Reliable representations of global urban extent remain limited, hindering scientific progress across a range of disciplines that study functionality of sustainable cities. We present an efficient and ...low-cost machine-learning approach for pixel-based image classification of built-up areas at a large geographic scale using Landsat data. Our methodology combines nighttime-lights data and Landsat 8 and overcomes the lack of extensive ground-reference data. We demonstrate the effectiveness of our methodology, which is implemented in Google Earth Engine, through the development of accurate 30m resolution maps that characterize built-up land cover in three geographically diverse countries: India, Mexico, and the US. Our approach highlights the usefulness of data fusion techniques for studying the built environment and is a first step towards the creation of an accurate global-scale map of urban land cover over time.
•An approach is proposed to map built-up land cover at a large geographical scale.•Our data fusion approach utilizes nighttime-lights data and Landsat imagery.•The approach overcomes the lack of extensive ground-reference data for urban research.•Hexagonal tessellation partition improves classification of heterogeneous land cover.•High quality maps of built-up LC are produced for 3 geographically diverse countries.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Infrastructure development is central to the processes that abate and produce vulnerabilities in cities. Urban actors, especially those with power and authority, perceive and interpret vulnerability ...and decide when and how to adapt. When city managers use infrastructure to reduce urban risk in the complex, interconnected city system, new fragilities are introduced because of inherent system feedbacks. We trace the interactions between system dynamics and decision-making processes over 700 years of Mexico City’s adaptations to water risks, focusing on the decision cycles of public infrastructure providers (in this case, government authorities). We bring together two lenses in examining this history: robustness-vulnerability trade-offs to explain the evolution of systemic risk dynamics mediated by feedback control, and adaptation pathways to focus on the evolution of decision cycles that motivate significant infrastructure investments. Drawing from historical accounts, archeological evidence, and original research on water, engineering, and cultural history, we examine adaptation pathways of humans settlement, water supply, and flood risk. Mexico City’s history reveals insights that expand the theory of coupled infrastructure and lessons salient to contemporary urban risk management: (1) adapting by spatially externalizing risks can backfire: as cities expand, such risks become endogenous; (2) over time, adaptation pathways initiated to address specific risks may begin to intersect, creating complex trade-offs in risk management; and (3) city authorities are agents of risk production: even in the face of new exogenous risks (climate change), acknowledging and managing risks produced endogenously may prove more adaptive. History demonstrates that the very best solutions today may present critical challenges for tomorrow, and that collectively people have far more agency in and influence over the complex systems we live in than is often acknowledged.
A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at ...which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential 'narco-capitalized' signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country- and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F = 9.90, p = 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio = 2.98, p = 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.
Global flood models (GFMs) and earth observation (EO) play a crucial role in characterising flooding, especially in data-sparse, under-resourced regions of the world. However, validation studies are ...often limited to a handful of historic events and do not directly assess the ability of these products to simulate flood hazard-the probability that flooding will occur in a given location. As a result, it is difficult for stakeholders to decipher the ability of either models or observations to identify flood hazard and make decisions to mitigate for flooding. Here, we leverage flood observations from 20 years of MODIS data to compare the recorded flooding with what would be expected given the hazard simulated by a GFM. We devise an approach, Flood Expectation Per Pixel, and apply it across four large basins in Africa-Congo, Niger, Nile and Volta representing a variety of biomes. We estimate the uncertainty of EO to capture flood events due to burned areas, cloud cover and vegetation, incorporating uncertainty estimates when comparing to modelled hazard. We found that at lower return periods (RPs) (<20 years), the EO data records less flooding than the GFM, suggesting GFMs overpredict frequent flooding. For RPs between 50 and 100 years, GFM and EO data show greater consistency given the uncertainties we consider. For large RPs (100 years) the EO observations show more flooding than expected given the GFM data, potentially due to data errors and non-fluvial flooding, however there are too few observations to draw significant conclusions at these RPs. The EO record indicates that the GFM can differentiate between flood RPs. We find EO and GFM complement each other and thus should be used in tandem to inform strategies to mitigate floods across the hazard spectrum from frequent to extreme flood events.
Informal urban land expansion is produced through a diversity of social and political transactions, yet 'pixelizable' data capturing these transactions is commonly unavailable. Understanding informal ...urbanization entails differentiating spatial patterns of informal settlement from formal growth, associating such patterns with the social transactions that produce them, and evaluating the social and environmental outcomes of distinct settlement types. Demonstrating causality between distinct urban spatial patterns and social-institutional processes requires both high-resolution spatial temporal time-series data of urban change and insights into social transactions giving rise to these patterns. We demonstrate an example of linking distinct spatial patterns of informal urban expansion to the institutional processes each engenders in Mexico City. The approach presented here can be applied across cases, potentially improving land projection models in the rapidly urbanizing Global South, characterized by high informality. We conclude with a research agenda to identify, project, and evaluate informal urban expansion patterns.
The most alarming finding of the study is that the impact of the second drought or flood was larger than that of the first in all but two cases in which it was the more extreme event - no matter how ...much risk management had been undertaken, or to what extent exposure and vulnerability had been reduced. Managing flood risk by constructing levees, or drought risk by expanding irrigation infrastructure, can also backfire, because these developments incentivize people to settle in floodplains or start new agricultural activities in droughtprone areas. ...the discriminatory practice known as redlining, in which financial services were withheld from communities of colour in the United States - intentionally excluding them from access to capital investment - has led to inadequate flood-mitigation infrastructure in these communities and increased exposure to disaster (see go.nature.com/3cpp3mz). In facing these challenges, it is not risk management that is needed, but rather transformation, a concept embraced by the growing number of climate-justice activists and researchers14, as well as by the Intergovernmental Panel on Climate Change in this year's report on impacts, adaptation and vulnerability15.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Governments, development banks, corporations, and nonprofits are increasingly considering the potential contribution of watershed conservation activities to secure clean water for cities and to ...reduce flood risk. These organizations, however, often lack decision-relevant, initial screening information across multiple cities to identify which specific city-watershed combinations present not only water-related risks but also potentially attractive opportunities for mitigation via natural infrastructure approaches. To address this need, this paper presents a novel methodology for a continental assessment of the potential for watershed conservation activities to improve surface drinking water quality and mitigate riverine and stormwater flood risks in 70 major cities across Latin America. We used publicly available geospatial data to analyze 887 associated watersheds. Water quality metrics assessed the potential for agricultural practices, afforestation, riparian buffers, and forest conservation to mitigate sediment and phosphorus loads. Flood reduction metrics analyzed the role of increasing infiltration, restoring riparian wetlands, and reducing connected impervious surface to mitigate riverine and stormwater floods for exposed urban populations. Cities were then categorized based on relative opportunity potential to reduce identified risks through watershed conservation activities. We find high opportunities for watershed activities to mitigate at least one of the risks in 42 cities, potentially benefiting 96 million people or around 60% of the urbanites living in the 70 largest cities in Latin America. We estimate water quality could be improved for 72 million people in 27 cities, riverine flood risk mitigated for 5 million people in 13 cities, and stormwater flooding mitigated for 44 million people in 14 cities. We identified five cities with the potential to simultaneously enhance water quality and mitigate flood risks, and in contrast, six cities where conservation efforts are unlikely to meaningfully mitigate either risk. Institutions investing in natural infrastructure to improve water security in Latin America can maximize their impact by focusing on specific watershed conservation activities either for cleaner drinking water or flood mitigation in cities identified in our analysis where these interventions are most likely to reduce risk.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Emerging parametric insurance products targeted at regional governments consider an index of flooding as the instrument for payoff and rate setting. Inundation extent from satellite remote sensing ...may provide a more direct measure of flood risk in this context than hydraulic modeling of flow and inundation. Here, we examine satellite‐based fractional inundated area as a proxy for flood impact that can be used for index insurance payment at a regional scale. Typical methods for estimating return periods from unbounded distributions such as the Generalized Extreme Value distribution are not appropriate for fractional flooded area, which is bounded by 0 and 1. Here we examine alternative bounded distributions (2 parameter and a 4 parameter Beta) to estimate return periods and quantify uncertainty using a bootstrap sampling procedure for the short duration satellite record of fractional flooded area. We consider two examples with distinct flood dynamics (a) a country (Bangladesh) where a flood can cover the majority of the land surface, and (b) a river basin (the Rio Salado basin in Argentina) where the worst flood covered only a modest fraction of the watershed. We explore how a parametric insurance policy based on fractional flooded area could be priced based on a typical approach used in the industry, that accounts for uncertainty for small sample estimation. Our exploratory approach to model selection illustrates how estimating the uncertainty price influences insurance contract pricing and is important to consider the choice of distribution beyond just the traditional measures of goodness of fit.
Plain Language Summary
Index insurance, catastrophe bonds, and other types of risk transfer instruments could play an important role in adapting to floods and ensuring sustainable development in a world of increasing flood risk. In this article, we examine how satellite time series of inundation can be used to develop an emerging type of flood insurance, known as parametric or index‐based insurance. Unlike traditional indemnity insurance, which relies on adjusters to estimate loss for individual damage, index insurance uses data ex‐ante to determine payout contracts when pre‐specified thresholds are crossed. Inundation extent from satellite remote sensing may provide a more direct measure of flood risk than data from models or stream gauges. However, typical methods used to estimate return periods for floods from models and gauges are not appropriate for fractional inundated area measurements from satellites. Here we provide a more appropriate method to estimate return periods and quantify uncertainty to price an insurance product leveraging the relatively short satellite record. Example applications for Bangladesh and Rio Salado, Argentina are provided. We show why estimating and pricing uncertainty ultimately influences insurance contract pricing and can help governments select insurance policies that align with their flood adaptation strategy.
Key Points
Estimating return periods for fractional inundated area with the oft‐used Generalized Extreme Value distribution is inappropriate
Bounded distributions (e.g., Beta) reduce uncertainty estimates for probability of exceedance from short duration inundation time series
Example design and price of parametric flood insurance with fractional inundated area in Bangladesh and Argentina accounting for uncertainty
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
On frontiers dominated by illicit activities such as narcotrafficking, criminal organizations’ usurpation of land and resources is profoundly changing rural livelihoods and prospects for biodiversity ...conservation. Prior work has demonstrated how drug trafficking catalyzes forest loss and smallholder dispossession but does not make clear the extent to which the long-term control of land is moved from state, Indigenous, or smallholders to criminal or other actors. This study attempts to describe those shifts. Specifically: we develop a typology of land control, and use it to track how drug trafficking initiates shifts from public lands and Indigenous territories to private large holdings. We examine an array of secondary sources indicating shifts in land control related to narcotrafficking, including illegal land seizure documents, news media, and surveys of land managers. In absence of formal land registries, frontier actors may signal their control over land through land use change. After establishing where changes in land control have taken place, we analyzed land use and resulting changes in spatial patterns of forest loss. We found that large scale sustained forest losses (over 713,244 ha and 417,329 ha), in Guatemala and Honduras, respectively, from 2000–2019) corresponds with areas undergoing shifts in control towards large landowners, often related to narcotrafficking. Incomplete empirical data on land control prevent comprehensive attribution of all sustained forest loss related to narcotrafficking. Yet the limited evidence gathered here indicates drug trafficking activities initiate widespread and sustained shifts and consolidation of who controls land and resources at the frontier. Our work suggests that in Central America and likely elsewhere, control over land—quite separate from property rights—is the key factor in understanding social and ecological change.
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