Many thanks to our contributors: Kerry Schiel, Léandre Fabri and Cyrille Médard de Chardon

Day 8: HDX by Kerry Schiel

Day 8: HDX by Léandre Fabri

Day 7: Vintage by Cyrille Médard de Chardon

Day 7: Vintage by Kerry Schiel

Day 6: Raster by Kerry Schiel

Day 5: A journey by Léandre Fabri

Day 5: A journey by Kerry Schiel

Day 4: Hexagons by Cyrille Médard de Chardon

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Day 4: Hexagons by Kerry Schiel

Day 3: Polygons by Kerry Schiel

Day 2: Lines by Léandre Fabri

Day 2: Lines by Kerry Schiel

Day 1: Points by Kerry Schiel

Day 1: Points by Cyrille Médard de Chardon

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Letz start!

After a first super succesful session in May 2023, from which we developed a package for radial analysis with the team of Rouen (UMR Idees), Port-Louis (Morbihan, France) will welcome our 2nd coding retreat from February 26th to March 1st.

The retreat is aimed as a team building moment where uni.lu geographers and associated researchers spend time together consolidating their code.

This is mostly an R spatial training, peppered with some Py spatial analytics.

Rationale: we do all have our “own” pieces of code on our personal machines, on a server and/ on our own Git repos, which we fine tune along various projects and need. Then we quickly discover other colleagues have done similar, sometimes better, would benefit from similar lines, or, when reproducing, that some parts do not lead to the exact same results for some reasons (parameters, cut-offs, pre-processing of data,…)

In view of (i) reproducibility, (ii) improving, and (iii) sharing our codes, the retreat is a moment to take stock, compare and develop further our scripts and data.

The program is super simple:

• Intense mornings: 8AM to 2PM Monday to Friday including a quick sandwich lunch,
• Some more relax time up to 4.30PM (a walk outside before sunset)
• And further reading/correcting in the evening 5PM-7PM before enjoying a creperie or a nice
• … starting anew the next day…

For the venue, we joint-venture with the Gîtes de Kerouzec (https://gitesdekerouzec.fr/) so we are housed together, and live for and eat for coding 24/7 (well…24/5) while enjoying a view, a beach and a small but fully serviced town where all our needs are fulfiled in under 5min walk! No time wasted!

Organizer: Geoffrey Caruso, University of Luxembourg.

Venue: 5 Place au Bois, 56290 Port-Louis FR

2 presentations by Yufei Wei and by Estelle Mennicken

When? 18th June 2021, 14:00-16:00

Where? Webex

The Quadtrees Hubs are to share opinions and discuss research in progress. The meetings of Quadtrees Hubs are open to anyone interested and somehow familiar with some quantitative techniques and willing to progress with these. Please contact Isabelle Pigeron-Piroth isabelle.piroth@uni.lu for more information and obtaining the webex link.

The Effects of Distance to City Centers and Population Size on the NO2 Concentrations in Europe

Yufei Wei (University of Luxembourg, DGEO)

Ground-level NO₂ surface concentrations measured by monitoring stations and tropospheric NO₂ columns from Sentinel-5P are the data sources of NO₂. We filter the data to get the annual mean NO₂ concentrations of European cities. We regress the data to find how urban population size influences the NO₂ concentrations, and how the NO₂ concentrations change within the cities.

The results show larger cities have higher levels of NO₂ concentrations. We also find distinct spatial patterns of the NO₂ concentrations within the cities. The results indicate monitoring stations and Sentinel-5P are reliable in describing and predicting the NO₂ concentrations of European cities.

European urban cores under pressure: quantifying the congestion of trips in and out from city centers as function of population size

Estelle Mennicken (LISER, UDM)

Traffic congestion has many negative social, environmental and economic consequences. We can cite among others the loss of time (hours of delay) inducing productivity and well-being losses, the excess fuel consumption, and the excess emitted CO₂. Understanding and quantifying this phenomenon at the scale of an entire continent is therefore a serious societal challenge. In particular, we focus on comparing the accessibility of city centers based on the geographical location of urban areas but also on the population size. Larger cities benefit from positive agglomeration effects but whether they proportionally show more radial traffic congestion is still an open question.

We simulate intra-urban trips between residential locations and city centers in 303 European cities and retrieve travel information around the clock during a typical weekday. We then compute several congestion indices to reveal the excess time people spend on roads driving during peak traffic time compared to a free-flow situation and establish a city ranking. Second, we observe how the total population size influences the indices. Finally, thanks to previously computed detour indices, we examine the relationship between the physical road network shape and the congestion.

Kaarel Sikk (University of Luxembourg, C2DH and DGEO)

When? 21^st May 2021, 2 to 3 pm

Where? via Webex (request meeting link by registering to isabelle.piroth@uni.lu or geoffrey.caruso@uni.lu)

Point process modelling provides a framework for exploring systems that can be observed as a set of points. In this study, we studied archaeological settlement patterns with the purpose of isolating regions in landscapes that were suitable for habitation by different populations. We create point process models of the settlement systems of hunter-fisher-gatherer groups (Narva and Combed Ware Culture) and early agrarian communities (Corded Ware Culture) in Stone Age Estonia and compare the spatial structure.

We conceptualize settlement system formation as a point process and develop a first-order point process model representing the environmental suitability for habitation based on geomorphology, soil, and proximity to water. We use MaxEnt and the SDMTune machine learning framework for building the model, variable selection, and estimation. The model is applied to the two communities and the effects of the variables and the resulting spatial patterns compared.

The spatial comparison showed significant differences between the suitable environments for habitation between the two groups. While the hunter-fisher-gatherer population had an entirely shoreline-connected settlement system, the Corded Ware people inhabited the areas further away from water bodies. This resulted in significantly expanded potential space with differing spatial configurations for the incoming agrarian groups but the areas also had a certain overlap.

The results also indicated higher predictive power for hunter-fisher-gatherer sites, which might be caused by a higher variety of agrarian activities, different socio-economic organizations, or effects of the spatial structure of the landscape.

The aim of Quadtrees’ Hubs is to share and discuss research in progress. The hubs are open to anyone interested and somehow familiar with quantitative spatial analysis and modelling and willing to progress with these. Please contact Isabelle Pigeron-Piroth or Geoffrey Caruso for information or to obtain the linnk to the meeting.

On May 21^st, our sixth Quadtrees Hub will take place. The aim is to share and discuss research in progress. Quadtrees’hubs are open to anyone interested and somehow familiar with some quantitative techniques and willing to progress with these. Please contact Isabelle Pigeron-Piroth for information.

When? 21^st May 2021, 2 to 3 pm

Where? via Webex

2-3 pm : Marlène Boura  (University of Luxembourg, DGEO): Towards a spatially explicit urban CO₂ budget. Urban carbon emissions, dispersion and sequestration in Europe

Modelling a steady-state urban carbon balance for 802 European cities at a fine spatial resolution.

Anthropogenic CO2 emissions are downscaled spatially (down to 1 ha) and temporally (from annual to daily) based on the sector of activity, the land use category and the location. Sequestration of CO2 is estimated for different types of urban vegetation, following the IPCC guidelines at the same spatial and temporal resolutions.

For one typical day of each month, we simulate 2 steady-state situations for the CO2 molecules dispersion and capture. The absolute carbon balance and the relative carbon capture (as a percentage of effective anthropogenic emissions) are then computed. The data produced can be used to assess the spatial heterogeneity of the carbon balance within a specific urban area. It can also be used to assess how much of its own emissions an urban area can capture.

Zenodo: http://doi.org/10.5281/zenodo.4301952

Description

The datasets provide a typology for 689 European urban areas, the land cover metrics and landscape metrics used to create the typology and the Urban Forest Ecosystem Services (UFES) indexes created from them.

The typology of Urban Forest Ecosystem Services (UFES) presents 10 clusters of cities aggregated into 4 groups: Forest cities (F1-4), Anthropogenic cities (A1-3), Herbaceous cities (H1-2) and Standard European cities (E1). The data can be used to support urban planning policies at local and regional scales; in urban forestry, urban form and ecosystem services work-related at different spatial scales. The metrics used capture the spatial integration of different layers of natural, semi-natural and artificial land within functional urban areas.

The data refers to the article under revision “Urban Forests Ecosystems in Europe: Types and Ranking of Cities”

The details of iEMSs 2020 are here.

The followings are the abstract and the video of the presentation Scaling of Urban Heat Island and NO₂ with Urban Population: A Meta-Analysis

Abstract

Due to urban population growth worldwide, thermal anomalies and toxic air pollution are increasing concern for citizens. Despite this increasing challenge and indications that these environmental problems increase with city size, there is still no consolidated understanding of the effect of city size on urban heat island (UHI) and nitrogen dioxide (NO₂) pollution. Meanwhile, research on urban scaling laws, which formally relates population size and urban characteristics, has been quickly increasing over the past decade but is mostly devoted to the socio-economic outcome of cities rather than pollution or heat stress. Most studies dedicated to UHI or NO₂ consider only a single city or analyze a few cities within the top ranks of specific world regions or globally. We intend to fill this gap by conducting a qualitative synthesis of the literature and performing a statistical meta-analysis from published work with the aim to uncover scaling laws of UHI and NO₂ with the population size of cities. Under the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline, we collect and filter about 500 research outcomes on UHI and NO₂ from Scopus and Google Scholar. We find that moving from a city with a population of 100-thousand to a city with a population of 1 million, the max UHI intensity increases by 2.66 °C, the annual mean NO₂ surface concentration increases by 14.95 𝜇g/m³. Moving from a city having a population of 1 million to a city with a population of 10-million, the max UHI intensity increases by 3.87 °C, the annual mean NO₂ surface concentration increases by 21.72 𝜇g/m³. Thus, larger cities have higher levels of UHI effects and NO₂ pollution. We also give the progress of verifying the NO₂ scaling using census data and in-situ and RS-measured NO₂ data at the level of Urban Atlas 2012.

Abstract

Air pollution is of increasing concern to urban residents and urban planners are struggling to find interventions which tackle the trade‐off between environmental, health, and economic impacts arising from this. We analyze within a spatially explicit theoretical residential choice model how different urban interventions can reduce exposure to endogenous traffic‐induced air pollution at residential locations. We model a city of fixed population size, where households are averse to localized pollution and examine how a flat commuting tax, an urban growth boundary, a cordon toll, and the optimal distance‐based tax compare to an urban scenario without any planner’s intervention. We find that an urban intervention to optimally address exposure concerns needs to achieve steep density gradients near the urban fringe and flat gradients near the center. We show the deficiencies of the alternative interventions to achieve optimal population distributions within the city and in a scenario where peoples’ aversion to pollution increases. We then discuss these interventions in light of resulting spatial patterns of exposure and spatial equity that is households’ assessment of their own exposure to air pollution relative to their responsibility for the exposure of others depending on their spatial location within the city. Our results show that, when equity is also a concern, compensations are needed from households who live in the periphery and our simulations suggest that a cordon toll can then achieve a more balanced outcome.

https://doi.org/10.1111/gean.12288

Cet article analyse les principales dimensions spatiales et socioprofessionnelles des travailleurs frontaliers aux différentes frontières de la France, notamment au sein des pôles d’emploi transfrontaliers de Genève, Bâle et de Luxembourg. Il s’appuie sur une exploitation des données du recensement français de la population, complétées par les données issues des pays de travail des frontaliers. Si les travailleurs frontaliers ont des caractéristiques sociodémographiques relativement communes aux différents pôles d’emploi transfrontaliers (plutôt des hommes, relativement jeunes…), l’article met en lumière une spécificité territoriale des profils socioprofessionnels en fonction des différents espaces transfrontaliers observés. Le travail frontalier constitue alors une modalité de la gestion territoriale de la main-d’œuvre et des compétences.

This article analyzes the main spatial and socio-professional dimensions of cross-border workers at the different borders of France, particularly within the cross-border employment poles of Geneva, Basel and Luxembourg. It is based on data from the French population census, supplemented by data from the countries where cross-border workers work. While cross-border workers have socio-demographic characteristics that are relatively common to the different cross-border employment centres (mostly men, relatively young, etc.), the article highlights the territorial specificity of socio-professional profiles according to the different cross-border spaces observed. Cross-border work thus constitutes a modality of territorial management of labor and skills.

Plus d’informations sur la publication

Accessible sur ORBI

This article appeared on Teagasc Daily 4th June 2020

Background: Water Quality in Ireland and EU Directives

The European Union (EU) has introduced a number of directives aimed at improving water quality, such as the Nitrates Directive (ND) (91/676/EEC) and Water Framework Directive (WFD) (2000/60/EC). The WFD set out to achieve ‘good status’ in surface waters by2027 at the latest but also aims to ensure that there is no decrease in quality. Nitrogen and phosphorus losses from agriculture have attracted considerable attention. In Ireland, water quality had stabilised and began to improve over the last few decades.

However, the Environmental Protection Agency (EPA) water quality report 2013-2018, showed a 5.5 % net decline in quality of rivers over the period. According to the EPA a total of 53 % of river water bodies were at high or good quality with the remaining 47 % at moderate or worse. The percentage of high-quality monitoring sites was just 17%, down from 32% in the 1987–1990 period, which is a significant decline.

In response to decreasing water quality, the 4th Nitrates Action Programme (NAP) which started in 2017, sees the introduction of additional measures aimed at reducing the overall level of nutrient losses from agriculture. These measures relate to the location of drinking points on farms, spreading of fertiliser, farmyards, roads and cattle exclusion from watercourses (DAFM, 2018).

In addressing climate and environmental needs at local level, voluntary and mandatory measures can be used in a more targeted way. With increasing pressure on the Common Agricultural Policy (CAP) budget and limited resources, EPA funded this study to create a database which can ensure money is spent as efficiently as possible.

The 4th NAP of the Nitrates Directive (ND) requires farms with an allowance (derogation, so called as they derogate from the directive) to farm at a grassland stocking rate over 170 kg N/ha, to prevent cattle from accessing watercourses from January 2021. This 170 kg N/ha relates to the spreading of organic manure or slurry and that deposited by the animals themselves. Five EU member states apply for a derogation from the Nitrates Directive; Belgium (Flanders), UK (Northern Ireland), Denmark, Ireland and Italy (Piedmont and Lombardy). Derogations are reviewed every four years like the Nitrates Directive.

Impact and potential benefits of fencing off watercourses

This research uses Land Parcel Identification System (LPIS) data from the Department of Agriculture, Food and the Marine (DAFM) along with the Ordnance Survey Ireland (OSI) database PRIME2. PRIME2 is the most sophisticated dataset produced by OSI. It contains every building and feature in the country (houses, sheds, roads, field boundaries, rivers, railways).

One of the issues with the LPIS data is that it is not spatially accurate. Field boundaries zig-zag across the landscape. Matching the LPIS with the PRIME2 dataset produced a spatial database SLIDE (Spatial Land Identification Database for Éire), containing all 130,000 farms and over 2 million individual fields in Ireland. The figure shows a sub-sample of the information contained in the SLIDE database.

The objective was first to quantify the total amount of on-farm watercourses in Ireland and secondly using stocking rate, create a measure of potential damage to watercourses arising from livestock dung (and faecal matter), as other studies have found that cattle drinking in streams prefer to defecate in the stream as opposed to in the field.

Studies have estimated that cattle produce on average 23kg of faecal matter daily. If given access to a river, between 7-10% of 23kg will be deposited in-stream. Over the entire grazing season, that would be over 100kg per cow. In addition to the damage caused by the faecal matter, there is the additional damage due to sediment, damage to the riverbank and increased risk of disease.

To judge the effectiveness of a policy, the benefits and costs must be considered. The costs are measured by cost of the fencing and lost area around the riverbank. The benefits are measured by reduced faecal matter deposited in the river. The stocking rate is therefore an important determinant of cost effectiveness, as the more intensive a farm is, the more faecal matter deposited and the greater risk to water courses. The results of the cost benefit analysis show that farms with the highest stocking rates and largest paddocks with access to a watercourse should be prioritized for fencing. Although some areas might have higher amounts of on-farm watercourses, if agricultural intensity is low, the cost effectiveness of fencing is reduced.

These important local differences can only be calculated and identified using highly detailed information as it is not feasible to go through each of the 130,000 farms one by one to identify needs and suitable environmental measures. This is where the use of technology can help. The SLIDE maps can be utilised to identify the areas with the greatest level of cost effectiveness for a particular measure, thus achieving greater impact.

Place based approaches using technology can be used to implement more targeted policies. Rather than using a national approach, we can use large scale datasets to implement more locally relevant policies. One example is fencing of water courses another could be fertiliser application periods.

In 2020, the European Court of Auditors completed an audit in how new imaging technologies can be used to monitor the Common Agricultural Policy (CAP). Normally the LPIS is only updated every 3 years with a need to carry out ground inspections of ~5% of farms (6,500 farms in Ireland). Machine learning algorithms can be used to identify noncompliance reducing the need for random inspections and allow for more targeted inspections. Article

Summary

• The areas where fencing off water courses is most cost effective are located in the south of the country.
• Farm size and shape and farmer characteristics all play a role in determining the level of cost effectiveness of fencing individual farms.
• The study confirms that fencing areas according to agricultural intensity as recommended in the 4th NAP of the Nitrates Directive is a cost effective solution.
• CAP: Move away from one-size-fits-all regulation and incentives for farm management practices.
• Agri-Environmental Schemes: A local approach to regulation and AES design could be more beneficial in ensuring more targeted and efficient use of resources.

The results and findings in this article come from the published article:

Kilgarriff, P., Ryan, M., O’Donoghue, C., Green, S., Ó hUallacháin, D. 2020. Livestock Exclusion from Watercourses: Policy Effectiveness and Implications. Environmental Science and Policy. 106 58-67. https://doi.org/10.1016/j.envsci.2020.01.013

This research was funded by the Environmental Protection Agency (EPA), Ireland as part of the Research Programme 2014–2020 as part of the COSAINT project: Cattle exclusion from watercourses: Environmental and socio-economic implications. The entire report [pdf] can be viewed on the EPA website [1]

[1] DISCLAIMER: Although every effort has been made to ensure the accuracy of the material contained in this journal article, complete accuracy cannot be guaranteed. Neither the Environmental Protection Agency nor the authors accept any responsibility whatsoever for loss or damage occasioned or claimed to have been occasioned, in part or in full, as a consequence of any person acting or refraining from acting, as a result of a matter contained in this journal article.