Landsat's past paves the way for data democratization in earth science
Abstract: The Landsat Program has been observing and collecting Earth system data from space since 1972. Over this time, advances in spatial, spectral, and radiometric resolution have allowed the Landsat satellites to evolve into powerful global Earth observation imaging systems. The longevity of the Landsat Program has produced a massive catalogue of imagery data. The sheer magnitude of this collection necessitates the use of scalable techniques to extract value from decades of remote sensing data. With the introduction of commercial cloud computing, it is now possible to cheaply provision resources for processing and storing enormous amounts of such data. Machine learning based computer vision is advancing at a blistering pace and has shown great promise when applied to satellite imagery. The combination of cloud computing and machine learning offers the ability to analyze the decades of imagery collected by the Landsat Program at a cost never before possible. The focus of this chapter is to discuss the Landsat Program progression, cloud computing, machine learning, and data policy and how all these components contribute to greater understanding on the state of our planet Earth.