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Development cooperation actors have been addressing climate change as a cross-cutting issue and investing in climate adaptation projects since the early 2000s. More recently, as concern has risen about the potential impacts of climate variability and change on human mobility, development cooperation actors have begun to design projects that intentionally address the drivers of migration, including climate impacts on livelihoods. However, to date, we know little about the development cooperation’s role and function in responding to climate related mobility and migration. As such, the main aim of this paper is to outline the policy frameworks and approaches shaping development cooperation actors’ engagement and to identify areas for further exploration and investment. First, we frame the concept of climate mobility and migration and discuss some applicable policy frameworks that govern the issue from various perspectives; secondly, we review the toolbox of approaches that development cooperation actors bring to climate mobility; and third, we discuss the implications of the current Covid-19 pandemic and identify avenues for the way forward. We conclude that ensuring safe and orderly mobility and the decent reception and long-term inclusion of migrants and displaced persons under conditions of more severe climate hazards, and in the context of rising nationalism and xenophobia, poses significant challenges. Integrated approaches across multiple policy sectors and levels of governance are needed. In addition to resources, development cooperation actors can bring data to help empower the most affected communities and regions and leverage their convening power to foster more coordinated approaches within and across countries.
Robert Stojanov; Sarah Rosengaertner; Alex de Sherbinin; Raphael Nawrotzki. Climate Mobility and Development Cooperation. Population and Environment 2021, 1 -23.
AMA StyleRobert Stojanov, Sarah Rosengaertner, Alex de Sherbinin, Raphael Nawrotzki. Climate Mobility and Development Cooperation. Population and Environment. 2021; ():1-23.
Chicago/Turabian StyleRobert Stojanov; Sarah Rosengaertner; Alex de Sherbinin; Raphael Nawrotzki. 2021. "Climate Mobility and Development Cooperation." Population and Environment , no. : 1-23.
The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in disaster risk over time. Disaster databases are potentially useful tools for exploring trends, however, criteria for inclusion of events and for associated descriptive characteristics is not standardized. For example, some databases include only primary disaster types, such as ‘flood’, while others include subtypes, such as ‘coastal flood’ and ‘flash flood’. Here we outline a method to identify candidate events for assignment of a specific disaster subtype—namely, ‘flash floods’—from the corresponding primary disaster type—namely, ‘flood’. Geophysical data, including variables derived from remote sensing, are integrated to develop an enhanced flash flood confidence index, consisting of both a flash flood confidence index based on text mining of disaster reports and a flash flood susceptibility index from remote sensing derived geophysical data. This method was applied to a historical flood event dataset covering Ecuador. Results indicate the potential value of disaggregating events labeled as a primary disaster type into events of a particular subtype. The outputs are potentially useful for disaster risk reduction and vulnerability assessment if appropriately evaluated for fitness of use.
Andrew Kruczkiewicz; Agathe Bucherie; Fernanda Ayala; Carolynne Hultquist; Humberto Vergara; Simon Mason; Juan Bazo; Alex de Sherbinin. Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility. Remote Sensing 2021, 13, 2764 .
AMA StyleAndrew Kruczkiewicz, Agathe Bucherie, Fernanda Ayala, Carolynne Hultquist, Humberto Vergara, Simon Mason, Juan Bazo, Alex de Sherbinin. Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility. Remote Sensing. 2021; 13 (14):2764.
Chicago/Turabian StyleAndrew Kruczkiewicz; Agathe Bucherie; Fernanda Ayala; Carolynne Hultquist; Humberto Vergara; Simon Mason; Juan Bazo; Alex de Sherbinin. 2021. "Development of a Flash Flood Confidence Index from Disaster Reports and Geophysical Susceptibility." Remote Sensing 13, no. 14: 2764.
Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- and middle-income countries lack reliable or recent census data at the sufficiently fine spatial scales needed to monitor SDG progress. While the increasing abundance of Earth observation-derived gridded population products provides analysis-ready population estimates, end users lack clear use criteria to track SDGs indicators. In fact, recent comparisons of gridded population products identify wide variation across gridded population products. Here we present three case studies to illuminate how gridded population datasets compare in measuring and monitoring SDGs to advance the “fitness for use” guidance. Our focus is on SDG 11.5, which aims to reduce the number of people impacted by disasters. We use five gridded population datasets to measure and map hazard exposure for three case studies: the 2015 earthquake in Nepal; Cyclone Idai in Mozambique, Malawi, and Zimbabwe (MMZ) in 2019; and flash flood susceptibility in Ecuador. First, we map and quantify geographic patterns of agreement/disagreement across gridded population products for Nepal, MMZ, and Ecuador, including delineating urban and rural populations estimates. Second, we quantify the populations exposed to each hazard. Across hazards and geographic contexts, there were marked differences in population estimates across the gridded population datasets. As such, it is key that researchers, practitioners, and end users utilize multiple gridded population datasets—an ensemble approach—to capture uncertainty and/or provide range estimates when using gridded population products to track SDG indicators. To this end, we made available code and globally comprehensive datasets that allows for the intercomparison of gridded population products.
Cascade Tuholske; Andrea Gaughan; Alessandro Sorichetta; Alex de Sherbinin; Agathe Bucherie; Carolynne Hultquist; Forrest Stevens; Andrew Kruczkiewicz; Charles Huyck; Greg Yetman. Implications for Tracking SDG Indicator Metrics with Gridded Population Data. Sustainability 2021, 13, 7329 .
AMA StyleCascade Tuholske, Andrea Gaughan, Alessandro Sorichetta, Alex de Sherbinin, Agathe Bucherie, Carolynne Hultquist, Forrest Stevens, Andrew Kruczkiewicz, Charles Huyck, Greg Yetman. Implications for Tracking SDG Indicator Metrics with Gridded Population Data. Sustainability. 2021; 13 (13):7329.
Chicago/Turabian StyleCascade Tuholske; Andrea Gaughan; Alessandro Sorichetta; Alex de Sherbinin; Agathe Bucherie; Carolynne Hultquist; Forrest Stevens; Andrew Kruczkiewicz; Charles Huyck; Greg Yetman. 2021. "Implications for Tracking SDG Indicator Metrics with Gridded Population Data." Sustainability 13, no. 13: 7329.
Citizen science is an important vehicle for democratizing science and promoting the goal of universal and equitable access to scientific data and information. Data generated by citizen science groups have become an increasingly important source for scientists, applied users and those pursuing the 2030 Agenda for Sustainable Development. Citizen science data are used extensively in studies of biodiversity and pollution; crowdsourced data are being used by UN operational agencies for humanitarian activities; and citizen scientists are providing data relevant to monitoring the sustainable development goals (SDGs). This article provides an International Science Council (ISC) perspective on citizen science data generating activities in support of the 2030 Agenda and on needed improvements to the citizen science community's data stewardship practices for the benefit of science and society by presenting results of research undertaken by an ISC-sponsored Task Group.
Alex de Sherbinin; Anne Bowser; Tyng-Ruey Chuang; Caren Cooper; Finn Danielsen; Rorie Edmunds; Peter Elias; Elaine Faustman; Carolynne Hultquist; Rosy Mondardini; Ioana Popescu; Adenike Shonowo; Kishore Sivakumar. The Critical Importance of Citizen Science Data. Frontiers in Climate 2021, 3, 1 .
AMA StyleAlex de Sherbinin, Anne Bowser, Tyng-Ruey Chuang, Caren Cooper, Finn Danielsen, Rorie Edmunds, Peter Elias, Elaine Faustman, Carolynne Hultquist, Rosy Mondardini, Ioana Popescu, Adenike Shonowo, Kishore Sivakumar. The Critical Importance of Citizen Science Data. Frontiers in Climate. 2021; 3 ():1.
Chicago/Turabian StyleAlex de Sherbinin; Anne Bowser; Tyng-Ruey Chuang; Caren Cooper; Finn Danielsen; Rorie Edmunds; Peter Elias; Elaine Faustman; Carolynne Hultquist; Rosy Mondardini; Ioana Popescu; Adenike Shonowo; Kishore Sivakumar. 2021. "The Critical Importance of Citizen Science Data." Frontiers in Climate 3, no. : 1.
Conflict, drought, and locusts have been leading concerns for African food security in recent years, but the relative importance and spatiotemporal scales of crises resulting from each hazard is poorly characterized. Here we use continuous, subnational data from Sub-Saharan Africa to characterize how food crises differ according to livelihood strategy in response to each hazard. We find that when exposed to drought, pastoralists experienced more widespread, severe, and long-lasting food crises compared to those in agricultural zones. From 2009-2013 drought was the primary trigger of food security crises in all non-riverine zones; after 2013 conflict-related food security crises become prevalent. The few confirmed famines coincided with both conflict and drought. Locusts had little effect on food security during this time. These results provide multidimensional empirical evidence of how hazards affect food security in different livelihood zones, which provides an opportunity to improve scenario development in food security early warning forecasts.
Weston Anderson; Charles Taylor; Sonali Prabhat McDermid; Elisabeth Ilboudo-Nébié; Richard Seager; Wolfram Schlenker; Fabien Cottier; Alex De Sherbinin; Dara Mendeloff; Kelsey Markey. Characterizing the effect of drought, conflict, and locusts on food security in Africa. 2020, 1 .
AMA StyleWeston Anderson, Charles Taylor, Sonali Prabhat McDermid, Elisabeth Ilboudo-Nébié, Richard Seager, Wolfram Schlenker, Fabien Cottier, Alex De Sherbinin, Dara Mendeloff, Kelsey Markey. Characterizing the effect of drought, conflict, and locusts on food security in Africa. . 2020; ():1.
Chicago/Turabian StyleWeston Anderson; Charles Taylor; Sonali Prabhat McDermid; Elisabeth Ilboudo-Nébié; Richard Seager; Wolfram Schlenker; Fabien Cottier; Alex De Sherbinin; Dara Mendeloff; Kelsey Markey. 2020. "Characterizing the effect of drought, conflict, and locusts on food security in Africa." , no. : 1.
Anne Bowser; Caren Cooper; Alex De Sherbinin; Andrea Wiggins; Peter Brenton; Tyng-Ruey Chuang; Elaine Faustman; Mordechai (Muki) Haklay; Metis Meloche. Still in Need of Norms: The State of the Data in Citizen Science. Citizen Science: Theory and Practice 2020, 5, 1 .
AMA StyleAnne Bowser, Caren Cooper, Alex De Sherbinin, Andrea Wiggins, Peter Brenton, Tyng-Ruey Chuang, Elaine Faustman, Mordechai (Muki) Haklay, Metis Meloche. Still in Need of Norms: The State of the Data in Citizen Science. Citizen Science: Theory and Practice. 2020; 5 (1):1.
Chicago/Turabian StyleAnne Bowser; Caren Cooper; Alex De Sherbinin; Andrea Wiggins; Peter Brenton; Tyng-Ruey Chuang; Elaine Faustman; Mordechai (Muki) Haklay; Metis Meloche. 2020. "Still in Need of Norms: The State of the Data in Citizen Science." Citizen Science: Theory and Practice 5, no. 1: 1.
Social vulnerability indicators seek to identify populations susceptible to hazards based on aggregated sociodemographic data. Vulnerability indices are rarely validated with disaster outcome data at broad spatial scales, making it difficult to develop effective national scale strategies to mitigate loss for vulnerable populations. This paper validates social vulnerability indicators using two flood outcomes: death and damage. Regression models identify sociodemographic factors associated with variation in outcomes from 11,629 non-coastal flood events in the USA (2008–2012), controlling for flood intensity using stream gauge data. We compare models with (i) socioeconomic variables, (ii) the composite social vulnerability index (SoVI), and (iii) flood intensity variables only. The SoVI explains a larger portion of the variance in death (AIC = 2829) and damage (R2 = 0.125) than flood intensity alone (death—AIC = 2894; damage—R2 = 0.089), and models with individual sociodemographic factors perform best (death—AIC = 2696; damage—R2 = 0.229). Socioeconomic variables correlated with death (rural counties with a high proportion of elderly and young) differ from those related to property damage (rural counties with high percentage of Black, Hispanic and Native American populations below the poverty line). Results confirm that social vulnerability influences death and damage from floods in the USA. Model results indicate that social vulnerability models related to specific hazards and outcomes perform better than generic social vulnerability indices (e.g., SoVI) in predicting non-coastal flood death and damage. Hazard- and outcome-specific indices could be used to better direct efforts to ameliorate flood death and damage towards the people and places that need it most. Future validation studies should examine other flood outcomes, such as evacuation, migration and health, across scales.
Beth Tellman; Cody Schank; Bessie Schwarz; Peter Howe; Alex De Sherbinin. Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA. Sustainability 2020, 12, 6006 .
AMA StyleBeth Tellman, Cody Schank, Bessie Schwarz, Peter Howe, Alex De Sherbinin. Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA. Sustainability. 2020; 12 (15):6006.
Chicago/Turabian StyleBeth Tellman; Cody Schank; Bessie Schwarz; Peter Howe; Alex De Sherbinin. 2020. "Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA." Sustainability 12, no. 15: 6006.
Coastal areas worldwide represent an aggregation of population and assets of growing economic, geopolitical, and sociocultural significance, yet their functions are increasingly challenged by worsening coastal hazards. Vulnerability assessments have been recognized as one way we can better understand which geographic areas and segments of society are more susceptible to adverse impacts from different stressors or hazards. The aims of this paper are to evaluate the state of coastal vulnerability assessment mapping efforts and to identify opportunities for advancement and refinement that will lead to more cohesive, impactful, and policy-relevant coastal vulnerability studies. We conducted a systematic review of the literature that addresses physical and social vulnerability to coastal hazards and contains corresponding mapping products. The content was analyzed for the scale of analysis, location, disciplinary focus, conceptual framework, metrics used, methodological approach, data sources, mapping output, and policy relevance. Results showed that most Coastal Vulnerability Mapping Assessments (CVMAs) are conducted at the local level using a range of methodologies, often with limited inclusion of social considerations and limited discussion of policy relevance. Based on our analysis, we provide seven recommendations for the advancement of this field that would improve CVMAs’ methodological rigor, policy relevance, and alignment with other vulnerability assessment paradigms.
Anamaria Bukvic; Guillaume Rohat; Alex Apotsos; Alex De Sherbinin. A Systematic Review of Coastal Vulnerability Mapping. Sustainability 2020, 12, 2822 .
AMA StyleAnamaria Bukvic, Guillaume Rohat, Alex Apotsos, Alex De Sherbinin. A Systematic Review of Coastal Vulnerability Mapping. Sustainability. 2020; 12 (7):2822.
Chicago/Turabian StyleAnamaria Bukvic; Guillaume Rohat; Alex Apotsos; Alex De Sherbinin. 2020. "A Systematic Review of Coastal Vulnerability Mapping." Sustainability 12, no. 7: 2822.
Poverty alleviation resettlement (PAR) is a national rural development policy which uses resettlement as a tool for addressing environmental and poverty-related concerns in a rapidly changing world in China. It is regarded as one of the effective ways for the poor shaking off poverty in the implementation process of targeted poverty alleviation (TPA) strategy. Notable progress has been made in poverty alleviation for poverty-stricken people living in regions deemed unable to support sustainable livelihoods while problems have arisen during the process of its implementation. Based on literature review and a field survey, this paper attempts to conclude the beneficial policy as well as typical modes, problems and suggestions which might provide successful experience for regions to effectively implement the PAR projects and promote the management of rural resettlement. This article will offer a holistic and systematic research about China's PAR policy, which will make up for the lack of PAR researches in the context of targeted poverty alleviation. It will offer international experience for ending poverty by 2030 to achieve the Sustainable Development Goals (SDGs).
Yuanyuan Yang; Alex de Sherbinin; Yansui Liu. China's poverty alleviation resettlement: Progress, problems and solutions. Habitat International 2020, 98, 102135 .
AMA StyleYuanyuan Yang, Alex de Sherbinin, Yansui Liu. China's poverty alleviation resettlement: Progress, problems and solutions. Habitat International. 2020; 98 ():102135.
Chicago/Turabian StyleYuanyuan Yang; Alex de Sherbinin; Yansui Liu. 2020. "China's poverty alleviation resettlement: Progress, problems and solutions." Habitat International 98, no. : 102135.
Accelerated sea-level rise (SLR) is a major long-term outcome of climate change leading to increased inundation of low-lying areas and put global cities and coastal communities at greater risk. Building capacities at the community level to address the challenges of SLR is an important first step towards adaptation policy planning and decision-making. Building capacity through risk communication is a bottleneck challenge to translate complex climate science into policy and actions. To meet these challenges, this paper has put forth the research question as what information do the coastal stakeholders need and how does it need to be communicated in the context of SLR and to build capacities that favor for effective SLR policy planning and decision-making at the local level. As a result, we have evolved COREDAR (COmmunicating Risk of sea-level rise and Engaging stakeholDers in framing community-based Adaptation strategies), a climate service capacity building framework that provides an important exploratory study, examining the SLR risk communications and community-based adaptation, extending and clarifying certain findings within the current SLR literature. The framework highlight the need to consider the relevance of addressing SLR risk communication in a systemic and holistic approach that integrates science, society, and policy in SLR research, whilst at the same time pointing to some interesting directions for engaging local communities in the decision-making process for framing adaptation strategies that are community-centric. Importantly, this framework emphasizes the significance of climate communication strategies and use of climate information in policy planning and decision-making as one of the potential climate services for SLR risk research.
A. Saleem Khan; Robert S. Chen; Alex De Sherbinin. COREDAR: A Coastal Climate Service Framework on Sea-Level Rise Risk Communication for Adaptation Policy Planning. Climate Change Management 2020, 85 -104.
AMA StyleA. Saleem Khan, Robert S. Chen, Alex De Sherbinin. COREDAR: A Coastal Climate Service Framework on Sea-Level Rise Risk Communication for Adaptation Policy Planning. Climate Change Management. 2020; ():85-104.
Chicago/Turabian StyleA. Saleem Khan; Robert S. Chen; Alex De Sherbinin. 2020. "COREDAR: A Coastal Climate Service Framework on Sea-Level Rise Risk Communication for Adaptation Policy Planning." Climate Change Management , no. : 85-104.
This paper discusses the effects of long-term environmental change (represented by the abundance or scarcity relative to the long-term average level of crop yield/river flow) and short-term environmental shock (represented by the maximum number of consecutive years below the median crop yield/river flow per decade) on population redistribution in Mexico and Ethiopia. Crop production and water resources, which are affected by climate change and influence human survival and activities, were selected as research variables. Two developing countries, namely, Mexico and Ethiopia, were selected as comparison cases. The results showed that short-term environmental shocks had no correlation with population redistribution. Short-term environmental shocks might fail to influence migration decisions or cause only temporary displacements that cannot be detected by demographic statistics. Among the long-term environmental change factors, only crop yield deviation was found to have a significant positive correlation with population redistribution. Based on two different datasets and two different decades, crop yield deviation is positively correlated with population redistribution; the correlation coefficients between crop yield deviation and population redistribution were 0.134 to 0.162 in Mexico and 0.102 to 0.235 in Ethiopia. When urbanization was considered as the control variable, the correlation coefficient between crop yield deviation and population redistribution in Mexico dropped by half, while it was almost the same in Ethiopia. However, Ethiopia’s population redistribution was more clearly influenced by the population itself. Crop yield deviation relative to water flow deviation meant changes in livelihoods. Population redistribution is a possible means of adapting to changes in livelihood. Mexico exhibited high resilience to changes in livelihoods caused by long-term environmental change, especially in its densely populated areas. In contrast, Ethiopia was characterized mainly by high population growth and low population migration. People in some areas of Ethiopia were forced to endure hardship of livelihood deterioration or to stay where they were due to the difficulty of obtaining sufficient resources to afford the cost of migration.
Haibin Xia; Susana B. Adamo; Alex De Sherbinin; Bryan Jones. The Influence of Environmental Change (Crops and Water) on Population Redistribution in Mexico and Ethiopia. Applied Sciences 2019, 9, 5219 .
AMA StyleHaibin Xia, Susana B. Adamo, Alex De Sherbinin, Bryan Jones. The Influence of Environmental Change (Crops and Water) on Population Redistribution in Mexico and Ethiopia. Applied Sciences. 2019; 9 (23):5219.
Chicago/Turabian StyleHaibin Xia; Susana B. Adamo; Alex De Sherbinin; Bryan Jones. 2019. "The Influence of Environmental Change (Crops and Water) on Population Redistribution in Mexico and Ethiopia." Applied Sciences 9, no. 23: 5219.
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. In this article, we outline the key extensions of the People and Pixels foundation since 1998 and highlight several breakthroughs in research on human–environment interactions. We also identify pressing research problems—disaster, famine, drought, war, poverty, climate change—and explore how interdisciplinary approaches integrating people and pixels are being used to address them.
Tracy A. Kugler; Kathryn Grace; David J. Wrathall; Alex De Sherbinin; David Van Riper; Christoph Aubrecht; Douglas Comer; Susana Beatriz Adamo; Guido Cervone; Ryan Engstrom; Carolynne Hultquist; Andrea E. Gaughan; Catherine Linard; Emilio Moran; Forrest Stevens; Andrew J. Tatem; Beth Tellman; Jamon Van Den Hoek. People and Pixels 20 years later: the current data landscape and research trends blending population and environmental data. Population and Environment 2019, 41, 209 -234.
AMA StyleTracy A. Kugler, Kathryn Grace, David J. Wrathall, Alex De Sherbinin, David Van Riper, Christoph Aubrecht, Douglas Comer, Susana Beatriz Adamo, Guido Cervone, Ryan Engstrom, Carolynne Hultquist, Andrea E. Gaughan, Catherine Linard, Emilio Moran, Forrest Stevens, Andrew J. Tatem, Beth Tellman, Jamon Van Den Hoek. People and Pixels 20 years later: the current data landscape and research trends blending population and environmental data. Population and Environment. 2019; 41 (2):209-234.
Chicago/Turabian StyleTracy A. Kugler; Kathryn Grace; David J. Wrathall; Alex De Sherbinin; David Van Riper; Christoph Aubrecht; Douglas Comer; Susana Beatriz Adamo; Guido Cervone; Ryan Engstrom; Carolynne Hultquist; Andrea E. Gaughan; Catherine Linard; Emilio Moran; Forrest Stevens; Andrew J. Tatem; Beth Tellman; Jamon Van Den Hoek. 2019. "People and Pixels 20 years later: the current data landscape and research trends blending population and environmental data." Population and Environment 41, no. 2: 209-234.
Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.
Stefan Leyk; Andrea E. Gaughan; Susana B. Adamo; Alex de Sherbinin; Deborah Balk; Sergio Freire; Amy Rose; Forrest R. Stevens; Brian Blankespoor; Charlie Frye; Joshua Comenetz; Alessandro Sorichetta; Kytt MacManus; Linda Pistolesi; Marc Levy; Andrew J. Tatem; Martino Pesaresi. The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use. Earth System Science Data 2019, 11, 1385 -1409.
AMA StyleStefan Leyk, Andrea E. Gaughan, Susana B. Adamo, Alex de Sherbinin, Deborah Balk, Sergio Freire, Amy Rose, Forrest R. Stevens, Brian Blankespoor, Charlie Frye, Joshua Comenetz, Alessandro Sorichetta, Kytt MacManus, Linda Pistolesi, Marc Levy, Andrew J. Tatem, Martino Pesaresi. The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use. Earth System Science Data. 2019; 11 (3):1385-1409.
Chicago/Turabian StyleStefan Leyk; Andrea E. Gaughan; Susana B. Adamo; Alex de Sherbinin; Deborah Balk; Sergio Freire; Amy Rose; Forrest R. Stevens; Brian Blankespoor; Charlie Frye; Joshua Comenetz; Alessandro Sorichetta; Kytt MacManus; Linda Pistolesi; Marc Levy; Andrew J. Tatem; Martino Pesaresi. 2019. "The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use." Earth System Science Data 11, no. 3: 1385-1409.
Maps synthesizing climate, biophysical and socioeconomic data have become part of the standard tool‐kit for communicating the risks of climate change to society. Vulnerability maps are used to direct attention to geographic areas where impacts on society are expected to be greatest and that may therefore require adaptation interventions. Under the Green Climate Fund and other bilateral climate adaptation funding mechanisms, donors are investing billions of dollars of adaptation funds, often with guidance from modeling results, visualized and communicated through maps and spatial decision support tools. This paper presents the results of a systematic review of 84 studies that map social vulnerability to climate impacts. These assessments are compiled by interdisciplinary teams of researchers, span many regions, range in scale from local to global, and vary in terms of frameworks, data, methods, and thematic foci. The goal is to identify common approaches to mapping, evaluate their strengths and limitations, and offer recommendations and future directions for the field. The systematic review finds some convergence around common frameworks developed by the Intergovernmental Panel on Climate Change, frequent use of linear index aggregation, and common approaches to the selection and use of climate and socioeconomic data. Further, it identifies limitations such as a lack of future climate and socioeconomic projections in many studies, insufficient characterization of uncertainty, challenges in map validation, and insufficient engagement with policy audiences for those studies that purport to be policy relevant. Finally, it provides recommendations for addressing the identified shortcomings. This article is categorized under: Vulnerability and Adaptation to Climate Change > Values‐Based Approach to Vulnerability and Adaptation
Alex de Sherbinin; Anamaria Bukvic; Guillaume Rohat; Melanie Gall; Brent McCusker; Benjamin Preston; Alex Apotsos; Carolyn Fish; Stefan Kienberger; Park Muhonda; Olga Wilhelmi; Denis Macharia; William Shubert; Richard Sliuzas; Brian Tomaszewski; Sainan Zhang. Climate vulnerability mapping: A systematic review and future prospects. WIREs Climate Change 2019, 10, 1 .
AMA StyleAlex de Sherbinin, Anamaria Bukvic, Guillaume Rohat, Melanie Gall, Brent McCusker, Benjamin Preston, Alex Apotsos, Carolyn Fish, Stefan Kienberger, Park Muhonda, Olga Wilhelmi, Denis Macharia, William Shubert, Richard Sliuzas, Brian Tomaszewski, Sainan Zhang. Climate vulnerability mapping: A systematic review and future prospects. WIREs Climate Change. 2019; 10 (5):1.
Chicago/Turabian StyleAlex de Sherbinin; Anamaria Bukvic; Guillaume Rohat; Melanie Gall; Brent McCusker; Benjamin Preston; Alex Apotsos; Carolyn Fish; Stefan Kienberger; Park Muhonda; Olga Wilhelmi; Denis Macharia; William Shubert; Richard Sliuzas; Brian Tomaszewski; Sainan Zhang. 2019. "Climate vulnerability mapping: A systematic review and future prospects." WIREs Climate Change 10, no. 5: 1.
The Brazilian Amazon contains the most active rainforest frontier in the world, and its socioeconomic, demographic and spatial dynamism has been a topic of interest for academics and policy makers for decades. In this paper, we use spatial statistical modeling to examine the context of migration in the Brazilian Amazon by investigating its socioeconomic, demographic, spatial and environmental heterogeneities at the municipal level between 2000 and 2010. First, we visualized the spatial distribution of net-migration, in-migration and out-migration rates among municipalities in the Brazilian Amazon. Then, we explored the presence of spatial autocorrelation using Global Moran's I Index, and use spatial modeling techniques to investigate the associations between response variables (in-migration and out-migration) and selected explanatory variables. We identified several in-migration frontiers in the region, especially in Center Mato Grosso and Southeast Pará, while out-migration seems more diffuse in the Amazonia territory. Global Moran's I scores indicate that most of the selected variables exhibit spatial dependence, and the spatial regression models present better estimates of the coefficients by incorporating the spatially lagged autoregressive parameter. Our results also confirm the spatial heterogeneity and multidimensional character of in-migration and out-migration in the Brazilian Amazon. Economic growth, regional inequality and the environmental dynamism of the rainforest frontier appear to be closely associated with the intensity of migration flows in the region. We also find that less-populated municipalities have a central role in regional migration dynamics, forming relevant in-migration frontiers and ensuring territorial robustness for migration in the region.
Douglas Sathler; Susana Adamo; Everton E.C. Lima; Diego Rodrigues Macedo; Alex de Sherbinin; Paola Kim-Blanco. Assessing the regional context of migration in the Brazilian Amazon through spatial regression modeling. Applied Geography 2019, 109, 102042 .
AMA StyleDouglas Sathler, Susana Adamo, Everton E.C. Lima, Diego Rodrigues Macedo, Alex de Sherbinin, Paola Kim-Blanco. Assessing the regional context of migration in the Brazilian Amazon through spatial regression modeling. Applied Geography. 2019; 109 ():102042.
Chicago/Turabian StyleDouglas Sathler; Susana Adamo; Everton E.C. Lima; Diego Rodrigues Macedo; Alex de Sherbinin; Paola Kim-Blanco. 2019. "Assessing the regional context of migration in the Brazilian Amazon through spatial regression modeling." Applied Geography 109, no. : 102042.
Urbanization poses significant challenges on sustainable development, disaster resilience, climate change mitigation, and environmental and resource management. Accurate urban extent datasets at large spatial scales are essential for researchers and policymakers to better understand urbanization dynamics and its socioeconomic drivers and impacts. While high-resolution urban extent data products - including the Global Human Settlements Layer (GHSL), the Global Man-Made Impervious Surface (GMIS), the Global Human Built-Up and Settlement Extent (HBASE), and the Global Urban Footprint (GUF) - have recently become available, intermediate-resolution urban extent data products including the 1 km SEDAC’s Global Rural-Urban Mapping Project (GRUMP), MODIS 1km, and MODIS 500 m still have many users and have been demonstrated in a recent study to be more appropriate in urbanization process analysis (around 500 m resolution) than those at higher resolutions (30 m). The objective of this study is to improve large-scale urban extent mapping at an intermediate resolution (500 m) using machine learning methods through combining the complementary nighttime Visible Infrared Imaging Radiometer Suite (VIIRS) and daytime Moderate Resolution Imaging Spectroradiometer (MODIS) data, taking the conterminous United States (CONUS) as the study area. The effectiveness of commonly-used machine learning methods, including random forest (RF), gradient boosting machine (GBM), neural network (NN), and their ensemble (ESB), has been explored. Our results show that these machine learning methods can achieve similar high accuracies across all accuracy metrics (>95% overall accuracy, >98% producer’s accuracy, and >92% user’s accuracy) with Kappa coefficients greater than 0.90, which have not been achieved in the existing data products or by previous studies; the ESB is not able to produce significantly better accuracies than individual machine learning methods; the total misclassifications generated by GBM are more than those generated by RF, NN, and ESB by 14%, 16%, and 11%, respectively, with NN having the least total misclassifications. This indicates that using these machine learning methods, especially NN and RF, with the combination of VIIRS nighttime light and MODIS daytime normalized difference vegetation index (NDVI) data, high accuracy intermediate-resolution urban extent data products at large spatial scales can be achieved. The methodology has the potential to be applied to annual continental-to-global scale urban extent mapping at intermediate resolutions.
Xue Liu; Alex De Sherbinin; Yanni Zhan. Mapping Urban Extent at Large Spatial Scales Using Machine Learning Methods with VIIRS Nighttime Light and MODIS Daytime NDVI Data. Remote Sensing 2019, 11, 1247 .
AMA StyleXue Liu, Alex De Sherbinin, Yanni Zhan. Mapping Urban Extent at Large Spatial Scales Using Machine Learning Methods with VIIRS Nighttime Light and MODIS Daytime NDVI Data. Remote Sensing. 2019; 11 (10):1247.
Chicago/Turabian StyleXue Liu; Alex De Sherbinin; Yanni Zhan. 2019. "Mapping Urban Extent at Large Spatial Scales Using Machine Learning Methods with VIIRS Nighttime Light and MODIS Daytime NDVI Data." Remote Sensing 11, no. 10: 1247.
Many human populations are dependent on marine ecosystems for a range of benefits, but we understand little about where and to what degree people rely on these ecosystem services. We created a new conceptual model to map the degree of human dependence on marine ecosystems based on the magnitude of the benefit, susceptibility of people to a loss of that benefit, and the availability of alternatives. We focused on mapping nutritional, economic, and coastal protection dependence, but our model is repeatable, scalable, applicable to other ecosystems, and designed to incorporate additional services and data. Here we show that dependence was highest for Pacific and Indian Ocean island nations and several West African countries. More than 775 million people live in areas with relatively high dependence scores. By identifying where and how people are dependent on marine ecosystems, our framework can be used to design more effective large‐scale management and policy interventions.
Elizabeth R. Selig; David G. Hole; Edward H. Allison; Katie K. Arkema; Madeleine C. McKinnon; Jingjie Chu; Alex de Sherbinin; Brendan Fisher; Louise Glew; Margaret B. Holland; Jane Carter Ingram; Nalini S. Rao; Roly B. Russell; Tanja Srebotnjak; Lydia C.L. Teh; Sebastian Troëng; Will R. Turner; Alexander Zvoleff. Mapping global human dependence on marine ecosystems. Conservation Letters 2018, 12, 1 .
AMA StyleElizabeth R. Selig, David G. Hole, Edward H. Allison, Katie K. Arkema, Madeleine C. McKinnon, Jingjie Chu, Alex de Sherbinin, Brendan Fisher, Louise Glew, Margaret B. Holland, Jane Carter Ingram, Nalini S. Rao, Roly B. Russell, Tanja Srebotnjak, Lydia C.L. Teh, Sebastian Troëng, Will R. Turner, Alexander Zvoleff. Mapping global human dependence on marine ecosystems. Conservation Letters. 2018; 12 (2):1.
Chicago/Turabian StyleElizabeth R. Selig; David G. Hole; Edward H. Allison; Katie K. Arkema; Madeleine C. McKinnon; Jingjie Chu; Alex de Sherbinin; Brendan Fisher; Louise Glew; Margaret B. Holland; Jane Carter Ingram; Nalini S. Rao; Roly B. Russell; Tanja Srebotnjak; Lydia C.L. Teh; Sebastian Troëng; Will R. Turner; Alexander Zvoleff. 2018. "Mapping global human dependence on marine ecosystems." Conservation Letters 12, no. 2: 1.
The debate on “Loss and Damage” (L&D) has gained traction over the last few years. Supported by growing scientific evidence of anthropogenic climate change amplifying frequency, intensity and duration of climate-related hazards as well as observed increases in climate-related impacts and risks in many regions, the “Warsaw International Mechanism for Loss and Damage” was established in 2013 and further supported through the Paris Agreement in 2015. Despite advances, the debate currently is broad, diffuse and somewhat confusing, while concepts, methods and tools, as well as directions for policy remain vague and often contested. This book, a joint effort of the Loss and Damage Network—a partnership effort by scientists and practitioners from around the globe—provides evidence-based insight into the L&D discourse by highlighting state-of-the-art research conducted across multiple disciplines, by showcasing applications in practice and by providing insight into policy contexts and salient policy options. This introductory chapter summarises key findings of the twenty-two book chapters in terms of five propositions. These propositions, each building on relevant findings linked to forward-looking suggestions for research, policy and practice, reflect the architecture of the book, whose sections proceed from setting the stage to critical issues, followed by a section on methods and tools, to chapters that provide geographic perspectives, and finally to a section that identifies potential policy options. The propositions comprise (1) Risk management can be an effective entry point for aligning perspectives and debates, if framed comprehensively, coupled with climate justice considerations and linked to established risk management and adaptation practice; (2) Attribution science is advancing rapidly and fundamental to informing actions to minimise, avert, and address losses and damages; (3) Climate change research, in addition to identifying physical/hard limits to adaptation, needs to more systematically examine soft limits to adaptation, for which we find some evidence across several geographies globally; (4) Climate risk insurance mechanisms can serve the prevention and cure aspects emphasised in the L&D debate but solidarity and accountability aspects need further attention, for which we find tentative indication in applications around the world; (5) Policy deliberations may need to overcome the perception that L&D constitutes a win-lose negotiation “game” by developing a more inclusive narrative that highlights collective ambition for tackling risks, mutual benefits and the role of transformation.
Reinhard Mechler; Elisa Calliari; Laurens M. Bouwer; Thomas Schinko; Swenja Surminski; Joanne Linnerooth-Bayer; Jeroen Aerts; Wouter Botzen; Emily Boyd; Natalie Delia Deckard; Jan S. Fuglestvedt; Mikel González-Eguino; Marjolijn Haasnoot; John Handmer; MasroorA Haque; Alison Heslin; Stefan Hochrainer-Stigler; Christian Huggel; Saleemul Huq; Rachel James; Richard G. Jones; Sirkku Juhola; Adriana Keating; Stefan Kienberger; Sönke Kreft; Onno Kuik; Mia Landauer; Finn Laurien; Judy Lawrence; Ana Lopez; Wei Liu; Piotr Magnuszewski; Anil Markandya; Benoit Mayer; Ian McCallum; Colin McQuistan; Lukas Meyer; Kian Mintz-Woo; Arianna Montero-Colbert; Jaroslav Mysiak; Johanna Nalau; Ilan Noy; Robert Oakes; Friederike E. L. Otto; Mousumi Pervin; Erin Roberts; Laura Schäfer; Paolo Scussolini; Olivia Serdeczny; Alex De Sherbinin; Florentina Simlinger; Asha Sitati; Saibeen Sultana; Hannah R. Young; Kees Van Der Geest; Marc Van Den Homberg; Ivo Wallimann-Helmer; Koko Warner; Zinta Zommers. Science for Loss and Damage. Findings and Propositions. Climate Risk Management, Policy and Governance 2018, 3 -37.
AMA StyleReinhard Mechler, Elisa Calliari, Laurens M. Bouwer, Thomas Schinko, Swenja Surminski, Joanne Linnerooth-Bayer, Jeroen Aerts, Wouter Botzen, Emily Boyd, Natalie Delia Deckard, Jan S. Fuglestvedt, Mikel González-Eguino, Marjolijn Haasnoot, John Handmer, MasroorA Haque, Alison Heslin, Stefan Hochrainer-Stigler, Christian Huggel, Saleemul Huq, Rachel James, Richard G. Jones, Sirkku Juhola, Adriana Keating, Stefan Kienberger, Sönke Kreft, Onno Kuik, Mia Landauer, Finn Laurien, Judy Lawrence, Ana Lopez, Wei Liu, Piotr Magnuszewski, Anil Markandya, Benoit Mayer, Ian McCallum, Colin McQuistan, Lukas Meyer, Kian Mintz-Woo, Arianna Montero-Colbert, Jaroslav Mysiak, Johanna Nalau, Ilan Noy, Robert Oakes, Friederike E. L. Otto, Mousumi Pervin, Erin Roberts, Laura Schäfer, Paolo Scussolini, Olivia Serdeczny, Alex De Sherbinin, Florentina Simlinger, Asha Sitati, Saibeen Sultana, Hannah R. Young, Kees Van Der Geest, Marc Van Den Homberg, Ivo Wallimann-Helmer, Koko Warner, Zinta Zommers. Science for Loss and Damage. Findings and Propositions. Climate Risk Management, Policy and Governance. 2018; ():3-37.
Chicago/Turabian StyleReinhard Mechler; Elisa Calliari; Laurens M. Bouwer; Thomas Schinko; Swenja Surminski; Joanne Linnerooth-Bayer; Jeroen Aerts; Wouter Botzen; Emily Boyd; Natalie Delia Deckard; Jan S. Fuglestvedt; Mikel González-Eguino; Marjolijn Haasnoot; John Handmer; MasroorA Haque; Alison Heslin; Stefan Hochrainer-Stigler; Christian Huggel; Saleemul Huq; Rachel James; Richard G. Jones; Sirkku Juhola; Adriana Keating; Stefan Kienberger; Sönke Kreft; Onno Kuik; Mia Landauer; Finn Laurien; Judy Lawrence; Ana Lopez; Wei Liu; Piotr Magnuszewski; Anil Markandya; Benoit Mayer; Ian McCallum; Colin McQuistan; Lukas Meyer; Kian Mintz-Woo; Arianna Montero-Colbert; Jaroslav Mysiak; Johanna Nalau; Ilan Noy; Robert Oakes; Friederike E. L. Otto; Mousumi Pervin; Erin Roberts; Laura Schäfer; Paolo Scussolini; Olivia Serdeczny; Alex De Sherbinin; Florentina Simlinger; Asha Sitati; Saibeen Sultana; Hannah R. Young; Kees Van Der Geest; Marc Van Den Homberg; Ivo Wallimann-Helmer; Koko Warner; Zinta Zommers. 2018. "Science for Loss and Damage. Findings and Propositions." Climate Risk Management, Policy and Governance , no. : 3-37.
The accurate monitoring and measurement of emission reductions is a critical step in Reducing Emissions from Deforestation and Degradation (REDD+). However, the existence of uncertainty in emission reduction estimates affects the performance of REDD+ projects. We assert that incentive could be a valuable policy tool for reducing monitoring errors and transaction costs. Using Stackelberg models and simulation research, this paper examines the effects of uncertainty and incentive on performance and stakeholder benefits of REDD+ projects. Finally, the uncertainties in REDD+ projects are further discussed, and equilibrium errors, emission reductions, and stakeholder benefits in different scenarios are compared. The results show that errors do affect the measured value of carbon emissions and compensation payments. However, incentive for investors can reduce monitoring errors and improve the performance of REDD+ projects. Therefore, in the future, incentive should be provided to investors rather than landholders.
Jichuan Sheng; Weihai Zhou; Alex De Sherbinin. Uncertainty in Estimates, Incentives, and Emission Reductions in REDD+ Projects. International Journal of Environmental Research and Public Health 2018, 15, 1544 .
AMA StyleJichuan Sheng, Weihai Zhou, Alex De Sherbinin. Uncertainty in Estimates, Incentives, and Emission Reductions in REDD+ Projects. International Journal of Environmental Research and Public Health. 2018; 15 (7):1544.
Chicago/Turabian StyleJichuan Sheng; Weihai Zhou; Alex De Sherbinin. 2018. "Uncertainty in Estimates, Incentives, and Emission Reductions in REDD+ Projects." International Journal of Environmental Research and Public Health 15, no. 7: 1544.
Cambridge Core - Climatology and Climate Change - Climate Change and Cities - edited by Cynthia Rosenzweig
Tom Bowman; Daniel A. Bader; Reginald Blake; Alice Grimm; Rafiq Hamdi; Yeonjoo Kim; Radley Horton; Keith Alverson; Stuart Gaffin; Stuart Crane; Ebru Gencer; Regina Folorunsho; Megan Linkin; XiaoMing Wang; Claudia E. Natenzon; Shiraz Wajih; Nivedita Mani; Maricarmen Esquivel; Hori Tsuneki; Ricardo Castro; Mattia Federico Leone; Panjwani Dilnoor; Romero-Lankao Patricia; Solecki William; Brenda Lin; Abhilash Panda; Stelios Grafakos; Chantal Pacteau; Martha Delgado; Mia Landauer; Oswaldo Lucon; Patrick Driscoll; David Wilk; Carolina Zambrano; Sean O’Donoghue; Debra Roberts; Jeffrey Raven; Brian Stone; Gerald Mills; Joel Towers; Lutz Katzschner; Pascaline Gaborit; Matei Georgescu; Maryam Hariri; James Lee; Jeffrey Lejava; Ayyoob Sharifi; Cristina Visconti; Andrew Rudd; Diana Reckien; Shuaib Lwasa; David Satterthwaite; Darryn McEvoy; Felix Creutzig; Mark Montgomery; Daniel Schensul; Deborah Balk; Iqbal Alam Khan; Blanca Fernandez; Donald Brown; Juan Camilo Osorio; Marcela Tovar-Restrepo; Alex De Sherbinin; Wim Feringa; Alice Sverdlik; Emma Porio; Abhishek Nair; Sabrina McCormick; Eddie Bautista; Reimund Schwarze; Peter B. Meyer; Anil Markandya; Shailly Kedia; David Maleki; María Victoria Román De Lara; Tomonori Sudo; Swenja Surminski; Nancy Anderson; Marta Olazabal; Saliha Dobardzic; Timon McPhearson; Madhav Karki; Cecilia Herzog; Helen Santiago Fink; Luc Abbadie; Peleg Kremer; Christopher M. Clark; Matthew I. Palmer; Katia Perini; Marielle Dubbeling; Richard J. Dawson; M. Shah Alam Khan; Vivien Gornitz; Maria Fernanda Lemos; Larry Atkinson; Julie Pullen; Lindsay Usher; Martha M. L. Barata; Patrick L. Kinney; Keith Dear; Eva Ligeti; Kristie L. Ebi; Jeremy Hess; Thea Dickinson; Ashlinn K. Quinn; Martin Obermaier; Denise Silva Sousa; Darby Jack; Livia Marinho; Felipe Vommaro; Kai Chen; Claudine Dereczynski; Mariana Carvalho; Diana Pinheiro Marinho; Nathalie Jean-Baptiste; Veronica Olivotto; Wilbard Kombe; Antonia Yulo-Loyzaga; Mussa Natty. Climate Change and Cities. Climate Change and Cities 2018, 1 .
AMA StyleTom Bowman, Daniel A. Bader, Reginald Blake, Alice Grimm, Rafiq Hamdi, Yeonjoo Kim, Radley Horton, Keith Alverson, Stuart Gaffin, Stuart Crane, Ebru Gencer, Regina Folorunsho, Megan Linkin, XiaoMing Wang, Claudia E. Natenzon, Shiraz Wajih, Nivedita Mani, Maricarmen Esquivel, Hori Tsuneki, Ricardo Castro, Mattia Federico Leone, Panjwani Dilnoor, Romero-Lankao Patricia, Solecki William, Brenda Lin, Abhilash Panda, Stelios Grafakos, Chantal Pacteau, Martha Delgado, Mia Landauer, Oswaldo Lucon, Patrick Driscoll, David Wilk, Carolina Zambrano, Sean O’Donoghue, Debra Roberts, Jeffrey Raven, Brian Stone, Gerald Mills, Joel Towers, Lutz Katzschner, Pascaline Gaborit, Matei Georgescu, Maryam Hariri, James Lee, Jeffrey Lejava, Ayyoob Sharifi, Cristina Visconti, Andrew Rudd, Diana Reckien, Shuaib Lwasa, David Satterthwaite, Darryn McEvoy, Felix Creutzig, Mark Montgomery, Daniel Schensul, Deborah Balk, Iqbal Alam Khan, Blanca Fernandez, Donald Brown, Juan Camilo Osorio, Marcela Tovar-Restrepo, Alex De Sherbinin, Wim Feringa, Alice Sverdlik, Emma Porio, Abhishek Nair, Sabrina McCormick, Eddie Bautista, Reimund Schwarze, Peter B. Meyer, Anil Markandya, Shailly Kedia, David Maleki, María Victoria Román De Lara, Tomonori Sudo, Swenja Surminski, Nancy Anderson, Marta Olazabal, Saliha Dobardzic, Timon McPhearson, Madhav Karki, Cecilia Herzog, Helen Santiago Fink, Luc Abbadie, Peleg Kremer, Christopher M. Clark, Matthew I. Palmer, Katia Perini, Marielle Dubbeling, Richard J. Dawson, M. Shah Alam Khan, Vivien Gornitz, Maria Fernanda Lemos, Larry Atkinson, Julie Pullen, Lindsay Usher, Martha M. L. Barata, Patrick L. Kinney, Keith Dear, Eva Ligeti, Kristie L. Ebi, Jeremy Hess, Thea Dickinson, Ashlinn K. Quinn, Martin Obermaier, Denise Silva Sousa, Darby Jack, Livia Marinho, Felipe Vommaro, Kai Chen, Claudine Dereczynski, Mariana Carvalho, Diana Pinheiro Marinho, Nathalie Jean-Baptiste, Veronica Olivotto, Wilbard Kombe, Antonia Yulo-Loyzaga, Mussa Natty. Climate Change and Cities. Climate Change and Cities. 2018; ():1.
Chicago/Turabian StyleTom Bowman; Daniel A. Bader; Reginald Blake; Alice Grimm; Rafiq Hamdi; Yeonjoo Kim; Radley Horton; Keith Alverson; Stuart Gaffin; Stuart Crane; Ebru Gencer; Regina Folorunsho; Megan Linkin; XiaoMing Wang; Claudia E. Natenzon; Shiraz Wajih; Nivedita Mani; Maricarmen Esquivel; Hori Tsuneki; Ricardo Castro; Mattia Federico Leone; Panjwani Dilnoor; Romero-Lankao Patricia; Solecki William; Brenda Lin; Abhilash Panda; Stelios Grafakos; Chantal Pacteau; Martha Delgado; Mia Landauer; Oswaldo Lucon; Patrick Driscoll; David Wilk; Carolina Zambrano; Sean O’Donoghue; Debra Roberts; Jeffrey Raven; Brian Stone; Gerald Mills; Joel Towers; Lutz Katzschner; Pascaline Gaborit; Matei Georgescu; Maryam Hariri; James Lee; Jeffrey Lejava; Ayyoob Sharifi; Cristina Visconti; Andrew Rudd; Diana Reckien; Shuaib Lwasa; David Satterthwaite; Darryn McEvoy; Felix Creutzig; Mark Montgomery; Daniel Schensul; Deborah Balk; Iqbal Alam Khan; Blanca Fernandez; Donald Brown; Juan Camilo Osorio; Marcela Tovar-Restrepo; Alex De Sherbinin; Wim Feringa; Alice Sverdlik; Emma Porio; Abhishek Nair; Sabrina McCormick; Eddie Bautista; Reimund Schwarze; Peter B. Meyer; Anil Markandya; Shailly Kedia; David Maleki; María Victoria Román De Lara; Tomonori Sudo; Swenja Surminski; Nancy Anderson; Marta Olazabal; Saliha Dobardzic; Timon McPhearson; Madhav Karki; Cecilia Herzog; Helen Santiago Fink; Luc Abbadie; Peleg Kremer; Christopher M. Clark; Matthew I. Palmer; Katia Perini; Marielle Dubbeling; Richard J. Dawson; M. Shah Alam Khan; Vivien Gornitz; Maria Fernanda Lemos; Larry Atkinson; Julie Pullen; Lindsay Usher; Martha M. L. Barata; Patrick L. Kinney; Keith Dear; Eva Ligeti; Kristie L. Ebi; Jeremy Hess; Thea Dickinson; Ashlinn K. Quinn; Martin Obermaier; Denise Silva Sousa; Darby Jack; Livia Marinho; Felipe Vommaro; Kai Chen; Claudine Dereczynski; Mariana Carvalho; Diana Pinheiro Marinho; Nathalie Jean-Baptiste; Veronica Olivotto; Wilbard Kombe; Antonia Yulo-Loyzaga; Mussa Natty. 2018. "Climate Change and Cities." Climate Change and Cities , no. : 1.