The POPGRID Data Collective: Advancing the Use and Impact of Geospatial Population and Infrastructure Data

Authors: Robert Chen*, CIESIN/Columbia University, Gregory Yetman, CIESIN, Columbia University
Topics: Human-Environment Geography, Population Geography, Hazards and Vulnerability
Keywords: population distribution, built infrastructure, settlement patterns, urbanization, hazard exposure, vulnerability, sustainable development
Session Type: Paper
Day: 4/14/2018
Start / End Time: 2:00 PM / 3:40 PM
Room: Studio 10, Marriott, 2nd Floor
Presentation File: No File Uploaded

The number and variety of data products on the spatial distribution of human settlements, population, and infrastructure from local to global scales continue to increase, utilizing a wide range of inputs including census records, administrative boundary data, and remote sensing data including radar, night-time lights, and medium- and high-resolution imagery. These data have diverse applications in areas such as humanitarian assistance, disaster mitigation, assessment of climate vulnerability, development of sustainable development indicators, natural resource management, transportation planning, poverty reduction, and conservation. However, there has been relatively little effort to date to develop consistent terminology, clear documentation, formal intercomparison and validation studies, data quality metrics, and resources to help users determine which data are most appropriate for different applications. The POPGRID Data Collective has been formed to bring together the relevant data providers, users, and other stakeholders from both the public and private sectors to accelerate the development and use of high quality, highly usable georeferenced data on population, human settlements, and infrastructure. Specific objectives are to: share resources; improve data quality and documentation; clarify user needs and priorities; address scientific and technical challenges; and facilitate appropriate data use and interpretation in a range of sustainable development application areas. We report here on progress to date in improving data accessibility, quality, metadata, interoperability, intercomparison, validation, and use, and in establishing a framework for long-term community collaboration and development.

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