Remote sensing and deep learning for environmental policy support: from theory to practice

Stien Heremans; Francis Turkelboom; Margot Verhulst; Matthew Blashko; Ben Somers

doi:10.1109/IGARSS47720.2021.9554514

Remote sensing and deep learning for environmental policy support: from theory to practice

Stien Heremans, Francis Turkelboom, Margot Verhulst, Matthew Blashko, Ben Somers

Research output: Contribution to conference › Paper/Powerpoint/Abstract

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Original language	English
Pages	5728-5731
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9554514
Publication status	Published - 16-Jul-2021

Thematic List 2020

Other

Policy

policy support (inc. instruments)

Geographic list

Flanders

Technological

image processing
detection technology

Access to Document

10.1109/IGARSS47720.2021.9554514

Remote_Sensing_and_Deep_Learning_for_Environmental_Policy_Support_From_Theory_to_PracticeFinal published version, 649 KB

Spatio-temporal deep learning workflows for transforming remote sensing data into geo-indicators for environmental policy support
Heremans, S. (Project leader), Callebaut, J. (Cooperator), Casaer, J. (Cooperator), Onkelinx, T. (Cooperator), Pallemaerts, L. (Cooperator), Rutten, A. (Cooperator) & Turkelboom, F. (Cooperator)
1/10/20 → 31/12/25
Project: Undefined

Cite this

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title = "Remote sensing and deep learning for environmental policy support: from theory to practice",

author = "Stien Heremans and Francis Turkelboom and Margot Verhulst and Matthew Blashko and Ben Somers",

year = "2021",

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day = "16",

doi = "10.1109/IGARSS47720.2021.9554514",

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pages = "5728--5731",

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TY - CONF

T1 - Remote sensing and deep learning for environmental policy support

T2 - from theory to practice

AU - Heremans, Stien

AU - Turkelboom, Francis

AU - Verhulst, Margot

AU - Blashko, Matthew

AU - Somers, Ben

PY - 2021/7/16

Y1 - 2021/7/16

U2 - 10.1109/IGARSS47720.2021.9554514

DO - 10.1109/IGARSS47720.2021.9554514

M3 - Paper/Powerpoint/Abstract

SP - 5728

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ER -

Remote sensing and deep learning for environmental policy support: from theory to practice

Thematic List 2020

Policy

Geographic list

Technological

Access to Document

Projects

Spatio-temporal deep learning workflows for transforming remote sensing data into geo-indicators for environmental policy support

Cite this