Europe's green arteries-A continental dataset of riparian zones

Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for improved ecosystem management, based on an accounting of changes and on monitoring of their functioning over time. In Europe, the main legislative driver behind this goal is the European Commission's Biodiversity Strategy to 2020, on the one hand aiming at halting biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as is feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%-1.19% of the study area can be attributed as actual riparian area (considering Strahler's stream orders 3-8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558-69,128 km2. Similarly, depending on the accounting approach, the potential riparian zones cover an area about 3-5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas. © 2016 by the authors

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth’s surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO) High-Resolution Layer (HRL) mapping of the HRL Forest for 20 Western, Central and (South)Eastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for

Operational monitoring services for our changing environment

With climate change speeding up and the on-going growth of the World’s population, the pressure on nature, biodiversity and our own living conditions increase steadily. To mitigate these threats, by effective adaptation strategies and counter measures, the frequent monitoring of our environment is crucial to provide decision makers and European citizens with accurate, up-to-date and reliable information on the changing conditions of our natural resources. Benefiting from Earth observation satellite data, the GMES Land Services provide such cross-border harmonised geo-information at global to local scales in a timely and cost-effective manner. These monitoring services have been defined, developed and implemented within a series of projects funded since 2003 by the European Commission (geoland, BOSS4GMES) and the European Space Agency (GSE Land / GSE Forest Monitoring). Building upon the results of the earlier projects, geoland2 now closes the gap between research and the operational implementation of fully mature GMES Land Services, consisting of Core Mapping Services and Core Information Services. The project aims to organise a qualified production network, to build, validate and demonstrate operational processing lines and to set-up a user driven product quality assurance process, to guarantee that the products meet the actual user requirements. The Core Mapping Services produce basic geo-information on land surfaces such as cover, use and biophysical parameters along with their annual and seasonal changes. This geo-information can thus describe, for instance, the continental vegetation state, the global radiation budget at the surface and the water cycle on the basis of satellite Earth observation data. The mapping products are of broad generic use being a very valuable information source in themselves. They also form the basis for more specialised geo-information services, i.e. the Core Information Services and further downstream applications. In geoland2 the Core Information Services offer specific information for European environmental policies and international treaties on climate change, food security and the sustainable development of Africa. Currently they address a broad variety of thematic fields, like for instance: water quality, forest managing, spatial planning, agri-environmental issues, the global carbon cycle, international food security, etc. In the framework of GMES for Africa, biophysical parameters have been provided to the AMESD (African Monitoring of the Environment for Sustainable Development) stations and specific e-tools are being tested to facilitate local data analysis supporting the sustainable management of natural resources.JRC.DDG.H.3-Global environement monitorin

Europe’s Green Arteries—A Continental Dataset of Riparian Zones

Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for improved ecosystem management, based on an accounting of changes and on monitoring of their functioning over time. In Europe, the main legislative driver behind this goal is the European Commission’s Biodiversity Strategy to 2020, on the one hand aiming at halting biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as is feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%–1.19% of the study area can be attributed as actual riparian area (considering Strahler’s stream orders 3–8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558–69,128 km2. Similarly, depending on the accounting approach, the potential riparian zones cover an area about 3–5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas

Europe's green arteries-A continental dataset of riparian zones

Riparian zones represent ecotones between terrestrial and aquatic ecosystems and are of utmost importance to biodiversity and ecosystem functions. Modelling/mapping of these valuable and fragile areas is needed for improved ecosystem management, based on an accounting of changes and on monitoring of their functioning over time. In Europe, the main legislative driver behind this goal is the European Commission's Biodiversity Strategy to 2020, on the one hand aiming at halting biodiversity loss, on the other hand enhancing ecosystem services by 2020, and restoring them as far as is feasible. A model, based on Earth Observation data, including Digital Elevation Models, hydrological, soil, land cover/land use data, and vegetation indices is employed in a multi-modular and stratified approach, based on fuzzy logic and object based image analysis, to delineate potential, observed and actual riparian zones. The approach is designed in an open modular way, allowing future modifications and repeatability. The results represent a first step of a future monitoring and assessment campaign for European riparian zones and their implications on biodiversity and on ecosystem functions and services. Considering the complexity and the enormous extent of the area, covering 39 European countries, including Turkey, the level of detail is unprecedented. Depending on the accounting modus, 0.95%-1.19% of the study area can be attributed as actual riparian area (considering Strahler's stream orders 3-8, based on the Copernicus EU-Hydro dataset), corresponding to 55,558-69,128 km2. Similarly, depending on the accounting approach, the potential riparian zones cover an area about 3-5 times larger. Land cover/land use in detected riparian areas was mainly of semi-natural characteristics, while the potential riparian areas are predominately covered by agriculture, followed by semi-natural and urban areas. © 2016 by the authors

Sentinel-based Evolution of Copernicus Land Services on Continental and Global Scale

Copernicus is a European Earth Observation (EO) programme headed by the European Commission (EC) in partnership with the European Space Agency (ESA) for the better understanding of the state and changes of our planet. Copernicus provides six operational services on the earth’s main sub-systems (i.e. Land, Atmosphere, Oceans) and on cross-cutting processes (i.e., Climate Change, Emergency and Security). These services are largely based on EO satellite data, which will rely on the fleet of ESA’s Sentinel satellites. The Copernicus Land Monitoring Service provides EO-based spatial information related to bio-geophysical variables and Land Cover/Land Use (LC/LU) characteristics as well as their changes over time. The related services are reflected in a Global, pan-European (Continental), Local Component, and an In-situ Component. The Horizon2020 project, “Evolution of Copernicus Land Services based on Sentinel data” (ECoLaSS), which will be implemented from 2017-2019 aims at developing innovative methods, algorithms and prototypes to improve and invent future pre-operational Copernicus Land services from 2020 onwards, for the pan-European and Global Components. ECoLaSS will make full use of dense Sentinel time series of optical (S-2, S-3) and Synthetic Aperture Radar (SAR) data (S-1). Rapidly evolving scientific as well as user requirements will be analyzed in support of a future pan-European roll-out of new/improved Copernicus Land Monitoring services, and the transfer to global applications. This paper will describe the ECoLaSS concept, explain the current status of Copernicus Land services, the envisaged methods for their production and present first analyses and examples. Service requirements assessment will be performed involving the main Copernicus Land stakeholders and users, and will thus steer methodological developments, such as: (i) Sentinel-1/-2/-3 time series integration, (ii) time series pre-processing methods, (iii) thematic classification and (iv) change detection from time series analysis, and (v) the development of an incremental update methodology for the Copernicus Land High Resolution Layers (HRLs). These methods will be applied on test sites, located both in Europe and Africa, prior to a prototyping phase. Larger demonstration sites representing various bio-geographic regions were selected to implement the following innovative prototypes: (i) indicators and variables from high spatial and temporal resolution data, for both the Continental and Global Component products; (ii) incremental update strategies for the main pan-European products (i.e. the HRLs); (iii) improved permanent grassland identification; (iv) crop area and crop status/parameters monitoring; (v) further novel LC/LU products. Finally, the main target to assess/benchmark all operational products in view of their innovation potential and technical excellence will be performed, leading to a strategy for an operationalization framework for a future pan-European roll-out of improved or newly developed Copernicus Land Monitoring services. ECoLaSS will promote the innovation potential of new land monitoring services and applications to diverse user communities. The project will thus contribute to a growing "Copernicus Economy" by boosting (new) Copernicus Land Services and value-added applications (Downstream Services). It is expected that such new services will provide a variety of inter-linkages with other LC/LU projects, and bring new opportunities for a wide range of dedicated applications to the market from 2020 onwards