Alex de Sherbinin
Columbia University
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Featured researches published by Alex de Sherbinin.
Climatic Change | 2014
Alex de Sherbinin
In the past 5 years there has been a proliferation of efforts to map climate change “hotspots” — regions that are particularly vulnerable to current or future climate impacts, and where human security may be at risk. While some are academic exercises, many are produced with the goal of drawing policy maker attention to regions that are particularly susceptible to climate impacts, either to mitigate the risk of humanitarian crises or conflicts or to target adaptation assistance. Hotspots mapping efforts address a range of issues and sectors such as vulnerable populations, humanitarian crises, conflict, agriculture and food security, and water resources. This paper offers a timely assessment of the strengths and weaknesses of current hotspots mapping approaches with the goal of improving future efforts. It also highlights regions that are anticipated, based on combinations of high exposure, high sensitivity and low adaptive capacity, to suffer significant impacts from climate change.
Bulletin of The Atomic Scientists | 2009
Charles J. Vörösmarty; James P. M. Syvitski; John W. Day; Alex de Sherbinin; Liviu Giosan; Chris Paola
The fragility of the world’s deltas is not solely a consequence of rising ocean waters. Human fresh water use is a predominant force behind receding coastlines.
Oryx | 2008
Alex de Sherbinin
The relationship between conservation and poverty has received extensive attention recently, and the impacts of protected areas on the welfare of communities surrounding them has been debated. I seek to contribute to this debate by using a unique sub-national database of infant mortality rates for an analysis of such mortality surrounding protected areas in developing countries. The paper tests the hypotheses that poverty rates in regions surrounding protected areas in developing countries are higher than national averages and that poverty rates are highest around large and strictly protected areas. Preliminary evidence suggests that infant mortality rates surrounding protected areas, and even those surrounding the most strictly protected areas, are not very different from national rates. Infant mortality rates are significantly higher among populations surrounding larger protected areas but the causal relationship is uncertain. Data limitations and other problems related to this kind of global analysis are discussed. Information of the kind presented in this paper can assist management authorities to assess the relative poverty surrounding protected areas in their countries so as to set priorities for poverty alleviation interventions, and may serve as a useful sampling frame for local case studies and long-term monitoring.
Environmental Research Letters | 2014
Alex de Sherbinin; Marc A. Levy; Erica Zell; Stephanie Weber; Malanding S. Jaiteh
Environmental indicators are increasingly being used in policy and management contexts, yet serious data deficiencies exist for many parameters of interest to environmental decision making. With its global synoptic coverage and the wide range of instruments available, satellite remote sensing has the potential to fill a number of these gaps, yet their potential contribution to indicator development has largely remained untested. In this paper we present results of a pilot effort to develop satellite-derived indicators in three major issue areas: ambient air pollution, coastal eutrophication, and biomass burning. A primary focus is on the vetting of indicators by an advisory group composed of remote sensing scientists and policy makers. S Online supplementary data available from stacks.iop.org/ERL/9/084013/mmedia
Oryx | 2008
Kent H. Redford; Marc A. Levy; Eric W. Sanderson; Alex de Sherbinin
In this paper we provide an empirically-based way to address the general question of the broad-scale spatial relationship between poverty occurrence and areas of interest to those seeking conservation of large wild areas. We address the question of the spatial relationship between poor people and areas less impacted by human activity by asking three questions about the global spatial relationship between poor people and ecological intactness and how it varies by major biome and geographical region. We use infant mortality rate as a proxy for poverty and the Human Footprint as a proxy for ecological intactness, comparing global terrestrial maps of both. The analysis shows that the vast majority of the worlds poor people live in extremely urban and very transformed (peri-transformed) areas. Only a small percentage of the worlds most poor are found in areas that are somewhat or extremely wild: about 0.25% of the worlds population. This fact has implications for the calls being made for conservation organizations to under- take poverty alleviation, suggesting that at a global scale those groups with interest in conserving wild areas would be able to contribute little to globally significant poverty alleviation efforts. However, these conservation groups are well positioned to develop new partnerships for delivery of benefits to some of the least accessible poor people in the wildest places of the world.
Environmental Research Letters | 2012
Alex de Sherbinin; Marc A. Levy; Susana B. Adamo; Kytt MacManus; Gregory G. Yetman; Valentina Mara; Liana Razafindrazay; Benjamin K. Goodrich; Tanja Srebotnjak; Cody Aichele; Linda I. Pistolesi
The potential for altered ecosystems and extreme weather events in the context of climate change has raised questions concerning the role that migration plays in either increasing or reducing risks to society. Using modeled data on net migration over three decades from 1970 to 2000, we identify sensitive ecosystems and regions at high risk of climate hazards that have seen high levels of net in-migration and out-migration over the time period. This paper provides a literature review on migration related to ecosystems, briefly describes the methodology used to develop the estimates of net migration, then uses those data to describe the patterns of net migration for various ecosystems and high risk regions. The study finds that negative net migration generally occurs over large areas, reflecting its largely rural character, whereas areas of positive net migration are typically smaller, reflecting its largely urban character. The countries with largest population such as China and India tend to drive global results for all the ecosystems found in those countries. Results suggest that from 1970 to 2000, migrants in developing countries have tended to move out of marginal dryland and mountain ecosystems and out of drought-prone areas, and have moved towards coastal ecosystems and areas that are prone to floods and cyclones. For North America results are reversed for dryland and mountain ecosystems, which saw large net influxes of population in the period of record. Uncertainties and potential sources of error in these estimates are addressed.
Data Science Journal | 2006
Andrew Nelson; Alex de Sherbinin; Francesca Pozzi
There is clear demand for a global spatial public domain roads data set with improved geographic and temporal coverage, consistent coding of road types, and clear documentation of sources. The currently best available global public domain product covers only one-quarter to one-third of the existing road networks, and this varies considerably by region. Applications for such a data set span multiple sectors and would be particularly valuable for the international economic development, disaster relief, and biodiversity conservation communities, not to mention national and regional agencies and organizations around the world. The building blocks for such a global product are available for many countries and regions, yet thus far there has been neither strategy nor leadership for developing it. This paper evaluates the best available public domain and commercial data sets, assesses the gaps in global coverage, and proposes a number of strategies for filling them. It also identifies stakeholder organizations with an interest in such a data set that might either provide leadership or funding for its development. It closes with a proposed set of actions to begin the process.
ISPRS international journal of geo-information | 2015
Alex de Sherbinin; Tricia K. Chai-Onn; Malanding S. Jaiteh; Valentina Mara; Linda I. Pistolesi; Emilie L. Schnarr; Sylwia Trzaska
Vulnerability mapping reveals areas that are likely to be at greater risk of climate-related disasters in the future. Through integration of climate, biophysical, and socioeconomic data in an overall vulnerability framework, so-called “hotspots” of vulnerability can be identified. These maps can be used as an aid to targeting adaptation and disaster risk management interventions. This paper reviews vulnerability mapping efforts in West Africa conducted under the USAID-funded African and Latin American Resilience to Climate Change (ARCC) project. The focus is on the integration of remotely sensed and socioeconomic data. Data inputs included a range of sensor data (e.g., MODIS NDVI, Landsat, SRTM elevation, DMSP-OLS night-time lights) as well as high-resolution poverty, conflict, and infrastructure data. Two basic methods were used, one in which each layer was transformed into standardized indicators in an additive approach, and another in which remote sensing data were used to contextualize the results of composite indicators. We assess the benefits and challenges of data integration, and the lessons learned from these mapping exercises.
Annals of the New York Academy of Sciences | 2015
William Solecki; Cynthia Rosenzweig; Reginald Blake; Alex de Sherbinin; Tom Matte; Fred Moshary; Bernice Rosenzweig; Mark Arend; Stuart R. Gaffin; Elie Bou-Zeid; Keith Rule; Geraldine Sweeny; Wendy Dessy
William Solecki,1,a Cynthia Rosenzweig,2,a Reginald Blake,3,a Alex de Sherbinin,4 Tom Matte,5 Fred Moshary,6 Bernice Rosenzweig,7 Mark Arend,6 Stuart Gaffin,8 Elie Bou-Zeid,9 Keith Rule,10 Geraldine Sweeny,11 and Wendy Dessy11 1City University of New York, CUNY Institute for Sustainable Cities, New York, NY. 2Climate Impacts Group, NASA Goddard Institute for Space Studies, Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 3Physics Department, New York City College of Technology, CUNY, Brooklyn, NY; Climate Impacts Group, NASA Goddard Institute for Space Studies. 4 Center for International Earth Science Information Network (CIESIN), Columbia University, Palisades, NY. 5New York City Department of Health and Mental Hygiene, New York, NY. 6NOAA CREST, City College of New York, CUNY, New York, NY. 7CUNY Environmental Crossroads, City College of New York, CUNY, New York, NY. 8Center for Climate Systems Research, Columbia University Earth Institute, New York, NY. 9Department of Civil & Environmental Engineering, Princeton University, Princeton, NJ. 10Princeton Plasma Physics Laboratory, Princeton, NJ. 11New York City Mayor’s Office of Operation, New York, NY
Data Science Journal | 2014
Taro Ubukawa; Alex de Sherbinin; Harlan J. Onsrud; Andrew Nelson; Karen Payne; Olivier Cottray; Mikel Maron
There is a clear need for a public domain data set of road networks with high special accuracy and global coverage for a range of applications. The Global Roads Open Access Data Set (gROADS), version 1, is a first step in that direction. gROADS relies on data from a wide range of sources and was developed using a range of methods. Traditionally, map development was highly centralized and controlled by government agencies due to the high cost or required expertise and technology. In the past decade, however, high resolution satellite imagery and global positioning system (GPS) technologies have come into wide use, and there has been significant innovation in web services, such that a number of new methods to develop geospatial information have emerged, including automated and semi-automated road extraction from satellite/aerial imagery and crowdsourcing. In this paper we review the data sources, methods, and pros and cons of a range of road data development methods: heads-up digitizing, automated/semi-automated extraction from remote sensing imagery, GPS technology, crowdsourcing, and compiling existing data sets. We also consider the implications for each method in the production of open data.