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Title: High Performance Geocomputation for Assessing Human Dynamics at Planet Scale

Abstract

Settlements are key indicators of human presence on the landscape. Large scale mapping of human settlements and their morphology from very high-resolution satellite images is a critical step towards developing an interpretative understanding of population distribution and the sociocultural attributes of the built environment they live in. Convolutional neural network (CNN) based Deep Learning experiments indicates that such computations can be scaled to some of the largest high-performance computing (HPC) architectures. While early results are encouraging for developing settlement and corresponding population maps at unprecedented speed and spatial resolutions, characterizing human dynamics at planet scale with high temporal resolution will require the community to develop novel geocomputational infrastructures and ecosystems.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1569370
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: GeoComputation 2019 - Queenstown, , New Zealand - 9/18/2019 8:00:00 AM-9/21/2019 8:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Bhaduri, Budhu, Lunga, Dalton D., Yang, Lexie, Mckee, Jacob, Laverdiere, Melanie, Kurte, Kuldeep R., and Sanyal, Jibonananda. High Performance Geocomputation for Assessing Human Dynamics at Planet Scale. United States: N. p., 2019. Web.
Bhaduri, Budhu, Lunga, Dalton D., Yang, Lexie, Mckee, Jacob, Laverdiere, Melanie, Kurte, Kuldeep R., & Sanyal, Jibonananda. High Performance Geocomputation for Assessing Human Dynamics at Planet Scale. United States.
Bhaduri, Budhu, Lunga, Dalton D., Yang, Lexie, Mckee, Jacob, Laverdiere, Melanie, Kurte, Kuldeep R., and Sanyal, Jibonananda. Sun . "High Performance Geocomputation for Assessing Human Dynamics at Planet Scale". United States. https://www.osti.gov/servlets/purl/1569370.
@article{osti_1569370,
title = {High Performance Geocomputation for Assessing Human Dynamics at Planet Scale},
author = {Bhaduri, Budhu and Lunga, Dalton D. and Yang, Lexie and Mckee, Jacob and Laverdiere, Melanie and Kurte, Kuldeep R. and Sanyal, Jibonananda},
abstractNote = {Settlements are key indicators of human presence on the landscape. Large scale mapping of human settlements and their morphology from very high-resolution satellite images is a critical step towards developing an interpretative understanding of population distribution and the sociocultural attributes of the built environment they live in. Convolutional neural network (CNN) based Deep Learning experiments indicates that such computations can be scaled to some of the largest high-performance computing (HPC) architectures. While early results are encouraging for developing settlement and corresponding population maps at unprecedented speed and spatial resolutions, characterizing human dynamics at planet scale with high temporal resolution will require the community to develop novel geocomputational infrastructures and ecosystems.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {9}
}

Conference:
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