Coral Reef and Seagrass habitats have been impacted by increased river run off, coastal developments, and climate change at local and global scales over the past decade. Monitoring and managing these impacts over time require up-to-date information on the composition, distribution, structure and abundance of these habitats and their physical attributes. Field data and remote sensing have been used independently and in combination over time. Recent technical developments in gathering and processing field and image data using machine learning and access to regular satellite imagery provide an opportunity to obtain timely and relevant information. This paper presents an overview of ongoing innovation at site, local, regional to global scale providing the ability to monitor the changes and spatial patterns over time and space. Earth observation is applied through close range photogrammetry and photoquadrat surveys of coral and seagrass habitat linked in with drone, plane and globally covering satellite sensors. Processing to extract information is applied through machine learning and object-based analysis at individual photoquadrat scale to globally covering satellite scale. It provide example of innovation at organism to global scale supporting management and conservation of shallow coastal habitats over time.