Development of a wireless sensor network for in-situ image validation for water and nitrogen management

Water and Nitrogen (N) are critical inputs for crop production. Remote sensing data collected from multiple spatial scales, including ground-based, aerial, and satellite, can be used for the formulation of an efficient and cost effective algorithm for the detection of N and water stress. Effective calibration of such techniques requires the continuous acquisition of ground based spectral data over the canopy enabling field measurements to coincide exactly with aerial and satellite observations. To test this idea, a wireless in-situ sensor network was developed to acquire spectral data in seven narrow wavebands (470, 550, 670, 700, 720, 750 and 790 nm) critical for monitoring crop growth and N status. The wireless sensor network (WSN) was established based on different spatial sampling strategies and each of the spectral measurements were recorded at specified temporal intervals (up to 30 seconds). The data were relayed through a multi-hop wireless network to a base computer at the field site. These data were then accessed by the remote sensing centre computing system through broad band internet. This paper describes the first phase of the experiment with the details of sensor development and instrumentation set up. Comparison of the data from the WSN and an industry standard ground based hyperspectral radiometer indicated that there were no significant differences in the spectral measurements for all the wavebands except for 790nm. Combining sensor and wireless technologies enables a robust means of aerial and satellite data calibration through acquisition of high temporal frequency data combined with simultaneous spatial distribution.