Many scientific fields require long-term monitoring of regions using sensors that are fixed in place, such as weather stations or acoustic stations that monitor fish abundance. These sensors produce high-quality streams of data in time, but typically over a small proportion of the study area. A long-standing sampling design problem is calculating how many sensors should be deployed to accurately estimate amounts of monitored variables such as rainfall. After a review of methods to scale point measurements to area, a new decision tree has been developed to help users decide which techniques should be used to scale time to space, and how many sensors to deploy to monitor an area of interest. The work by SAFS professor John Horne and SAFS Master’s graduate Dale Jacques, appears in the journal Environmental Monitoring and Assessment.