Synopsis: The main objective of this project is to study the potential of enhancing CESON capabilities with the use of Optical Remote Sensing (multispectral imaging) in unmanned aerial vehicles (UAV). Optical multispectral imaging is a useful tool for many applications such as soil analysis, crop health monitoring, earth and ocean topography, or even food processing. It is an efficient, noninvasive way of acquiring information with a high area coverage.

However, many of the techniques used today, as whisk broom and push broom, sacrifice efficiency for quality scanning an entire plane to acquire a single multispectral 3D data cube. This process makes it difficult and tedious to acquire dynamic scenes. Additionally, current spectral imaging instruments are expensive and thus restrictive for certain applications and settings

In this project we will work on the design, implementation and testing of a compact lightweight multispectral image acquisition system based on compressive sampling principles for UAV deployment using a high definition commercial camera for ocean and earth topographic analysis. The data collected in such instrument can help extend CESON capabilities by integrating it to current efforts to improve effective surface parameterization for improved high resolution satellite aerosol optical depth (AOD) over land for VIIRS, MODIS and GOES-R as well as validating new AOD approaches using LANDSAT data. We will develop multisensor data fusion mechanisms to effectively integrate the data and evaluate the quality of the obtained results against traditional AOD products. We will use historical satellite and UPRM ceilometer data to test the fusion mechanisms, while the Lidar Lab returns to operation.