Fusion of Satellite Image Time Series and Multimodal Data for Urban and Forestry Sustainable Development

Satellite Image Time Series (SITS) contain valuable information on the Earth’s surface evolution over time. Various applications can be derived from SITS analysis, e.g. land cover and land use change, urban growth, surveillance, resource management and so on. Considering the technological development of Earth Observation sensors and the increase in data variability and volume, the scope of the seminar is to show the importance of Earth Observation and ML/AI techniques in dealing with environmental issues, while raising awareness of the benefits of analysing multitemporal and multimodal remote sensing data.

In this seminar / workshop, we will develop and discuss techniques for SITS analysis for the benefit of creating sustainable cities and communities, while improving life on land. The following aspects will be discussed:

• Land surface processes monitoring using satellite time series
• Introduction to SITS analysis
• Urban and forestry data collection and management – the "Metropolitan Forest" project
• Data interpretation from the perspective of environmental sustainability
• Image analysis for environmental monitoring use case: wildfire detection
• Change detection
• Clustering and query by example retrieval in SITS
• Overview of environmental monitoring related projects, conclusions, and future perspectives

Students will analyse:

• impact of climate change on urban and forestry areas;
• techniques for SITS analysis (image analysis, change detection, clustering multitemporal; data, query by example retrieval, multimodal satellite imagery).

Students will be able to:

• discuss specific problems related to environment and climate change in a multidisciplinary framework;
• understand the benefits of remote sensing multimodal and multitemporal data;
• fuse knowledge extracted from SITS with information acquired by other types of sensors.

Coordinators:

• UPB: Assoc. Prof. Anamaria Rădoi, Prof. Alina Catrinel Ion
• UPM: Prof. Alicia Palacios, Prof. Silvia Merino de Miguel
• ITU: Prof. Behçet Uğur Töreyin, Prof. Elif Sertel.