A Webinar hosted by NASA Earthdata on November 30 featured CIESIN deputy director Alex de Sherbinin and research scientist Susana Adamo presenting air quality data sets distributed by the NASA Socioeconomic Data and Applications Center (SEDAC). The Webinar covered global gridded and tabular country and city trend data for particulate matter and other pollutants, and grids focusing on the United States for particulate matter, ozone, and nitrogen-dioxide. The Webinar also demonstrated the use of these data products with a variety of SEDAC data sets—Gridded Population of the World (GPWv4), Social Vulnerability Grids, and the recently released Global Relative Deprivation Index—to study health impacts and environmental justice.
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Climate change disproportionately affects the poor and socially vulnerable. The scientific community is responding in its commitment to data and services development that can advance environmental justice. A recent NASA Earthdata Backgrounder profiles some of the work the NASA Socioeconomic Data and Application Center (SEDAC) is doing in this area.
The backgrounder describes a research project focused on the low-wealth, predominately Black community of the Hampton Roads region of Norfolk, VA, which is experiencing rising sea level rise in part because the land area is sinking. SEDAC population data was paired with satellite data to reveal high population density combined with anomalously high sea surface height in this area, identifying high vulnerability. Integrating different types of data in this way lets planners and policymakers make better-informed mitigation decisions that take into consideration social as well as physical impacts of sea-level rise, better insuring environmental justice for vulnerable communities.
In a second example, in collaboration with the International Research Institute for Climate and Society (IRI), SEDAC helped develop an index that assesses flood vulnerability for Harris County, Texas. Taking a multidisciplinary approach to capturing resilience and susceptibility to flooding, 15 indicators were combined into an aggregate index. The tool can visualize flood vulnerability at the block group level for Harris County and analyze relative flood vulnerability across the region, improving prioritization of flood remediation policies and aid.
CIESIN director Robert Chen, with associate director for Science Applications Alex de Sherbinin and research scientist Susana Adamo, helped organize and co-lead a NASA Equity and Environmental Justice virtual workshop, in their respective SEDAC roles as manager, deputy manager, and project scientist. The workshop report was released in December 2021.
SEDAC manager Robert Chen, with deputy manager Alex de Sherbinin and project scientist Susana Adamo, helped organize and co-lead the NASA Equity and Environmental Justice virtual workshop held October 20, 2021. NASA Earth Science Division (ESD) director Karen St. Germain opened the event, which brought together 15 invited experts, including SEDAC User Working Group (UWG) chair Barbara Ryan and several other UWG members, ESD staff, and representatives from social science research organizations who engage with environmental justice (EJ) research and communities. Chen, de Sherbinin, and Adamo co-led several breakout groups, working closely with SEDAC program scientist Nancy Searby and other NASA staff. The workshop report is now available.
In early 2021, a Biden administration executive order on equity directed all federal agencies to incorporate achieving environmental justice in their missions. In June 2021, NASA launched Mission Equity, a comprehensive effort to assess expansion and modification of agency programs, procurements, grants, and policies, and examine potential barriers and challenges for historically underrepresented and underserved communities.
This summer has seen a spate of extreme climate-related events, from record high temperatures to forest fires, floods, and severe storms. Climate and other natural and manmade hazards do not affect all populations equally. Some sub-populations are particularly vulnerable to their effects owing to factors such as low income, lower levels of education, poor housing, or historical inequalities. Parsing out the fine-grained layers of social conditions across the strata of society—how much money people make, who makes up their households, minority status, ability to understand English, dwelling places, and access to transport—can provide the fundamental elements needed to quantify social vulnerability to hazards in the United States. The Centers for Disease Control (CDC) Social Vulnerability Index (SVI), created by the Geospatial Research, Analysis, and Services Program (GRASP) of the Centers for Disease Control and Prevention (CDC) and the Agency for Toxic Substances and Disease Registry (ATSDR), has long been a key resource for local officials to identify communities that may need support before, during, or after hazardous events or disease outbreaks.
To increase the utility of the SVI data set, the NASA Socioeconomic Data and Applications Center (SEDAC) operated by CIESIN gridded the input data and removed uninhabited areas. The resulting data set, the U.S. Social Vulnerability Index (SVI) Grids, enables calculation of the SVI for user-defined areas, facilitating integration with hazard and other geospatial data. The gridded SVI data set uses the same four themes as the CDC/ATSDR index—Socioeconomic, Household Composition and Disability, Minority Status and Language, and Housing Type and Transportation—to rank communities on vulnerability for the entire United States. The SVI data set is based on inputs at the census-tract level for 15 variables for the years 2000, 2010, 2014, 2016, and 2018, and aligns with the Gridded Population of the World (GPW) data set, SEDAC′s flagship data collection.
A map gallery includes an overall SVI map and four maps visualizing each of the themes. Development of the gridded data set and maps was led by Carolynne Hultquist, post-doctoral research scientist at CIESIN.
The NASA Socioeconomic Data and Applications Center (SEDAC) operated by CIESIN has released several new data sets related to hazards, infant mortality, and future socioeconomic scenarios. The Geocoded Disasters (GDIS) Dataset is a geocoded extension of a selection of natural disasters from the Centre for Research on the Epidemiology of Disaster (CRED) Emergency Events Database (EM-DAT). The data set includes nearly 40,000 locations for almost 10,000 disasters worldwide for the 58-year period spanning 1960–2018. It encompasses all EM-DAT-recorded floods, storms, earthquakes, landslides, droughts, volcanic activity and extreme temperatures, some at administrative level 3 (district/commune/village) but most at 1 (typically state/province/region). GDIS facilitates geospatial analysis of past hazard events.
The Shared Socioeconomic Pathways (SSPs) Literature Database consists of biographic information, abstracts, and analysis of 1,360 articles published 2014–2019 that make substantial use of the SSPs. The database was developed by Carole Green et al. as the basis for a recent article in Nature Climate Change that analyzes use of the Climate Change Scenario Framework and associated scenario data sets in diverse application areas and in assessments of the Intergovernmental Panel on Climate Change (IPCC). The International Committee on New Integrated Climate Change Assessment Scenarios (ICONICS) is planning to extend the literature database. SEDAC User Working Group member Brian O'Neill of the Joint Climate Change Research Institute and CIESIN director Robert Chen are members of ICONICS.
Global Subnational Infant Mortality Rates (IMR), Version 2.01, provides more recent and higher-resolution infant mortality data, including estimates of births and infant deaths. The estimates are for 234 countries and territories, 143 of which include subnational units and are benchmarked to the year 2015 (versus year 2000 for the first version). IMR data are drawn from national offices, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other sources covering 2006–2014. The birth and infant death data can be aggregated or disaggregated to calculate IMRs at different scales or resolutions. Boundary inputs are derived primarily from the Gridded Population of the World, Version 4 (GPWv4) data collection. National and subnational data are mapped at a spatial resolution of 30 arc-seconds (~1 km at the equator), facilitating integration with demographic, environmental, and other spatial data. Data set development was led by senior geographic information specialist Dara Mendeloff and research scientist Susana Adamo.
The data set, Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, 2020–2100, contains county-level population projection scenarios of total population, and by age, sex, and race in five-year intervals for all US counties 2020–2100. These data can serve as inputs for addressing questions involving sub-national demographic change in the United States in the near, middle- and long-term.
CIESIN has developed and released several new data sets recently. Now available from the NASA Socioeconomic Data and Applications Center (SEDAC) is the Food Insecurity Hotspots data set, which consists of gridded data identifying the level of intensity and frequency of food insecurity over ten years between 2009 and 2019, as well as hotspots of consecutive food insecurity events. The data set covers five regions: Central America and the Caribbean, Central Asia, East Africa, Southern Africa, and West Africa. The grids are at 250 meter (~7.2 arc-seconds) resolution and are based on subnational food security analyses for these regions provided by the Famine Early Warning Systems Network (FEWS NET). FEWS NET was established in 1985 by the U.S. Agency for International Development (USAID).
As part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) program managed by CIESIN, data on operational settlement points and/or boundaries, health facilities, and points of interests have been released for Zambia and the Democratic Republic of the Congo. Settlement extent data are now available for 41 African countries, created from Digitize Africa building footprints powered by Maxar. GRID3 has expedited settlement extent mapping to support countries in their COVID-19 response efforts. The data are broadly intended to support country decision-making in public health and education.
The POPGRID Data Collaborative, an initiative launched by CIESIN in 2017 to improve the quality, access, and use of global-scale spatial data on human population, settlements, and infrastructure, has recently updated its Web site and announced an international Webinar to be held February 4 in collaboration with Geospatial World.
The POPGRID Web site helps users learn about the many different gridded population data sets now available, providing detailed background information and documentation, and direct links to the data and data sources. In addition, the POPGRID Viewer lets users easily compare different data products for their specific regions of interest. The updated site now includes links to recent publications and recorded Webinars about gridded population data, together with updated information from the data providers. POPGRID is collaboratively managed by CIESIN, the Thematic Research Network on Data and Statistics (TReNDS) of the United Nations Sustainable Development Solutions Network, and the Global Partnership for Sustainable Development Data, and is supported by the Bill & Melinda Gates Foundation and NASA. More than 20 different groups from both the public and private sectors are active in the POPGRID Data Collaborative. The POPGRID Viewer was developed by the NASA Socioeconomic Data and Applications Center (SEDAC) operated by CIESIN.
On February 4, CIESIN director Robert Chen and Maryam Rabiee of TReNDS presented the Webinar, “Leaving No One Off the Map: Gridded Population Data for Decision Making,″ in coordination with Geospatial World. It attracted 150 participants from around the world. The Webinar focused on how gridded population data can help decision makers and other applied users improve efforts to achieve the Sustainable Development Goals (SDGs) adopted by the international community in 2015, and in particular to help reach those who might otherwise be left behind. Recent advances in mapping make it possible to better determine the location and characteristics of human settlements and households, allowing for more effective and efficient assistance, e.g., for vaccination campaigns, development assistance, and humanitarian relief. However, the proliferation of different data sets utilizing different methods and sources may confuse users about which data sets are the most appropriate to use in different situations. The Webinar discussed ongoing efforts by the POPGRID Data Collaborative to address this issue, and ways in which the geospatial community can both benefit from, and participate in, POPGRID activities. A recording is available here.
The NASA Socioeconomic Data and Applications Center (SEDAC) operated by CIESIN has released two new data sets, one focused on a new approach for assessing urban extent in the continental U.S. and a second that estimates the potential exposure of major food crops around the world to selected chemicals used in pesticides.
Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods is a highly accurate urban settlement layer at a spatial resolution of 500 meters that is based in part on nighttime lights data from NASA’s Black Marble project. Machine learning methods were used to provide a more consistent, quantitative measure of urban extent, drawing on observations collected at high temporal frequency by the Visible Infrared Imaging Radiometer Suite (VIIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing instruments. The data set was developed by former CIESIN scientist Xue Liu, now at Harvard University′s Center for Geographic Analysis, together with SEDAC deputy manager Alex de Sherbinin and former staff member Yanni Zhan. The derivation of the data set is described in a recent open access article by Liu et al. in the journal Remote Sensing.
The Global Pesticide Grids (PEST-CHEMGRIDS) data set was developed by Federico Maggi of the University of Sydney and colleagues, to assess human and ecosystem exposure to potential and recognized toxic chemicals, for the purposes of environmental modelling and assessment of agricultural chemical contamination and risk. PEST-CHEMGRIDS includes comprehensive data on the 20 most-used pesticide active ingredients, on six dominant crops and four aggregated crop classes, at 5 arc-minute resolution (about 10 kilometers at the equator), estimated for the year 2015 and projected to 2020 and 2025. The data set includes 200 data quality maps for each active ingredient on each crop. The data set is described in detail in a recent open access paper by Maggi et al. published in the journal Scientific Data.
These data are distributed as part of SEDAC′s mission to archive and disseminate key socioeconomic and related environmental data sets that either utilize or complement satellite-based remote sensing data, in support of scientific research, applications, and education. Data selection is overseen by SEDAC′s User Working Group (UWG). Data set authors are invited to submit their data for possible SEDAC archiving and open dissemination; for the submission criteria and form, please see the SEDAC Data Submission page.
TerraViva! SEDAC Viewer is a map viewer and standalone software application that uses a powerful data-viewing engine and tools to enable the visualization and integration of hundreds of socioeconomic and environmental variables and layers, including a range of satellite-based data. A three-part tutorial that explains how to use TerraViva! is now available through the YouTube Web site. The tutorial was produced by senior research associate Alex de Sherbinin and senior media designer Al Pinto, under the auspices of the NASA Socioeconomic Data and Applications Center (SEDAC) operated by CIESIN.
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