Publications de Dan Assouline | EPFL Graph Search

A machine learning methodology to quantify the potential of urban densification in the Oxford-Cambridge Arc, United Kingdom

Regional-scale urban residential densification provides an opportunity to tackle multiple challenges of sustain-ability in cities. But framework for detailed large-scale analysis of densification potentials and their integration with natural capital to ass ...

ELSEVIER2023

Residential density classification for sustainable housing development using a machine learning approach

Nahid Mohajeri Pour Rayeni, Dan Assouline, Alina Ursula Rosa Walch

Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here ...

IOP PUBLISHING LTD2021

A machine learning-assisted building electricity consumption profiling for anomaly detection

Jean-Louis Scartezzini, Nicolas Zwahlen, Dasaraden Mauree, Dan Assouline, Roberto Castello, Michele Vidulis, Daniele Hamm, Margherita Guido

2020

Machine Learning and Geographic Information Systems for large-scale mapping of renewable energy potential

Dan Assouline

A promising pathway to follow in order to reach sustainable development goals is an increased reliance on renewable sources of energy. The optimized use of these energy sources, however, requires the assessment of their potential supply, along with the dem ...

EPFL2019

A machine learning approach for mapping the very shallow theoretical geothermal potential

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

The very shallow geothermal potential (vSGP) is increasingly recognized as a viable resource for providing clean thermal energy in urban and rural areas. This is primarily due to its reliability, low-cost installation, easy maintenance, and little constrai ...

2019

A solar-based sustainable urban design: The effects of city-scale street-canyon geometry on solar access in Geneva, Switzerland

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Nahid Mohajeri Pour Rayeni, Dan Assouline

Buildings commonly have the largest share in the energy demand of a country, but they also offer sites for the generation of solar energy. Here we develop a methodology to analyse the effects of street-canyon geometries on the solar access of street surfac ...

2019

Machine learning and geographic information systems for large-scale wind energy potential estimation in rural areas

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dasaraden Mauree, Dan Assouline

Clean, safe, affordable and available in the long-term, wind is one of the most promising sources of renewable energy. Its optimized and profitable use, however, requires an estimation of the potential in locations of interest, given its very volatile beha ...

IOP2019

Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

2018

A city-scale roof shape classification using machine learning for solar energy applications

Jean-Louis Scartezzini, Bérénice Guiboud, Andreas Bill, Nahid Mohajeri Pour Rayeni, Dan Assouline

Solar energy deployment through PV installations in urban areas depends strongly on the shape, size, and orientation of available roofs. Here we use a machine learning approach, Support Vector Machine (SVM) classification, to classify 10,085 building roofs ...

Pergamon-Elsevier Science Ltd2018

Combining Fourier Analysis And Machine Learning To Estimate The Shallow-Ground Thermal Diffusivity In Switzerland

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

We propose a methodology combining physical modelling and machine learning (ML) to estimate the apparent ground thermal diffusivity at the scale of a country. Based on ground temperature time series at different depths, we estimate the diffusivity at 49 Sw ...

IEEE2018

Quantifying rooftop photovoltaic solar energy potential: A machine learning approach

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

The need for reduction in CO2 emissions to mitigate global warming has resulted in increasing use of renewable energy sources. In urban areas, solar photovoltaic (PV) deployment on existing rooftops is one of the most viable sustainable energy resources. T ...

Pergamon-Elsevier Science Ltd2017

Effects of city size on the large-scale decentralised solar energy potential

Jean-Louis Scartezzini, Nahid Mohajeri Pour Rayeni, Dan Assouline

To assess the PV-potential on rooftops for decentralized electricity supply in Switzerland, the potential is compared with the following urban-size parameters: (a) urban population, (b) number of buildings, (c) the cumulative building ground-floor area, an ...

Elsevier2017

How street canyon configuration control the accessibility of solar energy potential: Implication for urban design

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Govinda Upadhyay, Nahid Mohajeri Pour Rayeni, Dan Assouline

While the effects of street-canyon configuration on temperature, wind speed and direction, and air quality have received much attention, its impact on solar energy potential has not been much studied. This paper focuses on two aspects of the street-canyon ...

2016

Does roof shape matter? Solar photovoltaic (PV) integration on building roofs

Jean-Louis Scartezzini, Bérénice Guiboud, Nahid Mohajeri Pour Rayeni, Dan Assouline

This paper focuses on roof-shape classification and solar potential for integrating photovoltaics (PV) on roofs. A machine-learning approach, Support Vector Machine (SVM), is used to classify the roof shapes in the city of Geneva. The impact of various roo ...

2016

Effects of urban compactness on solar energy potential

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Govinda Upadhyay, Nahid Mohajeri Pour Rayeni, Dan Assouline

Compactness is a major urban form parameter that affects the accessibility of solar energy in the built environment. Here we explore the relation between various compactness indicators and solar potential in the 16 neighbourhoods (11,418 buildings) constit ...

Pergamon-Elsevier Science Ltd2016

Neighbourhood morphology and solar irradiance in relation to urban climate

Jean-Louis Scartezzini, Govinda Upadhyay, Nahid Mohajeri Pour Rayeni, Dan Assouline

Assessing the relationship between neighbourhood morphology and urban climate is becoming increasingly important as cities continue to grow and the climate continues to change. Here we focus on the impact of (1) shapes and sizes of buildings, (2) street la ...

2015