The University of Auckland
Browse
2_2_Bhaduri_et_al.pdf (225.73 kB)

High Performance Geocomputation for Assessing Human Dynamics at Planet Scale. GeoComputation 2019

Download (225.73 kB)
Version 2 2019-12-01, 23:28
Version 1 2019-09-18, 03:30
conference contribution
posted on 2019-12-01, 23:28 authored by Budhendra Bhaduri, Dalton Lunga, Hsiu-Han Yang, Jacob McKeeJacob McKee, Melanie Laverdiere, Kuldeep Kurte, Jibonananda Sanyal
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.

History

Publisher

University of Auckland

Usage metrics

    GeoComputation 2019

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC