Analysis of Remotely Sensed Images Through Social Media

During the past decades, the volume of big data available in remote sensing (RS) applications has grown significantly. In addition, a number of applications related to monitoring human activity are being developed based on this kind of data. This has considerably increased the demand for RS processing methods. In this sense, the scientific community is facing the challenge of how to maximize the potential of the data that are produced in a fast and efficient way. In particular, the provision of processing algorithms that can be developed in an easy way is a fundamental problem for the RS community, due to the large volume of data offered by different portals and agencies, and the need for algorithms developed on different platforms and using a variety of programming frameworks. To address these challenges, this article takes advantage of social media tools to bring images and algorithms closer to users. In particular, a new system based on the Telegram messaging application Bot (called @ThuleRSbot) has been developed to provide a wide variety of RS image processing methods to users under the same interface. The system has been developed using the Python language and the Telegram Bot application program interface (API). The most remarkable characteristics of the system are: first, a completely open architecture that facilitates the incorporation of new algorithms without effort; and second, an easy way to automatically gather satellite images from the Sentinel Hub platform.