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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., Measurement(s)surface reflectance • backscatterTechnology Type(s)satellite imagingSample Characteristic - LocationSwitzerland Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14635485

The Planetary Boundaries concept is a recent scientific framework, which identifies a set of nine bio-physical limits of the Earth system that should be respected in order to maintain conditions favourable to further human development. Crossing the suggested limits would lead to drastic changes in human society by disrupting some of the ecological bases that underlie the current socio-economic system. As a contribution to the international discussion, and using the case of Switzerland, this study proposes a methodology to apply the Planetary Boundaries concept on the national level. Taking such an approach allows to assess the environmental sustainability of the socio-economic activities (e.g. consumption) by the inhabitants of a country in a long-term global perspective, assuming that past, current and future populations on Earth have similar "rights" to natural resources. The performance of countries is evaluated by comparing the country limits with their environmental footprints according to a consumption-based perspective. An approach was developed to: i) better characterise the Planetary Boundaries and understand which limits can effectively be currently quantified; ii) identify related socio-economic indicators for which both country limits and footprints can be computed; iii) compute values for limits, footprints and performances (at global and country level); and iv) suggest priorities for action based on the assessment of global and national performances. It was found that Switzerland should, as a priority, act on its footprints related to Climate Change, Ocean Acidification, Biodiversity Loss and Nitrogen Loss. The methodology developed herein can be applied to the analysis of other countries or territories, as well as extended to analyse specific economic sectors.

Global environmental changes are mostly induced by human activities (e.g., food and energy production, urbanization, mining activities). To assess and understand these changes that are occurring all around the planet, regular and continuous monitoring is an essential condition. However, due to the potentially large area spread over numerous locations that need to be followed, this usually leads to a low frequency of monitoring of environmental changes of only a few selected sites at best. With the increasing number of freely and openly accessible big remotely-sensed Earth Observations (EO) Data repositories and the increasing capabilities of open and interoperable software solutions it is now possible to automate various EO data processing tasks to monitor environmental changes at large scale. This paper presents the Live Monitoring of Earth Surface (LiMES) framework that helps to automate image processing tasks in transforming raw data into information and knowledge through workflows using interoperable processing service chains for monitoring environmental changes. Both benefits and limitations are demonstrated and discussed through the implementation of a prototype to facilitate the update on the status of some of the 278 UNEP Environmental Hotspots. We believe that such a framework can help to reduce the gap between massive volumes of EO data and the users such as International Organizations (IO) in order to help them better fulfil their environmental monitoring mandates by bringing raw data to a level which can be used by non-remote sensing experts for basic impacts assessments.

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. Some of these environmental issues can be monitored using remotely sensed Earth Observations (EO) data that are increasingly available from a number of freely and openly accessible repositories. However, the full information potential of EO data has not been yet realized. They remain still underutilized mainly because of their complexity, increasing volume, and the lack of e cient processing capabilities. EO Data Cubes (DC) are a new paradigm aiming to realize the full potential of EO data by lowering the barriers caused by these Big data challenges and providing access to large spatio-temporal data in an analysis ready form. Systematic and regular provision of Analysis Ready Data (ARD) will signi cantly reduce the burden on EO data users. Nevertheless, ARD are not commonly produced by data providers and therefore getting uniform and consistent ARD remains a challenging task. This paper presents an approach to enable rapid data access and pre-processing to generate ARD using interoperable services chains. The approach has been tested and validated generating Landsat ARD while building the Swiss Data Cube.

The present contribution constitutes the first comprehensive attempt to (a) record the spatial characteristics of the beaches of the Aegean archipelago (Greece), a critical resource for both the local and national economy, and (b) provide a rapid assessment of the impacts of the long-term and episodic sea level rise (SLR) under different scenarios. Spatial information and other attributes (e.g., presence of coastal protection works and backshore development) of the beaches of the 58 largest islands of the archipelago were obtained on the basis of remote-sensed images available on the web. Ranges of SLR-induced beach retreats under different morphological, sedimentological and hydrodynamic forcing, and SLR scenarios were estimated using suitable ensembles of cross-shore (1-D) morphodynamic models. These ranges, combined with empirically derived estimations of wave run-up induced flooding, were then compared with the recorded maximum beach widths to provide ranges of retreat/erosion and flooding at the archipelago scale. The spatial information shows that the Aegean pocket beaches may be particularly vulnerable to mean sea level rise (MSLR) and episodic SLRs due to (i) their narrow widths (about 59 % of the beaches have maximum widths

Until the 1970s, disaster risk was perceived as a direct consequence of natural hazards. Gradually, disaster risk has come to be understood as a compound event, which lies at the intersection of hazards, exposure, and vulnerability of the exposed elements. After decades of research and lessons learned from mega-disasters, social scientists have introduced the social dimension of disaster risk, and the prevailing understanding is that disasters are also a human construct. Now, due to climate and global environmental changes, even the natural component of hazards is being altered by anthropogenic activities, changing hazard susceptibility, coverage, frequency, and severity. This review retraces the brief history and evolution of the global understanding of disaster risk as a compound event, in parallel with research on global environmental change. It highlights the main milestones in this area, and shows that there are tight connections between trends of disaster risk and global change. This paper aims to demonstrate the need to better consider the role of global environmental change in disaster risk assessment. In 2015, three major new agreements were reached to improve global environmental governance: the new Sendai Framework (2015–2030), the post-2015 development agenda with the 17 Sustainable Development Goals (SDGs), and the Climate COP21 in Paris. These all include a clear focus on disaster risk reduction; however, several aspects of disaster risk linked with global environmental changes are still not clearly addressed by the main stakeholders (governments, insurers, or agencies). As the complexity of risk unfolds, more actors are getting together; the need for a holistic approach for disaster risk reduction has become clear, and is closely connected with achieving sustainable development.

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.

With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

Sand and gravel are mined world-wide and account for the largest volume of solid material extracted globally. Formed by erosive processes over thousands of years they are now being extracted at a rate far greater than their renewal. Furthermore, the volume being extracted is having a major impact on rivers, deltas and coastal and marine ecosystems results in loss of land through river or coastal erosion, lowering of the water table and decreases in the amount of sediment supply. Despite the colossal quantities of sand and gravel being used, our increasing dependence on them and the significant impact that their extraction has on the environment, this issue has been mostly ignored by policy makers and remains largely unknown by the general public.

Hydrological fracturing techniques have made accessible vast unconventional gas reserves. However, observed impacts on the environment and human health raise legitimate public concerns. The potential climate benefits of coal-to-gas substitution are both less clear and more limited than initially claimed. The question of whether to allow or ban gas fracking needs to be carefully assessed by relevant authorities. A review of current related policies and regulations is critically needed.

Assessments of tropical cyclone risk trends are typically based on reported losses, which are biased by improvements in information access. Now research based on thousands of physically observed events and contextual factors shows that, despite projected reductions in tropical cyclone frequency, projected increases in demographic pressure and tropical cyclone intensity can be expected to exacerbate disaster risk.

With climate change, urban development and economic growth, more assets and infrastructures will be exposed to flooding. Now research shows that investments in flood protection are globally beneficial, but have varied levels of benefit locally.

Understanding the complexity of earth-system processes is crucial to convey improved information on the environment to decision-makers and the general public. Addressing this need by sharing environmental data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. In this regard, the Global Earth Observation System of Systems (GEOSS) portends major benefits through various sharing mechanisms and by giving access to services that could be linked together to process and generate new understandable knowledge and information. Various United Nations projects could greatly benefit from the GEOSS approach.

Higher temperatures and changes in precipitation patterns have induced an acute decrease in Andean glaciers, thus leading to additional stress on water supply. To adapt to climate changes, local governments need information on the rate of glacier area and volume losses and on current ice thickness. Remote sensing analyses of Coropuna glacier (Peru) delineate an acute glaciated area decline between 1955 and 2008. We tested how volume changes can be estimated with remote sensing and GIS techniques using digital elevation models derived from both topographic maps and satellite images. Ice thickness was measured in 2004 using a Ground Penetrating Radar coupled with a Ground Positioning System during a field expedition. It provided profiles of ice thickness on different slopes, orientations and altitudes. These were used to model the current glacier volume using Geographical Information System and statistical multiple regression techniques. The results revealed a significant glacier volume loss; however the uncertainty is higher than the measured volume loss. We also provided an estimate of the remaining volume. The field study provided the scientific evidence needed by COPASA, a local Peruvian NGO, and GTZ, the German international cooperation agency, in order to alert local governments and communities and guide them in adopting new climate change adaptation policies.

The growing concern for loss of services once provided by natural ecosystems is getting increasing attention. However, the accelerating rate of natural resources destruction calls for rapid and global action. With often very limited budgets, environmental agencies and NGOs need cost-efficient ways to quickly convince decision-makers that sound management of natural resources can help to protect human lives and their welfare. The methodology described in this paper, is based on geospatial and statistical analysis, involving simple Geographical Information System (GIS) and remote sensing algorithms. It is based on free or very low-cost data. It aims to scientifically assess the potential role of vegetation in mitigating landslides triggered by earthquakes by normalising for other factors such as slopes and distance from active fault. The methodology was applied to the 2005 North Pakistan/India earthquake which generated a large number of victims and hundreds of landslides. The study shows that if slopes and proximity from active fault are the main susceptibility factors for post landslides triggered by earthquakes in this area, the results clearly revealed that areas covered by denser vegetation suffered less and smaller landslides than areas with thinner (or devoid of) vegetation cover. Short distance from roads/trails and rivers also proved to be pertinent factors in increasing landslides susceptibility. This project is a component of a wider initiative involving the Global Resource Information Database Europe from the United Nations Environment Programme, the International Union for Conservation of Nature, the Institute of Geomatics and Risk Analysis from the University of Lausanne and the "institut universitaire d'études du développement" from the University of Geneva.

This paper presents a model of factors influencing levels of human losses from natural hazards at the global scale, for the period 1980–2000. This model was designed for the United Nations Development Programme as a building stone of the Disaster Risk Index (DRI), which aims at monitoring the evolution of risk. Assessing what countries are most at risk requires considering various types of hazards, such as droughts, floods, cyclones and earthquakes. Before assessing risk, these four hazards were modelled using GIS and overlaid with a model of population distribution in order to extract human exposure. Human vulnerability was measured by crossing exposure with selected socio-economic parameters. The model evaluates to what extent observed past losses are related to population exposure and vulnerability. Results reveal that human vulnerability is mostly linked with country development level and environmental quality. A classification of countries is provided, as well as recommendations on data improvement for future use of the model.

The tsunami that deeply impacted the North Indian Ocean shores on 26 December 2004, called for urgent rehabilitation of coastal infrastructures to restore the livelihood of local populations. A spatial and statistical analysis was performed to identify what geomorphological and biological configurations (mangroves forests, coral and other coastal vegetation) are susceptible to decrease or increase coastal vulnerability to tsunami. The results indicate that the width of flooded land strip was, in vast majority, influenced by the distance to fault lines as well as inclination and length of proximal slope. Areas covered by seagrass beds were less impacted, whereas areas behind coral reefs were more affected. The mangroves forests identified in the study were all located in sheltered areas, thus preventing to address the potential protecting role of mangroves forests.

Understanding the complexity of earth-system processes is crucial to convey improved information on the environment to decision-makers and the general public. Addressing this need by sharing environmental data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. In this regard, the Global Earth Observation System of Systems (GEOSS) portends major benefits through various sharing mechanisms and by giving access to services that could be linked together to process and generate new understandable knowledge and information. Various United Nations projects could greatly benefit from the GEOSS approach.

In this chapter, two different types of impacts on human and ecological systems are examined: (i) impacts of extreme weather and climate events; and (ii) extreme impacts triggered by less-than-extreme weather or climate events (in combination with non-climatic factors, such as high exposure and/or vulnerability). Where data are available, impacts are examined from sectoral and regional perspectives.

Fossil fuels are essential for modern, mechanized agricultural production systems.

In the aftermath of the 2004 Indian Ocean tsunami, a large increase in the activity of tsunami hazard and risk mapping is observed. Most of these are site-specific studies with detailed modelling of the run-up locally. However, fewer studies exist on the regional and global scale. Therefore, tsunamis have been omitted in previous global studies comparing different natural hazards. Here, we present a first global tsunami hazard and population exposure study. A key topic is the development of a simple and robust method for obtaining reasonable estimates of the maximum water level during tsunami inundation. This method is mainly based on plane wave linear hydrostatic transect simulations, and validation against results from a standard run-up model is given. The global hazard study is scenario based, focusing on tsunamis caused by megathrust earthquakes only, as the largest events will often contribute more to the risk than the smaller events. Tsunamis caused by non-seismic sources are omitted. Hazard maps are implemented by conducting a number of tsunami scenario simulations supplemented with findings from literature. The maps are further used to quantify the number of people exposed to tsunamis using the Landscan population data set. Because of the large geographical extents, quantifying the tsunami hazard assessment is focusing on overall trends.

Allocating resources for natural hazard risk management has high priority in development banks and international agencies working in developing countries. Global hazard and risk maps for Rank landslides and avalanches were developed to identify the most ex- posed countries. Based on the global datasets of climate, lithology, earthquake activity, and topography, areas with the highest hazard, or “hotspots”, were identified. The applied model was based on classed values of all input data. The model output is a landslide and avalanche hazard index, which is globally scaled into nine levels. The model re- sults were calibrated and validated in selected areas where good data on slide events exist. The results from the landslide and avalanche hazard model together with global population data were then used as input for the risk assessment. Regions with the highest risk can be found in Colombia, Tajikistan, India, and Nepal where the estimated number of people killed per year per 100 km2 was found to be greater than one. The model made a reasonable prediction of the landslide hazard in 240 of 249 countries. More and better input data could im- prove the model further. Future work will focus on selected areas to study the applicability of the model on national and regional scales.

Biomass burning constitutes a major contribution to global emissions of carbon dioxide, carbon monoxide, methane, greenhouse gases and aerosols. Furthermore, biomass burning has an impact on health, transport, the environment and land use. Vegetation fires are certainly not recent phenomena and the impacts are not always negative. However, evidence suggests that fires are becoming more frequent and there is a large increase in the number of fires being set by humans for a variety of reasons. Knowledge of the interactions and feedbacks between biomass burning, climate and carbon cycling is needed to help the prediction of climate change scenarios. To obtain this knowledge, the scientific community requires, in the first instance, information on the spatial and temporal distribution of biomass burning at the global scale. This paper presents an inventory of burned areas at monthly time periods for the year 2000 at a resolution of 1 kilometer (km) and is available to the scientific community at no cost. The burned area products have been derived from a single source of satellite-derived images, the SPOT VEGETATION S1 1 km product, using algorithms developed and calibrated at regional scales by a network of partners. In this paper, estimates of burned area, number of burn scars and average size of the burn scar are described for each month of the year 2000. The information is reported at the country level. This paper makes a significant contribution to understanding the effect of biomass burning on atmospheric chemistry and the storage and cycling of carbon by constraining one of the main parameters used in the calculation of gas emissions.

Biomass burning constitutes a major contribution to global emissions of carbon dioxide, carbon monoxide, methane, greenhouse gases and aerosols. Furthermore, biomass burning has an impact on health, transport, the environment and land use. Vegetation fires are certainly not recent phenomena and the impacts are not always negative. However, evidence suggests that fires are becoming more frequent and there is a large increase in the number of fires being set by humans for a variety of reasons. Knowledge of the interactions and feedbacks between biomass burning, climate and carbon cycling is needed to help the prediction of climate change scenarios. To obtain this knowledge, the scientific community requires, in the first instance, information on the spatial and temporal distribution of biomass burning at the global scale. This paper presents an inventory of burned areas at monthly time periods for the year 2000 at a resolution of 1 kilometer (km) and is available to the scientific community at no cost. The burned area products have been derived from a single source of satellite-derived images, the SPOT VEGETATION S1 1 km product, using algorithms developed and calibrated at regional scales by a network of partners. In this paper, estimates of burned area, number of burn scars and average size of the burn scar are described for each month of the year 2000. The information is reported at the country level. This paper makes a significant contribution to understanding the effect of biomass burning on atmospheric chemistry and the storage and cycling of carbon by constraining one of the main parameters used in the calculation of gas emissions.

[1] The scientific community interested in atmospheric chemistry, gas emissions from vegetation fires, and carbon cycling is currently demanding information on the extent and timing of biomass burning at the global scale. In fact, the area and type of vegetation that is burned on a monthly or annual basis are two of the parameters that provide the greatest uncertainty in the calculation of gas and aerosol emissions and burned biomass. To address this need, an inventory of burned areas at monthly time periods for the year 2000 at a resolution of 1 km2 has been produced using satellite data and has been made freely available to the scientific community. In this paper, estimates of burned area and number of burn scars for four broad vegetation classes and reported at the country level for the year 2000 are presented using data taken from the inventory. Over 3.5 million km2 of burned areas were detected in the year 2000, of which approximately 80% occurred in areas described as woodlands and shrublands. Approximately 17% of the burned area occurred in grasslands and croplands, the remaining 3% occurred in forests. Almost 600,000 separate burn scars were detected. Descriptions of vegetation burning activity are given for ten regions. Finally, monthly burned area estimates are presented for the Central African Republic to illustrate the usefulness of these data for understanding, monitoring and managing vegetation burning activities.

Understanding the complexity of earth-system processes is crucial to convey improved information on the environment to decision-makers and the general public. Addressing this need by sharing environmental data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. In this regard, the Global Earth Observation System of Systems (GEOSS) portends major benefits through various sharing mechanisms and by giving access to services that could be linked together to process and generate new understandable knowledge and information. Various United Nations projects could greatly benefit from the GEOSS approach.