Roland Löwe

Technical University of Denmark

Denmark

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Articles (14)

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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2021

Collaborators (9)

Allan Peter Engsig-Karup

Technical University of Denmark

DENMARK

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Ursula S. McKnight

Technical University of Denmark

DENMARK

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Luca Vezzaro

Technical University of Denmark

DENMARK

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Peter Steen Mikkelsen

Professor

Technical University of Denmark

DENMARK

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Thomas Balstrøm

Københavns Universitet

DENMARK

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Jacob Ladenburg

Technical University of Denmark

DENMARK

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Mark Koetse

University of Amsterdam

NETHERLANDS

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Peter Bauer-Gottwein

Technical University of Denmark

DENMARK

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Hjalte Jomo Danielsen Sørup

Technical University of Denmark

DENMARK

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Roland Löwe

Research Interests

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Articles (14)

Automated screening of control potential with spatially explicit results to support dialogue about sewer overflow reduction and beyond

Beyond meta-studies: Learnings from a large multi-site primary dataset on non-tangible benefits of nature-based solutions

Feedbacks between city development and coastal adaptation: A systems thinking approach

Ecosystem services potential is declining across European capital metropolitan areas

Holistic valuation of Nature-Based Solutions accounting for human perceptions and nature benefits

A Comparative Overview of the Transversal Connectivity of Natural Landscape Mosaics to Freshwaters in the Metropolitan Areas of Berlin, London, & Paris

Identifying barriers and potentials of integrated assessments of sustainable urban development and adaptation to rising sea levels

Surface Water Extent Mapping in Denmark: Comparing Airborne Thermal Imagery and Satellite Earth Observation

Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning

Assessing the recreational value of small-scale nature-based solutions when planning urban flood adaptation

Knowledge gaps and future research needs for assessing the non-market benefits of Nature-Based Solutions and Nature-Based Solution-like strategies

Approaches for unsupervised identification of data-driven models for flow forecasting in urban drainage systems

FloodStroem: A fast dynamic GIS-based urban flood and damage model

U-FLOOD – Topographic deep learning for predicting urban pluvial flood water depth

Collaborators (9)

Allan Peter Engsig-Karup

Ursula S. McKnight

Luca Vezzaro

Peter Steen Mikkelsen

Thomas Balstrøm

Jacob Ladenburg

Mark Koetse

Peter Bauer-Gottwein

Hjalte Jomo Danielsen Sørup

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