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1 Geospatial Information and Earth Observations: Supporting Official Statistics in Monitoring the SDGs UNSC STATISTICAL-GEOSPATIAL INTEGRATION FORUM United Nations 7 March 2016 Session III. Geospatial and Earth Observations Data as Inputs to the Indicators Lawrence Friedl USA / NASA
2 Earth Observations & Geospatial Information Space-based Satellites Airborne Ground-based In Situ
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4 Some What Can Types We of See Earth With Observations Satellites... Land Temperature Sea Surface Temperature Vegetation Sea Surface Salinity Total Rainfall Aerosols Fires & Thermal Anomalies Chlorophyll Sea Surface Height
5 Some What Can Types We of See Earth With Observations Satellites... Environmental factors for malaria transmission Land Temperature Sea Surface Temperature Vegetation Sea Surface Salinity Total Rainfall Aerosols Fires & Thermal Anomalies Chlorophyll Sea Surface Height
6 Some What Can Types We of See Earth With Observations Satellites... Land Temperature Sea Surface Temperature Vegetation Environmental factors for fisheries management Sea Surface Salinity Total Rainfall Aerosols Fires & Thermal Anomalies Chlorophyll Sea Surface Height
7 Indicator Forest area as a percentage of total land area Target 15.1 By 2020 ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands Forest Area from Earth-observing Environmental Satellites 2000 % tree cover % tree cover Tree Cover Credit: Matthew C. Hansen, Univ. Maryland, et al.
8 Indicator Forest area as a percentage of total land area Target 15.1 By 2020 ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands... Forest Cover Trees greater than 16 feet tall and make up greater than 20 percent of the total vegetation cover. Data Source: U.S. National Land Cover Dataset based on Landsat satellites. Forests in Contiguous USA: 29% of land area (2011) US: Credit: NLCD
9 Indicator Forest area as a percentage of total land area Target 15.1 By 2020 ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands... Vietnam: Forest Cover Mapping 2000 % tree cover 2014 Total annual gross forest cover loss : 3.2 million ha. Credit: Matthew C. Hansen, Univ. Maryland, et al.
10 Indicator Forest area as a percentage of total land area Target 15.1 By 2020 ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands Gross Forest Cover Change: % tree cover Brazil Indonesia % 100% Annual forest loss, million ha Tree canopy cover Forest loss DRC << Annual loss shown using 3-year mean filter Credit: M. Hansen, UMd, et al.
11 Indicator Annual mean levels of fine particulate matter (i.e. PM2.5 and PM10) in cities (population weighted) Target 11.6 By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management Source: CIESIN Columbia University. Air Quality: Annual Average PM2.5 Grids Background image: Data from Circled values: Two-year ( ) country-specific values based on average population-weighted exposure. Data Source: Aerosol Optical Depth from MISR and MODIS sensors on Terra & Aqua satellites.
12 Indicator Annual mean levels of fine particulate matter (i.e. PM2.5 and PM10) in cities (population weighted) Target 11.6 By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management Source: CIESIN Columbia University. Air Quality: Annual Average PM2.5 Grids Background image: Data from Circled values: Two-year ( ) country-specific values based on average population-weighted exposure. Data Source: Aerosol Optical Depth from MISR and MODIS sensors on Terra & Aqua satellites
13 Other Examples & Pilots in Development Indicator 3.9.1: Population in urban areas exposed to outdoor air pollution levels above WHO guideline values Approach/Data Sources: US Census: Urban Areas in US (1:2000); Global gridded population dataset; Global population distribution at subnational level. NASA: EPA AIRNow pointbased air quality network; MERRA aerosol reanalysis. Indicator : Average share of the builtup area of cities that is open space in public use for all Approach/Data Sources: US Census: Vector data for infrastructure and public land ownership (1:2000); parcel data and municipal sources for open space definitions. NASA: Landsat-based mapping of land cover for urban areas and open space. Indicator : Percentage of land that is degraded over total land area. Approach/Data Sources: US Census: Gridded population distribution (100m grid) Demobase for Sub-Saharan Africa, others. NASA: Vegetation rigor from satellites (1981-present); 50cm satellite imagery; NASA GMAO reanalysis precipitation.
14 Other Examples & Pilots in Development Indicator 3.9.1: Population in urban areas exposed to outdoor air pollution levels above WHO guideline values Approach & Data Sources: US Census: Urban Areas in US (1:2000); Global gridded population dataset; Global population distribution at subnational level. NASA: EPA AIRNow point-based air quality network; MERRA aerosol reanalysis; Satellites. Air Quality ground monitor network; Satellite measurements Census population distribution
15 Earth Observations and Geospatial Information Support to SDGs Direct measures of some Indicators and indirect support to others. Contribute to progress on the Targets, which will show up in the Indicators.
16 Taking it to scale... Next Steps Work with statistical agencies to ensure the methods are sound for use with Indicators and Targets Ensure the methods and solutions are available for all to use Support countries and stakeholders to use the methods and build capacity
17 Taking it to scale... Next Steps Work with statistical agencies to ensure the methods are sound for use with Indicators and Targets Ensure the methods and solutions are available for all to use Support countries and stakeholders to use the methods and build capacity others
18 Training: Earth Observations & SDGs NASA offers hands-on training courses to build skills in accessing and using Earth observations data through computer-based sessions for professionals. We will design ones specific to SDG topics and audiences. Webinars In person Introductory Advanced Air Quality Water Resources Flooding Ecosystems Drought Land Management Conservation Health (new in 2016) Others TBD 2015: 11 Trainings with 2,877 Participants, 123 Countries and 1,021 Organizations
19 Training: Earth Observations & SDGs NASA offers hands-on training courses to build skills in accessing and using Earth observations data through computer-based sessions for professionals. We will design ones specific to SDG topics and audiences. Webinars In person Introductory Advanced 2015: 11 Trainings with 2,877 Participants, 123 Countries and 1,021 Organizations Air Quality Water Resources Flooding Ecosystems Drought Land Management Conservation Health (new in 2016) Others TBD Which topics does UNSC suggest for ?
20 GEO Initiative 18: Earth Observations in Service of the 2030 Agenda for Sustainable Development Image Credit: The Economist, 2003
21 Geospatial Information and Earth Observations: Supporting Official Statistics in Monitoring the SDGs UNSC STATISTICAL-GEOSPATIAL INTEGRATION FORUM United Nations 7 March 2016 Session III. Geospatial and Earth Observations Data as Inputs to the Indicators Additional Materials
22 Data models that use gridded population data Source: CIESIN Columbia University.
23 Indicator Forest area as a percentage of total land area Target 15.1 By 2020 ensure the conservation, restoration and sustainable use of terrestrial and inland freshwater ecosystems and their services, in particular forests, wetlands, mountains and drylands... Vietnam: Forest Cover Mapping 2000 % 2000 tree cover Credit: Matthew C. Hansen, Univ. Maryland, et al.
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