The Experts below are selected from a list of 77823 Experts worldwide ranked by ideXlab platform
Alexander J. Tatem - One of the best experts on this subject based on the ideXlab platform.
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high resolution Population distribution maps for southeast asia in 2010 and 2015
PLOS ONE, 2013Co-Authors: Andrea E Gaughan, Forrest R Stevens, Catherine Linard, Alexander J. TatemAbstract:Spatially accurate, contemporary data on human Population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and Population growth over the past decade, yet existing spatial Population distribution datasets covering the region are based principally on Population Count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) Population distribution datasets for each Country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model Population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global Population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable Population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.
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Population distribution settlement patterns and accessibility across africa in 2010
PLOS ONE, 2012Co-Authors: Catherine Linard, Abdisalan M Noor, Robert W Snow, Marius Gilbert, Alexander J. TatemAbstract:The spatial distribution of Populations and settlements across a Country and their interconnectivity and accessibility from urban areas are important for delivering healthcare, distributing resources and economic development. However, existing spatially explicit Population data across Africa are generally based on outdated, low resolution input demographic data, and provide insufficient detail to quantify rural settlement patterns and, thus, accurately measure Population concentration and accessibility. Here we outline approaches to developing a new high resolution Population distribution dataset for Africa and analyse rural accessibility to Population centers. Contemporary Population Count data were combined with detailed satellite-derived settlement extents to map Population distributions across Africa at a finer spatial resolution than ever before. Substantial heterogeneity in settlement patterns, Population concentration and spatial accessibility to major Population centres is exhibited across the continent. In Africa, 90% of the Population is concentrated in less than 21% of the land surface and the average per-person travel time to settlements of more than 50,000 inhabitants is around 3.5 hours, with Central and East Africa displaying the longest average travel times. The analyses highlight large inequities in access, the isolation of many rural Populations and the challenges that exist between Countries and regions in providing access to services. The datasets presented are freely available as part of the AfriPop project, providing an evidence base for guiding strategic decisions.
John Quinn - One of the best experts on this subject based on the ideXlab platform.
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identifying seasonal mobility profiles from anonymized and aggregated mobile phone data application in food security
PLOS ONE, 2018Co-Authors: Pedro J. Zufiria, David Pastorescuredo, Luis Ubedamedina, Miguel A Hernandezmedina, Iker Barrialesvalbuena, Alfredo J Morales, Damien Christophe Jacques, Wilfred Nkwambi, Bamba M Diop, John QuinnAbstract:We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a Population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale Population Count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable Populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.
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Seasonal mobility profiles in each livelihood zone.
2018Co-Authors: Pedro J. Zufiria, Alfredo J Morales, Wilfred Nkwambi, Bamba M Diop, David Pastor-escuredo, Luis Úbeda-medina, Miguel A. Hernandez-medina, Iker Barriales-valbuena, Damien C. Jacques, John QuinnAbstract:They are clustered with k = 3: yellow, red and orange. Each curve represents z-scored values of the Population Count Livelihood zones 1-13 (see S1 Fig) are ordered up-down, left-right. Cyan curves show the rainfall estimations averaged by livelihood zone, whereas black curves show the NDVI estimation averaged by livelihood zone. Both rain and NDVI curves have been rescaled to fit the scale of the Population Count signatures.
Christopher D. Elvidge - One of the best experts on this subject based on the ideXlab platform.
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a global poverty map derived from satellite data
Computers & Geosciences, 2009Co-Authors: Christopher D. Elvidge, Benjamin T. Tuttle, Paul C. Sutton, Tilottama Ghosh, Kimberly E Baugh, Budhendra L Bhaduri, Eddie A BrightAbstract:A global poverty map has been produced at 30arcsec resolution using a poverty index calculated by dividing Population Count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.
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paving the planet impervious surface as proxy measure of the human ecological footprint
Progress in Physical Geography, 2009Co-Authors: Paul C. Sutton, Benjamin T. Tuttle, Christopher D. Elvidge, Sharolyn Anderson, Tilottama GhoshAbstract:Fundamental questions regarding the human-environment-sustainability problematic remain contested. What are the relative roles of Population, consumption, and technology with respect to sustainability? How can sustainability be measured? Numerous metrics have been developed to address these controversial questions including ideas of carrying capacity, environmental sustainability indices, and ecological footprints. This work explores the question: is pavement a proxy measure of human impact on the environment? We explore and evaluate the use of satellite derived density grids of constructed area (aka ‘pavement’ or ‘impervious surface’) in the calculation of national and subnational ‘ecological footprints’. We generated a global constructed area density grid for the 2000—2001 period using satellite observed nighttime lights and a Population Count grid from the US Department of Energy. Satellite data inputs to the Population product include MODIS landcover, SRTM topography and high-resolution imagery. Calib...
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Global Distribution and Density of Constructed Impervious Surfaces
Sensors, 2007Co-Authors: Christopher D. Elvidge, Ara T. Howard, Benjamin T. Tuttle, K. E. Baugh, Paul C. Sutton, Cristina Milesi, Budhendra BhaduriAbstract:We present the first global inventory of the spatial distribution and density of constructed impervious surface area (ISA). Examples of ISA include roads, parking lots, buildings, driveways, sidewalks and other manmade surfaces. While high spatial resolution is required to observe these features, the new product reports the estimated density of ISA on a one-km2 grid based on two coarse resolution indicators of ISA – the brightness of satellite observed nighttime lights and Population Count. The model was calibrated using 30-meter resolution ISA of the USA from the U.S. Geological Survey. Nominally the product is for the years 2000-01 since both the nighttime lights and reference data are from those two years. We found that 1.05% of the United States land area is impervious surface (83,337 km2) and 0.43 % of the world’s land surface (579,703 km2) is constructed impervious surface. China has more ISA than any other Country (87,182 km2), but has only 67 m2 of ISA per person, compared to 297 m2 per person in the USA. The distribution of ISA in the world’s primary drainage basins indicates that watersheds damaged by ISA are primarily concentrated in the USA, Europe, Japan, China and India. The authors believe the next step for improving the product is to include reference ISA data from many more areas around the world.
Pedro J. Zufiria - One of the best experts on this subject based on the ideXlab platform.
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identifying seasonal mobility profiles from anonymized and aggregated mobile phone data application in food security
PLOS ONE, 2018Co-Authors: Pedro J. Zufiria, David Pastorescuredo, Luis Ubedamedina, Miguel A Hernandezmedina, Iker Barrialesvalbuena, Alfredo J Morales, Damien Christophe Jacques, Wilfred Nkwambi, Bamba M Diop, John QuinnAbstract:We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a Population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale Population Count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable Populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.
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Seasonal mobility profiles in each livelihood zone.
2018Co-Authors: Pedro J. Zufiria, Alfredo J Morales, Wilfred Nkwambi, Bamba M Diop, David Pastor-escuredo, Luis Úbeda-medina, Miguel A. Hernandez-medina, Iker Barriales-valbuena, Damien C. Jacques, John QuinnAbstract:They are clustered with k = 3: yellow, red and orange. Each curve represents z-scored values of the Population Count Livelihood zones 1-13 (see S1 Fig) are ordered up-down, left-right. Cyan curves show the rainfall estimations averaged by livelihood zone, whereas black curves show the NDVI estimation averaged by livelihood zone. Both rain and NDVI curves have been rescaled to fit the scale of the Population Count signatures.
Paul C. Sutton - One of the best experts on this subject based on the ideXlab platform.
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a global poverty map derived from satellite data
Computers & Geosciences, 2009Co-Authors: Christopher D. Elvidge, Benjamin T. Tuttle, Paul C. Sutton, Tilottama Ghosh, Kimberly E Baugh, Budhendra L Bhaduri, Eddie A BrightAbstract:A global poverty map has been produced at 30arcsec resolution using a poverty index calculated by dividing Population Count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.
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paving the planet impervious surface as proxy measure of the human ecological footprint
Progress in Physical Geography, 2009Co-Authors: Paul C. Sutton, Benjamin T. Tuttle, Christopher D. Elvidge, Sharolyn Anderson, Tilottama GhoshAbstract:Fundamental questions regarding the human-environment-sustainability problematic remain contested. What are the relative roles of Population, consumption, and technology with respect to sustainability? How can sustainability be measured? Numerous metrics have been developed to address these controversial questions including ideas of carrying capacity, environmental sustainability indices, and ecological footprints. This work explores the question: is pavement a proxy measure of human impact on the environment? We explore and evaluate the use of satellite derived density grids of constructed area (aka ‘pavement’ or ‘impervious surface’) in the calculation of national and subnational ‘ecological footprints’. We generated a global constructed area density grid for the 2000—2001 period using satellite observed nighttime lights and a Population Count grid from the US Department of Energy. Satellite data inputs to the Population product include MODIS landcover, SRTM topography and high-resolution imagery. Calib...
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Global Distribution and Density of Constructed Impervious Surfaces
Sensors, 2007Co-Authors: Christopher D. Elvidge, Ara T. Howard, Benjamin T. Tuttle, K. E. Baugh, Paul C. Sutton, Cristina Milesi, Budhendra BhaduriAbstract:We present the first global inventory of the spatial distribution and density of constructed impervious surface area (ISA). Examples of ISA include roads, parking lots, buildings, driveways, sidewalks and other manmade surfaces. While high spatial resolution is required to observe these features, the new product reports the estimated density of ISA on a one-km2 grid based on two coarse resolution indicators of ISA – the brightness of satellite observed nighttime lights and Population Count. The model was calibrated using 30-meter resolution ISA of the USA from the U.S. Geological Survey. Nominally the product is for the years 2000-01 since both the nighttime lights and reference data are from those two years. We found that 1.05% of the United States land area is impervious surface (83,337 km2) and 0.43 % of the world’s land surface (579,703 km2) is constructed impervious surface. China has more ISA than any other Country (87,182 km2), but has only 67 m2 of ISA per person, compared to 297 m2 per person in the USA. The distribution of ISA in the world’s primary drainage basins indicates that watersheds damaged by ISA are primarily concentrated in the USA, Europe, Japan, China and India. The authors believe the next step for improving the product is to include reference ISA data from many more areas around the world.