The CCIT invites you to a seminar on Feb 25th from 12-13h, where ITU alumni Viktor Due and Aske Meineche, and Assistant Professor Maria Astefanoaei present the following paper from the SIGSPATIAL conference.

Abstract:
The availability of moderate and high-resolution satellite imagery collections and advancements in large scale cloud computing have created opportunities to develop globally consistent and near real time (NRT) land use and land cover (LULC) classification products. Such products have in turn facilitated the monitoring of land use and land cover change (LULCC) at a much larger scale than before. This is essential in understanding and analysing the competition for space in the context of a rapidly growing population, increasing standard of living, and a strained ecosystem. Several studies pointed towards inaccuracies and spatial and typology bias in LULC classification products. In this paper we investigate the feasibility of utilizing publicly available, pretrained models for LULCC analysis. We describe a framework for large scale analysis that allows incorporating diverse sources of data and we discuss a case study of quantifying LULCC driven by green energy infrastructure expansion. We introduce the concept of Rapid Change Sequences which can be used to improve classification accuracy. Lastly, we propose a method to produce vector embeddings of the LULC change graph, which is the first tool to allow cross country comparisons of land use change dynamics.

More info and link to online meeting here: https://ccit.itu.dk/Seminar-series

Picture credits: Nicolas van Leekwijck