Abstract
Land cover is one of the main environmental climate variables (ECVs) as it is highly correlated with climate change. In this context, in the framework of the Climate Change Initiative (CCI) of ESA, the High Resolution Land Cover (HRLC) project is aimed to study the role of the spatial resolution in the mapping of land cover and land-cover changes to support climate modelling research. Land cover and related changes are indeed both cause and consequence of human-induced or natural climate changes. This has been demonstrated by the previous phase of the CCI program, focused on the generation of Medium Resolution (MR) Land Cover maps at global scale. Differently from the MR land cover CCI, which provided annual land cover maps at 300m resolution in the period 1992-2019, the HRLC project produces regional maps characterized by a spatial resolution
of 10m/30m. Moving from 300m to 30m requires the definition of new data analysis methods, reframing the perspective with respect to the MR project both from the theoretical and the operational viewpoints. Although HR potentially increases the capability of a detailed analysis of spatial patterns in the land cover, many challenges are introduced with respect to the MR case and limitations in the
available data make the development of products at very large scale very challenging. This contribution presents the architecture and the methodologies developed for implementing the full processing chains that have been developed to process Earth Observation (EO) data and generate the HRLC products. The primary products of the project consist of: (i) HR land-cover maps at subcontinental scale at 10m as reference static input (generated for 2019 only) to the climate models, (ii) a long-term record of regional HR land cover maps at 30m in the regions identified for the historical analysis every 5 years (generated in the period 1990-2015), and (iii) change information at 30m at yearly scale consistent with historical HR land-cover maps.
of 10m/30m. Moving from 300m to 30m requires the definition of new data analysis methods, reframing the perspective with respect to the MR project both from the theoretical and the operational viewpoints. Although HR potentially increases the capability of a detailed analysis of spatial patterns in the land cover, many challenges are introduced with respect to the MR case and limitations in the
available data make the development of products at very large scale very challenging. This contribution presents the architecture and the methodologies developed for implementing the full processing chains that have been developed to process Earth Observation (EO) data and generate the HRLC products. The primary products of the project consist of: (i) HR land-cover maps at subcontinental scale at 10m as reference static input (generated for 2019 only) to the climate models, (ii) a long-term record of regional HR land cover maps at 30m in the regions identified for the historical analysis every 5 years (generated in the period 1990-2015), and (iii) change information at 30m at yearly scale consistent with historical HR land-cover maps.
| Original language | English |
|---|---|
| Publication status | Published - 1 Jan 2022 |
| Event | ESA Living Planet Symposium 2022 - German Aerospace Center (DLR), Bonn, Germany Duration: 23 May 2022 → 27 May 2022 https://sentinel.esa.int/web/sentinel/-/2022-living-planet-symposium/1.3 |
Conference
| Conference | ESA Living Planet Symposium 2022 |
|---|---|
| Country/Territory | Germany |
| City | Bonn |
| Period | 23/05/22 → 27/05/22 |
| Internet address |