Relating remotely sensed forest damage data to wind data: storms Lothar (1999) and Vivian (1990) in Switzerland

This study compares the surface wind speed and forest damage data of two exceptionally severe winter storms, Vivian 1990 and Lothar 1999. The study area comprises the region that suffered damage in Switzerland. The wind speed data were derived from simulations of MeteoSwiss (Federal Office of Meteorology and Climatology), measurements during the storm periods and expert analyses of the data. The remotely sensed forest damage data were provided by the Federal Office for the Environment and the forest cover data by Swiss Federal Statistical Office. We compared data on the peak gust and maximum average wind speed, with data on the spatially related forest area and forest damage area, and found some clear differences in the correlations between the different wind data and forest damage. Our results point generally to the damage-causing role of near-surface gusts at maximum wind speeds during the storm. These tended to be spatially distributed on a fine scale. In only a few cases were the results statistically significant. However, these results could probably be improved with better wind data. For example, gust measurements spatially closer to forests or simulations of gusts at maximum wind speed could be produced with a spatially higher resolutio

The Swiss data cube, analysis ready data archive using earth observations of Switzerland

Since the opening of Earth Observation (EO) archives (USGS/NASA Landsat and EC/ESA Sentinels), large collections of EO data are freely available, offering scientists new possibilities to better understand and quantify environmental changes. Fully exploiting these satellite EO data will require new approaches for their acquisition, management, distribution, and analysis. Given rapid environmental changes and the emergence of big data, innovative solutions are needed to support policy frameworks and related actions toward sustainable development. Here we present the Swiss Data Cube (SDC), unleashing the information power of Big Earth Data for monitoring the environment, providing Analysis Ready Data over the geographic extent of Switzerland since 1984, which is updated on a daily basis. Based on a cloud-computing platform allowing to access, visualize and analyse optical (Sentinel-2; Landsat 5, 7, 8) and radar (Sentinel-1) imagery, the SDC minimizes the time and knowledge required for environmental analyses, by offering consistent calibrated and spatially co-registered satellite observations. SDC derived analysis ready data supports generation of environmental information, allowing to inform a variety of environmental policies with unprecedented timeliness and quality

The Swiss Data Cube: Earth Observations for monitoring Switzerland’s environment in space and time

Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental variability. The key to sustainable development is achieving a balance between the exploitation of natural resources for socioeconomic development and maintaining ecosystem services that are critical to human’s wellbeing and livelihoods. Some of these environmental issues can be monitored using remotely sensed Earth Observations (EO) data that are increasingly available from freely and openly accessible repositories. Hereafter, we present the Swiss Data Cube, a unique Analysis Ready Data archive of satellite imagery and some use cases to monitor Sustainable Development Goals

The Swiss data cube, analysis ready data archive using earth observations of Switzerland

Since the opening of Earth Observation (EO) archives (USGS/NaSa Landsat and EC/ESa Sentinels), large collections of EO data are freely available, offering scientists new possibilities to better understand and quantify environmental changes. Fully exploiting these satellite EO data will require new approaches for their acquisition, management, distribution, and analysis. Given rapid environmental changes and the emergence of big data, innovative solutions are needed to support policy frameworks and related actions toward sustainable development. Here we present the Swiss Data Cube (SDC), unleashing the information power of Big Earth Data for monitoring the environment, providing analysis Ready Data over the geographic extent of Switzerland since 1984, which is updated on a daily basis. Based on a cloud-computing platform allowing to access, visualize and analyse optical (Sentinel-2; Landsat 5, 7, 8) and radar (Sentinel-1) imagery, the SDC minimizes the time and knowledge required for environmental analyses, by offering consistent calibrated and spatially co-registered satellite observations. SDC derived analysis ready data supports generation of environmental information, allowing to inform a variety of environmental policies with unprecedented timeliness and quality