Environmental Impacts on Human Populations


“Slum” Mapping

Thomson DR, Kuffer M, Boo G, Hati B, Grippa T, Elsey H, Linard C, Mahabir R, Kyobutungi C, Maviti J, Mwaniki D, Ndugwa R, Makau J, Sliuzas R, Cheruiyot S, Nyambuga K, Mboga N, Kimani NW, de Albuquerque JP, Kabaria C. 2020. Need for an Integrated Deprived Area “Slum” Mapping System (IDEAMAPS) in Low- and Middle-Income Countries (LMICs). Social Sciences 9:80. DOI: 10.3390/socsci9050080.

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. Four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The authors summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local‐to‐international stakeholders for advocacy, planning, and decision‐making across Low‐ and Middle‐Income Countries. They suggest that machine learning models be extended to incorporate social area‐level covariates and regular contributions of up‐to‐date and context‐relevant field‐based classification of deprived urban areas.

Climate change perceptions and migration in West Africa

De Longueville F, Ozer P, Gemenne F, Henry S, Mertz O, Nielsen JØ. 2020. Comparing climate change perceptions and meteorological data in rural West Africa to improve the understanding of household decisions to migrate. Climatic Change. DOI: 10.1007/s10584-020-02704-7.

West African populations largely depend on agriculture. Climate change, increasing rainfall variability and drought may thus have negative impacts on crop production and livestock and increase poverty and food insecurity. One adaptation strategy is migration. This study, composed of a literature review and an empirical study, highlights the importance of taking into account people’s perceptions of climate change as it affects their adaptation responses. These do not always match with actual rainfall data. To improve the understanding of the decision to migrate on a household level, it is recommended to jointly consider data on climate as well as on the perception of climate variability. This approach definitely requires interdisciplinary research!

Urban Changes of Beijing

Sorichetta A, Nghiem SV, Masetti M, Linard C, Richter A. 2020. Transformative Urban Changes of Beijing in the Decade of the 2000s. Remote Sensing 12:652. DOI: 10.3390/rs12040652.

The rapid growth of urban populations and the associated infrastructure contribute to a large part to greenhouse gases from power generation, industry, transportation, and consumption. The rapid economic growth, the exodus from rural to urban areas, and the associated extreme urban development that occurred in China in the decade of the 2000s have severely impacted the environment in Beijing, its vicinity, and beyond. This article presents an innovative approach for assessing mega-urban changes and their impact on the environment based on the use of decadal QuikSCAT (QSCAT) satellite data, acquired globally by the SeaWinds scatterometer over that period. Here, the corresponding tropospheric nitrogen dioxide (NO2) column densities are used as a proxy. Results reveal a threefold increase of the yearly tropospheric NO2 column density within the Beijing infrastructure-based urban area extent in 2009, which had quadrupled since 2000.

Mobile Phone Data for Urban Climate Change Adaptation

Dujardin S, Jacques D, Steele J, Linard C. 2020. Mobile Phone Data for Urban Climate Change Adaptation: Reviewing Applications, Opportunities and Key Challenges. Sustainability 12:1501. DOI: 10.3390/su12041501.

Climate change places cities at increasing risk and poses a serious challenge for adaptation. Novel sources of data combined with data-driven logics and advanced spatial modelling techniques would have the potential for transformative change applied in urban planning. However, little practical guidance exists on the opportunities offered by mobile phone data for enhancing adaptive capacities in urban areas. This paper explores the opportunities offered by such digital information for providing spatially-explicit assessments of urban vulnerability, and shows the ways these can help developing more dynamic strategies and tools for urban planning and disaster risk management. Finally, building upon the limitations of mobile phone data analysis, it discusses the key urban governance challenges that need to be addressed for supporting the emergence of transformative change in current planning frameworks.


People and Pixels

Kugler TA, Grace K, Wrathall DJ, de Sherbinin A, Van Riper D, Aubrecht C, Comer D, Adamo SB, Cervone G, Engstrom R, Hultquist C, Gaughan AE, Linard C, Moran E, Stevens F, Tatem AJ, Tellman B, Van Den Hoek J. 2019. People and Pixels 20 years later: the current data landscape and research trends blending population and environmental data. Population and Environment 41:209–234. DOI: 10.1007/s11111-019-00326-5

In 1998, the National Research Council published People and Pixels: Linking Remote Sensing and Social Science. The volume focused on emerging research linking changes in human populations and land use/land cover to shed light on issues of sustainability, human livelihoods, and conservation, and led to practical innovations in agricultural planning, hazard impact analysis, and drought monitoring. Since then, new research opportunities have emerged thanks to the growing variety of remotely sensed data sources, an increasing array of georeferenced social science data, including data from mobile devices, and access to powerful computation cyberinfrastructure. This article outlines the key extensions of the People and Pixels foundation since 1998 and highlights several breakthroughs in research on human–environment interactions. Pressing research problems are identified—disaster, famine, drought, war, poverty, climate change—and it is explored how interdisciplinary approaches integrating people and pixels are being used to address them.

Wealth maps of cities

Georganos S, Gadiaga AN, Linard C, Grippa T, Vanhuysse S, Mboga N, Wolff E, Dujardin S, Lennert M. 2019. Modelling the Wealth Index of Demographic and Health Surveys within Cities Using Very High-Resolution Remotely Sensed Information. Remote Sensing 11:2543. DOI: 10.3390/rs11212543.

To address the United Nations Sustainable Development Goals (SDGs), a systematic and precise understanding of urban socio-economic spatial inequalities in developing regions is needed. However, exhaustive census information is often outdated, unreliable or inaccessible. Geolocated surveys such as the Demographic and Health Surveys (DHS) may provide alternative solutions but suffer from the lack of very high-resolution (VHR) predictor variables. This study couples satellite-derived VHR land-use/land-cover (LULC) datasets with the DHS Wealth Index (WI), a robust household wealth indicator, in order to provide city-scale wealth maps. Modelling approaches using a random forest regressor as the underlying algorithm at several geographic administrative scales are validated against an exhaustive census database of Dakar, Senegal. Results show that the WI was modelled to a satisfactory degree when compared against census data even at very fine resolutions. These findings might assist local authorities and stakeholders in rigorous evidence-based decision making and facilitate the allocation of resources towards the most disadvantaged populations.

Pollen allergy & green space

Aerts R, Stas M, Vanlessen N, Hendrickx M, Bruffaerts N, Hoebeke L, Dendoncker N, Dujardin S, Saenen ND, Van Nieuwenhuyse A, Aerts J-M, Van Orshoven J, Nawrot TS, Somers B. 2019. Residential green space and seasonal distress in a cohort of tree pollen allergy patients. International Journal of Hygiene and Environmental Health. DOI: 10.1016/j.ijheh.2019.10.004.

Residential green space may promote physical activity and thus, reduce stress and improve human health. Conversely, such green space may increase stress by emitting aeroallergens and exacerbating allergic disease. This study investigates seasonal distress in a panel of 88 patients allergic to tree pollen. In general, short-term distress decreased with increasing residential green space within 1 km distance. However, allergy patients suffered from higher distress than the general population. The perceived presence of allergenic tree species was associated with higher distress, which modulates the protective effect of residential green space against distress during the airborne tree pollen season.

Ordering space & changing climate

Dujardin S, Dendoncker N. 2019. Ordering Space in a Changing Climate: A Relational Analysis of Planning Practices in Bohol, Philippines. Planning Theory & Practice 0:1–22. DOI: 10.1080/14649357.2019.1672773

Approaches to planning for climate change deal primarily with physical planning mechanisms while social planning processes are hardly considered. This paper draws upon the analytical lens of modes of ordering to trace the network of relationships taking place in the preparation and implementation of municipal land use plans within the coastal municipalities of Bohol, Philippines. Results highlight how planning’s dominant mode of ordering tends to address disaster risk areas by focusing primarily upon the physical characteristics of space and infrastructures. Some networks, however, recognize place-based knowledge from the most vulnerable communities. Evidence of some amendments to planning processes are provided, so that approaches integrating the agency of both human and non-human actors can be brought effectively into planning frameworks.

Malaria risk & satellite imagery

Solano-Villarreal E, Valdivia W, Pearcy M, Linard C, Pasapera-Gonzales J, Moreno-Gutierrez D, Lejeune P, Llanos-Cuentas A, Speybroeck N, Hayette M-P, Rosas-Aguirre A. 2019. Malaria risk assessment and mapping using satellite imagery and boosted regression trees in the Peruvian Amazon. Scientific Reports 9:1–12. DOI: 10.1038/s41598-019-51564-4.

In spite of the investment in control and prevention allocated by the Peruvian government over the last decades, malaria due to both Plasmodium vivax and P. falciparum remains a significant public health issue in the country. This is the first study to assess the risk of co-endemic Malaria pathogen transmission in the Peruvian Amazon using boosted regression tree (BRT) models based on social and environmental predictors derived from satellite imagery and data. Cumulative rainfall, population density and time to populated villages were consistently the top three predictors for both P. vivax and P. falciparum incidence. Maps created using the BRT models characterize the spatial distribution of the malaria incidence and should contribute to malaria-related decision making in the investigated Amazon region.

Birch pollen in Belgium

Verstraeten WW, Dujardin S, Hoebeke L, Bruffaerts N, Kouznetsov R, Dendoncker N, Hamdi R, Linard C, Hendrickx M, Sofiev M, Delcloo AW. 2019. Spatio-temporal monitoring and modelling of birch pollen levels in Belgium. Aerobiologia. DOI: 10.1007/s10453-019-09607-w

About 10% of the Belgian population suffer from allergies due to birch pollen. However, real-time and detailed spatial information on forthcoming pollen exposure episodes that would allow preventive actions is lacking. This study evaluates birch pollen levels near the surface with SILAM (System for Integrated modeLling of Atmospheric coMposition) simulations based on meteorological data and areal fraction maps of birch trees. The correlation (R2) between SILAM modelled and observed time series of daily birch pollen levels was up to ~ 50%. The 5-day averaged pollen concentrations from SILAM have R2 values between 0.49 and 0.84 at the pollen stations included in this study.

Comparison of methods to disaggregate human population

Stevens FR, Gaughan AE, Nieves JJ, King A, Sorichetta A, Linard C, Tatem AJ. 2019. Comparisons of two global built area land cover datasets in methods to disaggregate human population in eleven countries from the global South. International Journal of Digital Earth 0:1–23. DOI: 10.1080/17538947.2019.1633424

Mapping built land cover at unprecedented detail has been facilitated by increasing availability of global high-resolution imagery and image processing methods. These advances in urban feature extraction and built-area detection can refine the mapping of human population densities, especially in lower income countries where rapid urbanization and changing population is accompanied by frequently out-of-date or inaccurate census data. Here, two methods were tested, that include simple, areal weighting and more complex statistical models with other ancillary information. Outcomes were assessed across eleven countries, representing different world regions varying in population densities, types of built infrastructure, and environmental characteristics. For seven of them, a Random Forest-based, machine learning approach outperforms simple, binary dasymetric disaggregation into remotely-sensed built areas.

Geographical Random Forest (GRF) to estimate population

Georganos S, Grippa T, Gadiaga A, Vanhuysse S, Kalogirou S, Lennert M, Linard C. 2019. An Application of Geographical Random Forests for Population Estimation in Dakar, Senegal using Very-High-Resolution Satellite Imagery. In: 2019 Joint Urban Remote Sensing Event (JURSE). 1–4. DOI: 10.1109/JURSE.2019.8809049

This paper studies a local implementation of Random Forest (RF), named Geographical Random Forest (GRF) to predict population density with Very-High-Resolution Remote Sensing (VHHRS) data. As an independent variable, population density at the neighbourhood level was used from the 2013 census of Dakar. The proportions of three different built-up types in each neighbourhood derived from a VHHRS land cover classification served as explanatory features. The results show, that by using an appropriate geographic scale to calibrate GRF, prediction accuracy can be maximised due to the incorporation of spatial heterogeneity in the estimates. Additionally, since GRF is an ensemble of local sub-models, the results can be mapped, highlighting local model performance and other interesting spatial variations. Consequently, GRF is suggested as valuable exploratory and explanatory technique to model remotely-sensed spatially heterogeneous relationships.

Extending Data for Urban Health Decision-Making

Thomson DR, Linard C, Vanhuysse S, Steele JE, Shimoni M, Siri J, Caiaffa WT, Rosenberg M, Wolff E, Grippa T, Georganos S, Elsey H. 2019. Extending Data for Urban Health Decision-Making: a Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs. Journal of Urban Health. DOI: 10.1007/s11524-019-00363-3.

This paper aims at the extension of awareness among urban health decision-makers and data scientists about existing and potential datasets that can support urban health decision-making. It summarizes sources of neighbourhood-level data and introduces two case studies that demonstrate the need for neighbourhood-level indicator datasets for decision-making. It further reviews indicators at neighbourhood-level that determine health and urban poverty. This allowed the generation of a list containing important neighbourhood-level datasets, that can be processed by data scientists for health decision-makers. Ideally, these should be open source and freely available.

A public health threat due to illegal import?

Jansen W, Linard C, Noll M, Nöckler K, Al Dahouk S. 2019. Brucella-positive raw milk cheese sold on the inner European market: A public health threat due to illegal import? Food Control 100:130–137. DOI: 10.1016/j.foodcont.2019.01.022.

Brucellosis is a very common zoonosis caused by Gram-negative bacteria Brucella sp. Humans are usually infected by consuming unpasteurized milk or dairy products in or from endemic regions. Despite successful eradication from livestock in EU Member States, human infections occur annually. This study found Brucella-DNA in 20% of 200 cheese samples from endemic countries that were sold at weekly markets, in supermarkets and by delis in Berlin (Germany). Clustered positive samples at certain vendors suggest organized trade of illegal imports undermining EU food safety standards. A few cheeses investigated were produced from raw milk with short ripening periods that Brucella might survive.

Diseases & land use

Vanwambeke SO, Linard C, Gilbert M. 2019. Emerging challenges of infectious diseases as a feature of land systems. Current Opinion in Environmental Sustainability 38:31–36. DOI: 10.1016/j.cosust.2019.05.005.

The association of infectious diseases to the environment, and in particular land use, has regained interest in the late 20th century in relation to global environmental change. Four major challenges are identified: First, the multifactorial determinants of the complex ecological systems of infectious diseases should be better acknowledged. Second, new challenges appear in urban areas in relation to their dynamics. Third, livestock raising, as a component of land systems, creates specific types of ecological interfaces. Fourth, tensions discussed in the land use community regarding conservation must account for issues related to the health of human, livestock and wildlife.

Does climate influence migration?

De Longueville F, Zhu Y, Henry S. 2019. Direct and indirect impacts of environmental factors on migration in Burkina Faso: application of structural equation modelling. Population and Environment. DOI: 10.1007/s11111-019-00320-x.

Does drought in Africa cause massive migration to Europe? For 20 years now, this question intrigues Sabine Henry (Geography). She published the first empirical evidence for the impact of droughts on migration in 2004, a highly cited publication. Today, she and Florence De Longeville remain pioneers in distinguishing the direct effects of the environment on migration from indirect effects that reduce the socio-economic level of households. This was also one of the first proofs of the concept of “trapped populations” as defined by Black et al. (2011), communities, that too poor to migrate and are thus extremely vulnerable to climate change. The result of a successful collaboration with the London School of Economy and the University of Cambridge, this study helps to develop more appropriate climate change adaptation policies.

MR vs. VHR

Grippa T, Linard C, Lennert M, Georganos S, Mboga N, Vanhuysse S, Gadiaga A, Wolff E. 2019. Improving Urban Population Distribution Models with Very-High Resolution Satellite Information. Data 4:13. DOI: 10.3390/data4010013.

Freely available medium resolution (MR) satellite information is useful in dasymetric mapping, but suffers from important limitations at the intra-urban level. This paper finds that very-high resolution (VHR) data increase the accuracy of the dasymetric mapping procedure by ~13%.  However, their acquisition and processing costs hinders their applicability for large-scale population mapping in Africa. This paper compares data sets with different spatial and thematic resolutions to disaggregate population counts into 1-hectare grid cells.

Spread of mosquitoes, carrier of deseases

Kraemer MUG, Reiner RC, Brady OJ, ..., Linard C, .... 2019. Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus. Nature Microbiology:1. DOI: 10.1038/s41564-019-0376-y.

Tropical viral diseases (e.g. dengue, yellow fever, Zika) expand globally as do their key vectors, two mosquito species: Aedes aegypti & Aedes albopictus. Their distribution is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, actual processes are described and future distributions predicted for both species in relation to accelerating urbanization, connectivity and climate change. These maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Patterns of urban growth in SSA

Wolff E, Grippa T, Forget Y, Georganos S, Vanhuysse S, Shimoni M, Linard C. 2019. Diversity of urban growth patterns in Sub-Saharan Africa in the 1960–2010 period. African Geographical Review 0:1–13. DOI: 10.1080/19376812.2019.1579656.

Since 1960, urbanization in Sub-Saharan Africa (SSA) has been rapid. While consistent demographic statistics now exist on urban population growth rates, these data have not been fully exploited to improve our understanding of the evolution of urbanization at the continental scale. We investigate urban change between 1950 and 2010 across SSA using cluster analyses performed on three complementary aspects: the evolution of urban growth rates, primacy, and the densification of the urban mesh. Results show that SSA countries followed diverse urbanization trajectories over the last 60 years and are currently unevenly distributed along the urban transition model.

Climate zones & urban health

Brousse O, Georganos S, Demuzere M, Vanhuysse S, Wouters H, Wolff E, Linard C, van Lipzig NP-M, Dujardin S. 2019. Using Local Climate Zones in Sub-Saharan Africa to tackle urban health issues. Urban Climate 27:227–242. DOI: 10.1016/j.uclim.2018.12.004.

This study gives an example on how to link models of urban climate with climate-related health issues in Sub-Saharan Africa. Universal classifications of Local Climate Zones are combined with very high resolution satellite imagery and can then be used to create a simple urban canopy model over two cities: Kampala (Uganda) and Dakar (Senegal). Such models can help to analyze health issues, such as malaria risk, in highly dynamic environments.

Georganos S, Grippa T, Gadiaga AN, Linard C, Lennert M, Vanhuysse S, Mboga NO, Wolff E, Kalogirou S. 2019. Geographical Random Forests: A Spatial Extension of the Random Forest Algorithm to Address Spatial Heterogeneity in Remote Sensing and Population Modelling. Geocarto International 0:1–12. DOI: 10.1080/10106049.2019.1595177.


Support global urban mapping

Forget, Y, Linard, C, Gilbert, M, Forget, Y, Linard, C, & Gilbert, M 2018, ‘Supervised Classification of Built-Up Areas in Sub-Saharan African Cities Using Landsat Imagery and OpenStreetMap’, Remote Sensing, vol. 10, no. 7, p. 1145, doi: 10.3390/rs10071145

Landsat (Satellite) images allow the production of high resolution built-up maps, but the amount of work to classify algorithms relying on supervised learning is tremendous, especially for highly heterogeneous urban environments. Volunteered Geographic Information (VGI) projects such as OpenStreetMap (OSM) provide an increasing amount of information on the earth’s surface that is useful to generate such maps. Here, a classification method is proposed that makes use of OSM to automatically collect training samples for supervised learning of built-up areas.

Social perspectives of climate change adaptations

Dujardin, S, Orban-Ferauge, F, Cañares, MP, & Dendoncker, N 2018, ‘Capturing multiple social perspectives on adaptation across scales: a Q-method analysis of actors from development planning in the Philippines’, Climate and Development, vol. 10, no. 5, pp. 458–470, doi: 10.1080/17565529.2017.1301863

This paper describes and analyses viewpoints regarding climate change adaptation held among key social actors from the field of development planning in the Philippines. Four empirically significant social perspectives are determined – institutional, grassroots, developmental, and physical planning – using Q-method, an intensive qualitative and quantitative technique. Major differences and commonalities between perspectives are highlighted, in addition to actors’ arguments used to justify claims. Drawing upon an actor-oriented approach, results contribute filling a knowledge gap in the literature on the need to develop approaches that can guide adaptation thinking in development planning.

Dujardin, S, Hermesse, J & Dendoncker, N 2018, 'Making space for experiential knowledge in climate change adaptation?: Insights from planning officers in Bohol, Philippines' Jàmbá: Journal of Disaster Risk Studies, vol 10, no. 1, a433. DOI:10.4102/jamba.v10i1.433

Forget Y, Shimoni M, Gilbert M, Linard C. 2018. Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa. Preprints 2018100695 DOI: 10.20944/preprints201810.0695.v1.

Nieves JJ, Sorichetta A, Linard C, Bondarenko M, Steele J, Stevens F, Gaughan AE, Carioli A, Clarke D, Esch T, Tatem AJ. 2018. Modelling Built-Settlements between Remotely-Sensed Observations. Preprints 2018120250 DOI: 10.20944/preprints201812.0250.v1.

Forget Y, Linard C, Gilbert M, Shimoni M, Lopez J. 2018. Fusion Scheme for Automatic and Large-Scaled Built-up Mapping. In: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2072–2075. DOI: 10.1109/IGARSS.2018.8518266.

Steele JE, Nieves J, Tatem AJ, Forget Y, Shimoni M, Linard C. 2018. Worldpop - Fusion of Earth and Big Data for Intraurban Population Mapping. In: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. 2070–2071. DOI: 10.1109/IGARSS.2018.8518181.


De Longueville, F, Hountondji, Y-C, Djivo, VP, Ozer, P & Henry, S 2017, 'Impacts des aérosols sahariens sur la santé respiratoire des enfants en Afrique de l’Ouest : étude préliminaire dans le Bénin septentrional' Sciences et Changements Planétaires/Sécheresse.

Kabaria, CW, Gilbert, M, Noor, AM, Snow, RW & Linard, C 2017, 'The impact of urbanization and population density on childhood Plasmodium falciparum parasite prevalence rates in Africa' Malaria Journal, vol 16, no. 1, 49. DOI: 10.1186/s12936-017-1694-2

Linard C, Kabaria CW, Gilbert M, Tatem AJ, Gaughan AE, Stevens FR, Sorichetta A, Noor AM, Snow RW. 2017. Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009. International Journal of Digital Earth 10:1017–1029. https://doi.org/10.1080/17538947.2016.1275829.

Nieves Jeremiah J., Stevens Forrest R., Gaughan Andrea E., Linard Catherine, Sorichetta Alessandro, Hornby Graeme, Patel Nirav N., Tatem Andrew J. 2017. Examining the correlates and drivers of human population distributions across low- and middle-income countries. Journal of The Royal Society Interface 14:20170401. https://doi.org/10.1098/rsif.2017.0401.

Pezzulo C, Hornby GM, Sorichetta A, Gaughan AE, Linard C, Bird TJ, Kerr D, Lloyd CT, Tatem AJ. 2017. Sub-national mapping of population pyramids and dependency ratios in Africa and Asia. Scientific Data 4:170089. https://doi.org/10.1038/sdata.2017.89.


De Longueville F, Hountondji Y-C, Kindo I, Gemenne F, Ozer P. 2016. Long-term analysis of rainfall and temperature data in Burkina Faso (1950–2013). International Journal of Climatology 36:4393–4405. DOI: 10.1002/joc.4640.

Ignacio JAF, Cruz GT, Nardi F, Henry S. 2016. Assessing the effectiveness of a social vulnerability index in predicting heterogeneity in the impacts of natural hazards: Case study of the Tropical Storm Washi flood in the Philippines. Vienna Yearbook of Population Research 2015:91–129. DOI: 10.1553/populationyearbook2015s91.

Gaughan, AE, Stevens, FR, Huang, Z, Nieves, JJ, Sorichetta, A, Lai, S, Ye, X, Linard, C, Hornby, GM, Hay, SI, Yu, H & Tatem, AJ 2016, 'Spatiotemporal patterns of population in mainland China, 1990 to 2010' Scientific Data, vol 3, 160005. DOI: 10.1038/sdata.2016.5

Kabaria, CW, Molteni, F, Mandike, R, Chacky, F, Noor, AM, Snow, RW & Linard, C 2016, 'Mapping intra-urban malaria risk using high resolution satellite imagery: A case study of Dar es Salaam' International Journal of Health Geographics, vol 15, no. 1, 26. DOI: 10.1186/s12942-016-0051-y

Zickgraf C, Vigil S, De Longueville F, Ozer P, Gemenne F. 2016. The Impact of Vulnerability and Resilience to Environmental Changes on Mobility Patterns in West Africa. World Bank. link

Zu Erbach-Schoenberg, E, Alegana, VA, Sorichetta, A, Linard, C, Lourenço, C, Ruktanonchai, NW, Graupe, B, Bird, TJ, Pezzulo, C, Wesolowski, A & Tatem, AJ 2016, 'Dynamic denominators: The impact of seasonally varying population numbers on disease incidence estimates' Population Health Metrics, vol 14, no. 1, 35. DOI: 10.1186/s12963-016-0106-0