Environmental Factors
Sky Conditions
As operators of research-grade remote sensing systems, we always pray for good weather. But this is not something we can control. Keeping close tabs on forecasts is a vital part to the success of research remote sensing, especially when involving hyperspectral sensors.
Depending on a user's requirements, hyperspectral collection requires bright, consistent lighting for optimal data capture. This means flying within two hours of solar noon during the summer season, limiting to one or one and a half hours from solar noon the further in time from summer solstice.
We recommend having no clouds in the sky when possible, but at the very least no clouds may pass in front of the sun during data collection. Extreme haze can also caused reduced data quality, and should be avoided when possible.
Wind
When thinking in the context of remote sensing, especially hyperspectral line-scan sensors that are very sensitive to aircraft attitude and speed, wind plays a big factor. Beyond the obvious limitations of the platform carrying the sensors and its ability to fly safely, we have to consider the implications of wind on the aircraft and how it affects the aircraft's stability, from the lens of maximizing our remote sensing data quality.
Many factors will impact how much wind can be tolerated while achieving sufficient data quality. A few of these are:
Ratio of payload weight to total payload capacity of an aircraft
Aircraft size and number/power of motors
Aircraft hull design and how aerodynamic it is
Flight controller's response and stability in wind
A general recommendation, with the caveats above and your own personal experience in assessing data quality in various wind levels, is that 50% of an aircraft's rated wind resistance may still be suitable for maximizing data quality. Beyond this, caution is advised, and addressing the potential for instability should be considered when flight planning and configuring sensors (adding additional oversampling in hyperspectral, for example).
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