Matthew O. Jones

TL;DR: The Carnegie Airborne Observatory (CAO) provides in-flight fusion of high-fidelity visible/near-infrared imaging spectrometer data with scanning, waveform light detection and ranging (wLiDAR) data, along with an integrated navigation and data processing approach, that results in geo-orthorectified products for vegetation structure, biochemistry and physiology as well as the underlying topography.

TL;DR: This paper analyzed global phenology cycles over a six-year record (2003-2008) using satellite passive microwave remote sensing based Vegetation Optical Depth (VOD) retrievals derived from daily time series brightness temperature (Tb) measurements from the Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and other ancillary data inputs.

TL;DR: Analysis of canopy hyperspectral reflectance properties of 37 distinct species or phenotypes, 7 common native and 24 introduced tree species, provides a basis for more detailed studies of invasive species in Hawai'i, along with more explicit treatment of the biochemical properties of the canopies and their prediction using imaging spectroscopy.

TL;DR: In this article, a hybrid airborne system combining the Carnegie Airborne Observatory (CAO) small-footprint light detection and ranging (LiDAR) system with the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) was deployed to map the three-dimensional spectral and structural properties of Hawaiian forests.

TL;DR: This work uses Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset, and uses a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales.