@article{Kerzabi2021,

title = {Contribution of remote sensing and GIS to mapping groundwater vulnerability in arid zone: Case from Amour Mountains- Algerian Saharan Atlas},

author = {R. Kerzabi and H. Mansour and S. Yousfi and A. I. Marín and B. Andreo and K. E. Bensefia},

url = {https://doi.org/10.1016/j.jafrearsci.2021.104277},

doi = {https://doi.org/10.1016/j.jafrearsci.2021.104277},

year  = {2021},

date = {2021-10-01},

journal = {Journal of African Earth Sciences},

volume = {182},

number = {104277},

issue = {October 2021},

abstract = {Protecting groundwater resource from pollution in arid zone is coming an important act for sensing development in this region calling for geomatics tools to characterize the geological and hydrogeological environment. The present work gives a new way to combine remote sensing and geographic information systems to elaborate vulnerability map of Deffa watershed (in Amour Mountains). This region is a good example of arid zones how know an important growth of agriculture, but there is under gap of geological, hydrogeological and soil knowledge. In the first time, we analyzed the Landsat 8-OLI image data with bands combination, ratios composition in RGB and filters to cartography the lithology's contours and lineament map. The false color composition of bands (765, 753, and 543) in RGB given the primary lithological delimitation. Supported by band rationing technique, we produced of 1/50000 geological map. The filter treatments given the lineament map superposed to the first one to realize geo-structural map. In addition, these images served to elaborate pedology map, using Decision Tree (Slope, Redness Index and Lithology parameters). Secondly, we established a GIS including the result map of RS treatment (lithology, lineament and soil maps) and additional spatial information (aquifer type and deep of groundwater surface and precipitations …). In GIS, the vulnerability index are calculated using GOD and PI methods. Both of maps displayed four classes of vulnerability: between Low and Extreme in the first map, and Very low to High vulnerability in the second one. In the some areas, we have controversial values of vulnerability; this leads us to validate these maps using pollution indicators (NO3−, NH4+ and SO42−). The validation displayed that the PI coincides better with special concentrations of pollutants.},

keywords = {Climate Change, Conservation and management, Geotechnology, Groundwater, Pressures},

pubstate = {published},

tppubtype = {article}

}

@article{Weise2019,

title = {Wetland extent tools for SDG 6.6.1 reporting from the Satellite-based Wetland Observation Service (SWOS)},

author = {K. Weise and R. Höfer and J. Franke and A. Guelmami and W. Simonson and J. Muro and B. O'Connor and A. Strauch and S. Flink and J. Eberle and E. Mino and S. Thulin and P. Philipson and E. van Valkengoed and J. Truckenbrodt and F. Zander and A. Sánchez-Espinosa and C. Schröder and F. Thinfeld and E. Fitoka and E. Scott and M. Ling and M. Schwarz and I. Kunz and G. Thürmer and A. Plasmeijer and L. Hilarides},

url = {https://doi.org/10.1016/j.rse.2020.111892},

doi = {https://doi.org/10.1016/j.rse.2020.111892},

year  = {2019},

date = {2019-09-15},

journal = {Remote Sensing of Environment},

volume = {247},

abstract = {Wetlands are the most fragile and threatened ecosystems worldwide, and also one of the most rapidly declining. At the same time wetlands are typically biodiversity hotspots and provide a range of valuable ecosystem services, such as water supply and purification, disaster risk reduction, climate change adaptation, and carbon sequestration.



Pressures on wetlands are likely to further intensify in the coming decades due to increased global demand for land and water, and due to climate change. Stakeholders at all levels of governance have to be involved to slow, stop and reverse these processes. However, the information they need on wetland extent, their ecological character, and their ecosystem services is often scattered, sparse and difficult to find and access.



The freely available Sentinel satellite data of the Copernicus Programme, as well as the Landsat archive, provide a comprehensive basis to map and inventory wetland areas (extent), to derive information on the ecological status, as well as long- and short-term trends in wetland characteristics. However, making use of these Earth Observation (EO) resources for robust and standardized wetland monitoring requires expert knowledge on often complex data processing techniques, which impedes practical implementation. In this respect, the Satellite-based Wetland Observation Service (SWOS), a Horizon 2020 funded project (www.swos-service.eu) has developed and made disseminated monitoring approaches based on EO data, specifically designed for less experienced satellite data users.



The SWOS monitoring tools aim at assisting countries in conducting national wetland inventories for their Sustainable Development Goals (SDG) reporting and monitoring obligations, and additionally facilitates other monitoring obligations such as those required by the Ramsar Convention and supports decision-making in local conservation activities. The four main components of the SWOS approach are: map and indicator production; software development; capacity building; and initializing the GEO Wetlands Community Portal. Wetland managers and data analysists from more than fifty wetland sites and river basins across Europe, the Middle East, and Africa investigated the benefits and limitations of this EO-based wetland mapping and monitoring approach.



We describe research that applies the SWOS tools to test their potential for the mapping of wetlands in a case study based in Albania, and show its effectiveness to derive metrics relevant to the monitoring of SDG indicator 6.6.1.},

keywords = {Climate Change, Conservation and management, Environmental conservation, SWOS, Wetlands},

pubstate = {published},

tppubtype = {article}

}

@article{Hatziiordanou2019,

title = {Indicators for mapping and assessment of ecosystem condition and of the ecosystem service habitat maintenance in support of the EU Biodiversity Strategy to 2020},

author = {L. Hatziiordanou and E. Fitoka and E. Hadjicharalampous and N.E. Votsi and D. Palaskas and D. Abdul-Malak},

url = {https://oneecosystem.pensoft.net/article/32704/},

doi = {10.3897/oneeco.4.e32704},

year  = {2019},

date = {2019-06-13},

journal = {One Ecosystem},

volume = {4},

number = {e32704},

abstract = {A systematic approach to map and assess the “maintenance of nursery populations and habitats” ecosystem service (ES) (hereinafter called “habitat maintenance”) has not yet emerged. In this article, we present an ecosystem service framework implementation at landscape level, by proposing an approach for calculating and combining a series of indicators with spatial modelling techniques. Necessary conceptual elements for this approach are: a) ecosystem condition, b) supply and demand of the targeted ecosystem service and c) spatial relationships between the Service Providing Units (SPU) and the Service Connecting Units (SCU). Ecosystem condition is quantified and mapped based on two indicators, the Biodiversity State and the Anthropogenic Impact. Quantification and mapping of supply and demand are based on the hypothesis that high supply can be activated in strictly protected areas and that a demand is localised in the Natura 2000 sites (N2K), considering them as the Service Benefit Areas (SBA). Wetlands are assessed as SCU between the SBA and the landscape areas where the habitat maintenance ES is supplied. By assessing wetlands as SCU, we intent to highlight their role as biodiversity stepping stones and as green infrastructures. Overall, we conclude that the EU biodiversity policy demand for no net loss and for a coherent N2K network can be met by enhancing the delivery of the habitat maintenance ES. This approach can assist policy-makers in prioritisation of conservation and restoration targets, in line with the EU biodiversity strategy to 2020 and the preparation of the post-2020 Strategy.},

keywords = {Biodiversity, Climate Change, Conservation and management, Ecosystem services, Forest, Land and soil, Pressures, Wetlands},

pubstate = {published},

tppubtype = {article}

}

@article{Rodríguez-Rodríguez2016d,

title = {Achieving Blue Growth through maritime spatial planning: Offshore wind energy optimization and biodiversity conservation in Spain},

author = {D. Rodríguez-Rodríguez and D. Abdul-Malak and T. Soukissian and A. Sánchez-Espinosa},

url = {https://www.researchgate.net/publication/305824278_Achieving_Blue_Growth_through_maritime_spatial_planning_Offshore_wind_energy_optimization_and_biodiversity_conservation_in_Spain},

doi = {10.1016/j.marpol.2016.07.022},

year  = {2016},

date = {2016-11-01},

journal = {Marine Policy},

volume = {73},

pages = {8-14},

abstract = {Spain has a high potential for renewable energy production, being the world's third country by installed on-shore wind power. However, it has not yet fully developed its renewable energy production capacity, with no commercial offshore wind production to date, and remains highly dependent on fossil fuel imports. The country is also one of Europe's most biodiverse, on land and at sea. This study spatially assesses the country's offshore wind energy potential by incorporating the newly designated marine protected areas (MPAs) to the official Spanish strategic environmental assessment for the installation of offshore windfarms (SEA). It also identifies optimal areas for offshore windfarm development according to key physical variables such as wind speed, depth and substrate type. It finally assesses real commercial windfarm projects against current environmental constraints. The results show that nearly 50% of the whole area within 24 nm from the Spanish coast could be suitable for offshore windfarm development at the planning phase. However, only 0.7% of that area is optimal for wind energy production with current fixed turbine technology. Nevertheless, either area would allow Spain to meet its national targets of 750 MW of ocean power capacity installed by 2020 under adequate local wind conditions. Over 88% of all commercial windfarm project area is within the SEA's Exclusion zone, thus unfeasible under current circumstances. Technological breakthroughs like floating turbines may soon make the optimal windfarm area (OWA) less restrictive and reduce current environmental impacts of marine windfarms within a truly sustainable Blue Growth.},

keywords = {Biodiversity, Blue Growth, Climate Change, Conservation and management, Pressures},

pubstate = {published},

tppubtype = {article}

}

@article{Rodríguez-Rodrígueza2015,

title = {Cumulative pressures and low protection: a concerning blend for Mediterranean MPAs},

author = {D. Rodríguez-Rodríguez and A. Sánchez-Espinosa and C. Schröder and D. Abdul-Malak and J. Rodríguez},

url = {https://www.sciencedirect.com/science/article/pii/S0025326X15300540},

doi = {https://doi.org/10.1016/j.marpolbul.2015.09.039},

year  = {2015},

date = {2015-12-01},

journal = {Marine Pollution Bulletin},

volume = {101},

pages = {288-295},

abstract = {This study classifies Mediterranean marine protected areas (MPAs) according to the combined result of pressure level and protection. Six major marine environment pressures were considered: pressures from fish farms, fishing, marine litter, pressures from marinas, pollution from maritime transport, and climate change. MPA protection was assessed through legal protection and management effort. Most MPA area in the Mediterranean is under relatively high pressure level and afforded low protection. Inshore areas show higher pressure levels. Five marine ecoregions, nine countries and nineteen MPA designation categories have over 50% of their MPA area under major concern. The mean number of cumulative pressures occurring in priority MPAs ranges between three and four, although the mean combined intensity of those pressures is low. However, these figures are most likely underestimated, especially for the southern Mediterranean. The most concerning pressures to MPAs regarding extent and intensity were: climate change, fishing and pollution from maritime transport.},

keywords = {Climate Change, Marine protected areas, Mediterranean sea, Pressures},

pubstate = {published},

tppubtype = {article}

}

@article{Mancosu2015,

title = {Future land-use change scenarios for the Black Sea catchment},

author = {E. Mancosu and A. Gago-Silva and A. Barbosa and A. de Bono and E. Ivanov and A. Lehmann and J. Fons},

url = {https://www.sciencedirect.com/science/article/pii/S1462901114000550},

doi = {https://doi.org/10.1016/j.envsci.2014.02.008},

year  = {2015},

date = {2015-02-01},

journal = {Environmental Science & Policy},

volume = {46},

pages = {26-36},

abstract = {Plausible future scenarios have been created for the Black Sea catchment, focussing on spatially explicit alternatives for land-use changes. Four qualitative storylines (HOT, ALONE, COOP and COOL) were first developed, based on interpretation of the respective global scenarios (A1, A2, B1 and B2) produced by the Intergovernmental Panel on Climate Change. Quantitative statistical downscaling techniques were then used to disaggregate the outputs of global scenarios at a regional level. The resulting land-use maps were spatially allocated at 1 km resolution in the Metronamica model, using a set of factors related to the identified drivers of change. The land-use change model was calibrated on historical trends of land-cover change (MODIS 2001 and 2008) translated into spatial allocation rules, and future land-use projections (IMAGE, 2001) were adopted. Suitability and constraint maps and population trends were used to regulate the modelling process. The calibrated model was validated by statistical procedures, visual evaluation and stakeholder involvement in order to ensure its plausibility and accuracy. This methodology bridged the gap between the global and regional scales. Four simulated future states were produced for the main land-use classes–forest, grassland, cropland and built-up areas, as well as scrublands, crops/natural vegetation and barren land–for 2025 and 2050. The results suggest that the features highlighted in these scenarios are guided by global trends, such as population rise and decreasing agriculture, but with different growth rates and a variety of spatial patterns, with regional variations resulting from local backgrounds and policy objectives. This study aims to provide future land-use data as a potential geographical tool to assist policy makers in addressing environmental emergencies such as water stress and pollution. In particular, the exploration of plausible futures can support future assessments to comply with the EU Water Framework Directive and Integrated Coastal Zone Management policies around the Black Sea.},

keywords = {Climate Change, Geotechnology, Land and soil, Pressures},

pubstate = {published},

tppubtype = {article}

}

@article{Lehmann2015,

title = {Filling the gap between Earth observation and policy making in the Black Sea catchment with enviroGRIDS},

author = {A. Lehmann and G. Giuliania and E. Mancosu and K. C. Abbaspour and S. Sözen and D. Gorgan and A. Beel and N. Ray},

url = {https://www.sciencedirect.com/science/article/pii/S1462901114000525},

doi = {https://doi.org/10.1016/j.envsci.2014.02.005},

year  = {2015},

date = {2015-02-01},

journal = {Environmental Science & Policy},

volume = {46},

pages = {1-12},

abstract = {The environmental status of the Black Sea is obviously closely related to its catchment. Being a closed sea, this large water body drains an area of more than 2 million km2, encompassing 23 countries inhabited by more than 180 million people. The main environmental issues faced by the Black Sea catchment are the same as elsewhere in Europe. These problems are exacerbated by global changes with drastic changes predicted in temperature and precipitation by the end of the century, as well as land use and demographic changes. These environmental problems are taking place in a complex geopolitical situation. In this particular context, data sharing is essential to inform managers and policy-makers about the state of the environment, which will ultimately influence the state of the Black Sea itself. The enviroGRIDS project was set up in order to promote international data sharing initiatives such as the Global Earth Observation System of Systems and the European INSPIRE directive. The enviroGRIDS project was successful in reaching the following objectives: (a) performing a gap analysis on existing Earth observations systems in the region; (b) developing regional capacities at institutional, infrastructure and human resource levels; (c) creating regional scenarios to set the scene for plausible climatic, demographic and land use futures; (d) building the first hydrological model for the entire Black Sea catchment; (e) developing the Black Sea Catchment Observation System based on interoperability standards and Grid computing technologies; (f) showcasing data sharing in several case studies, addressing important environmental issues while building a network of people with improved capacity on data sharing principles. These relative successes should not, however, hide the difficulties in making the necessary Earth observation data available to scientists, decision makers and the public, as the mind-sets at all levels are changing slowly. Controlling the access to data is still perceived by many as a necessity to guarantee the power of the state on society and as a way to preserve its security. The need to develop national spatial data infrastructures (SDI) is very important to convince all ministries and data owner that publically funded data should be made publically available. The progress in the implementation of SDI seems more limited by political agendas than by technology. It is clear, however, that implementation of the INSPIRE directive in Europe is a prerequisite for the success of many other environmental policies (e.g. Water Framework Directive; Marine Strategy Framework Directive; Biodiversity strategy 2020).},

keywords = {Climate Change, Geotechnology, Pressures},

pubstate = {published},

tppubtype = {article}

}