The practice of raw material extraction has a high impact on the environment and represents a potential threat to the health and thriving of local communities.The concept of Extractive Essential Variables(EEVs)are exp...The practice of raw material extraction has a high impact on the environment and represents a potential threat to the health and thriving of local communities.The concept of Extractive Essential Variables(EEVs)are explored in order to propose variables that can be used to quantify the environmental footprint of mineral extraction.Considering the interdependence of mining activities with social,economic and environmental issues,the variables target the development of monitoring tools for the implementation of the Sustainable Development Goals(SDGs).The identification of EEVs is based on the use of Earth Observation products in the field of mineral resources exploitation.A list of variables is proposed based on three classes of Essential Variables(EVs):installation and exploration phase,mineral extraction,and ore processing.These variables take into account the impacts of mining on the hydrology,land,water resources and the atmosphere of the area subjected to mineral exploitation.One of the variables is implemented as an operational workflow addressing SDG15,“life on land”.The workflow is intended to assess the area of forest ecosystem lost due to the presence of a mining site.Geospatial data on the extent of mining concessions and forest cover are combined using ArcGIS^(TM).The workflow is successively translated into a Unix script to automatize the process of data treatment.The script is developed using the Geospatial Data Abstraction Library(GDAL).The use of a Virtual Laboratory Platform(VLab),a web-service-based access platform,increases the accessibility of data and resources and the re-use of the script.This work is a first attempt to propose a framework of EEVs,derived data workflows,while the underlying methodology,partially based on scientific publications and on personal reasoning,still needs to be tested and,improved based on expertise in the sector.展开更多
Exacerbated by climate change,Europe has experienced series of hot and dry summer since the beginning of the 21st century.The importance of land conditions became an international concern with a dedicated sustainable ...Exacerbated by climate change,Europe has experienced series of hot and dry summer since the beginning of the 21st century.The importance of land conditions became an international concern with a dedicated sustainable development goal(SDG),the SDG 15.It calls for developing and finding innovative solu-tions to follow and evaluate impacts of changing land condi-tions induced by various driving forces.In Switzerland,drought risk will significantly increase in the coming decades with severe consequences on agriculture,energy production and vegeta-tion.In this paper,we used a 35-year satellite-derived annual and seasonal times-series of normalized difference water index(NDWI)to follow vegetation water content evolution at different spatial and temporal scales across Switzerland and related them to temperature and precipitation to investigate possible responses of changing climatic conditions.Results indicate that there is a small and slow drying tendency at the country scale with a NDWI mean decreasing slope of−0.22%/year for the 23%significant pixels across Switzerland.This tendency is mostly visible below 2000 m above sea level(m.a.s.l.)and in all biogeographical regions.The Southern Alps regions appear to be more responsive to changing drying conditions with a significant and slight negative NDWI trend(−0.39%/year)over the last 35 years.Moreover,NDWI values are mostly a func-tion of temperature at elevations below the tree line rather than precipitation.Findings suggest that multi-annual and seasonal NDWI can be a valuable indicator to monitor vegetation water content at different scales,but other components such as land cover type and evapotranspiration should be considered to better characterize NDWI variability.Satellite Earth Observations data can provide valuable complementary obser-vations for national statistics on the ecological state of vegeta-tion to support SDG 15 to monitor land affected by drying conditions.展开更多
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...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 efficient 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 significantly 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.展开更多
Avoiding,reducing,and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth.To halt and reverse the current tre...Avoiding,reducing,and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth.To halt and reverse the current trends in land degradation,there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands,as required by the Sustainable Development Goals(SDGs),in particular,the SDG indicator 15.3.1(“proportion of land that is degraded over total land area”).Earth Observations(EO)can play an important role both for generating this indicator as well as complementing or enhancing national official data sources.Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR.Consequently,there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data(e.g.Landsat or Sentinels).In response to this issue,this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators.展开更多
基金The authors would like to acknowledge the European Commission“Horizon 2020 Program”that funded ERAPLANET/GEOEssential project(Grant Agreement no.689443).
文摘The practice of raw material extraction has a high impact on the environment and represents a potential threat to the health and thriving of local communities.The concept of Extractive Essential Variables(EEVs)are explored in order to propose variables that can be used to quantify the environmental footprint of mineral extraction.Considering the interdependence of mining activities with social,economic and environmental issues,the variables target the development of monitoring tools for the implementation of the Sustainable Development Goals(SDGs).The identification of EEVs is based on the use of Earth Observation products in the field of mineral resources exploitation.A list of variables is proposed based on three classes of Essential Variables(EVs):installation and exploration phase,mineral extraction,and ore processing.These variables take into account the impacts of mining on the hydrology,land,water resources and the atmosphere of the area subjected to mineral exploitation.One of the variables is implemented as an operational workflow addressing SDG15,“life on land”.The workflow is intended to assess the area of forest ecosystem lost due to the presence of a mining site.Geospatial data on the extent of mining concessions and forest cover are combined using ArcGIS^(TM).The workflow is successively translated into a Unix script to automatize the process of data treatment.The script is developed using the Geospatial Data Abstraction Library(GDAL).The use of a Virtual Laboratory Platform(VLab),a web-service-based access platform,increases the accessibility of data and resources and the re-use of the script.This work is a first attempt to propose a framework of EEVs,derived data workflows,while the underlying methodology,partially based on scientific publications and on personal reasoning,still needs to be tested and,improved based on expertise in the sector.
文摘Exacerbated by climate change,Europe has experienced series of hot and dry summer since the beginning of the 21st century.The importance of land conditions became an international concern with a dedicated sustainable development goal(SDG),the SDG 15.It calls for developing and finding innovative solu-tions to follow and evaluate impacts of changing land condi-tions induced by various driving forces.In Switzerland,drought risk will significantly increase in the coming decades with severe consequences on agriculture,energy production and vegeta-tion.In this paper,we used a 35-year satellite-derived annual and seasonal times-series of normalized difference water index(NDWI)to follow vegetation water content evolution at different spatial and temporal scales across Switzerland and related them to temperature and precipitation to investigate possible responses of changing climatic conditions.Results indicate that there is a small and slow drying tendency at the country scale with a NDWI mean decreasing slope of−0.22%/year for the 23%significant pixels across Switzerland.This tendency is mostly visible below 2000 m above sea level(m.a.s.l.)and in all biogeographical regions.The Southern Alps regions appear to be more responsive to changing drying conditions with a significant and slight negative NDWI trend(−0.39%/year)over the last 35 years.Moreover,NDWI values are mostly a func-tion of temperature at elevations below the tree line rather than precipitation.Findings suggest that multi-annual and seasonal NDWI can be a valuable indicator to monitor vegetation water content at different scales,but other components such as land cover type and evapotranspiration should be considered to better characterize NDWI variability.Satellite Earth Observations data can provide valuable complementary obser-vations for national statistics on the ecological state of vegeta-tion to support SDG 15 to monitor land affected by drying conditions.
基金The authors would like to thank the Swiss Federal Office for the Environment(FOEN)for their financial support to the Swiss Data Cube.
文摘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 efficient 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 significantly 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.
基金This research was funded by the European Commission“Horizon 2020 Program”ERA-PLANET/GEOEssential project,grant number 689443.
文摘Avoiding,reducing,and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth.To halt and reverse the current trends in land degradation,there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands,as required by the Sustainable Development Goals(SDGs),in particular,the SDG indicator 15.3.1(“proportion of land that is degraded over total land area”).Earth Observations(EO)can play an important role both for generating this indicator as well as complementing or enhancing national official data sources.Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR.Consequently,there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data(e.g.Landsat or Sentinels).In response to this issue,this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators.
