Creating a Data-Driven Forest Monitoring Architecture from LiDAR, Sensors, and Remote Sensing

Forest monitoring is becoming a data-integration problem. A typical monitoring program might use satellite imagery, LiDAR data, IoT sensors, field observations, weather reports, and various machine learning models. Each of these sources provide a different set of information, how to combine them comes with an interesting set of constraints. It's not a matter of getting data. It's a matter of using heterogeneous environmental data to create something useful to people who need to study or manage the forest.