:
- light sensors
- temperature sensors (soil, water, and air)
- humidity sensors
- rain gauges
- soil moisture probes
- electrical conductivity
- ion-selective electrodes (pH, specific nutrients)
- students will be encouraged to bring in their own sensors as 
well
 
3. Automated data collection: 
- what are the advantages, drawbacks, and limitations of 
commonly used dataloggers?
- What can and cannot be measured with different dataloggers 
(and why)?
- Datalogger programming: how do you make them do what you want 
to?
- What is the accuracy, resolution and precision of different 
loggers (and why does it matter)?
- Interfacing sensors and dataloggers
- Troubleshooting common problems
- How to use equipment in remote locations: unattended 
operation, power options, communications, and data retrieval
- Using dataloggers for environmental control in plant and soil 
science research (relays and relay drivers: using datalogger to 
turn equipment on and off)