The last few years have seen an increase in the number of earth observation platforms, such as satellites and airborne sensors which can monitor the earth’s surface. The availability of a wide range of sensors from optical, hyperspectral to synthetic aperture radar further facilitates a more accurate observation of earth surface. The images acquired from these sensors are typically analyzed using computer vision methods such as segmentation, classification, registration, detection, fusion, regression, etc.

As the IEEE GRSS IADF, we are pleased to announce our first school on Computer Vision for Earth Observation (CV4EO). This school will focus on applying CV methods to address challenges in remote sensing. This school will contain a series of lectures on the existing methods utilized for analyzing satellite images, along with the challenges encountered. Each lecture (2h) will be followed by a practical session (2h) where the participants will implement the techniques discussed in the lecture using some commonly used programming languages (e.g., Python) and open-source software tools to address the exercises provided by the expert teachers. The school will be held online from October 3-7, 2022. 

The school is open to everybody who has a strong motivation and interest in the topics addressed by it. Participants will not be charged a registration fee. The number of participants is limited to 75 to guarantee high-quality lessons with good interaction. If a higher number of registrations is received, the organizing committee will select the 75 participants and the broadcasting of the course will be guaranteed to everyone who showed an interest. All the selected participants will receive a certificate confirming their attendance to the school.