A5091209998- Flood Risk Assessment and Management
- Disaster Management and Resilience
- Radioactive contamination and transfer
- Climate Change, Adaptation, Migration
- Geographic Information Systems Studies
- Radiation Detection and Scintillator Technologies
- Human Mobility and Location-Based Analysis
- Climate Change and Health Impacts
- Species Distribution and Climate Change
- Data-Driven Disease Surveillance
- Air Quality and Health Impacts
- Atmospheric and Environmental Gas Dynamics
- Agriculture, Land Use, Rural Development
- COVID-19 impact on air quality
- Fire effects on ecosystems
- Complex Systems and Decision Making
- Agricultural risk and resilience
- Tropical and Extratropical Cyclones Research
- Scientific Computing and Data Management
- Air Quality Monitoring and Forecasting
- Research Data Management Practices
- Remote Sensing and Land Use
- Geochemistry and Geologic Mapping
- Urban Transport and Accessibility
- Remote-Sensing Image Classification
University of Canterbury
2022-2025
Columbia University
2020-2024
Pennsylvania State University
2015-2022
Earth Island Institute
2020-2022
Lamont-Doherty Earth Observatory
2021
University of North Carolina at Charlotte
2014
Citizen science is an important vehicle for democratizing and promoting the goal of universal equitable access to scientific data information. Data generated by citizen groups have become increasingly source scientists, applied users those pursuing 2030 Agenda Sustainable Development. are used extensively in studies biodiversity pollution; crowdsourced being UN operational agencies humanitarian activities; scientists providing relevant monitoring sustainable development goals (SDGs). This...
AbstractRemote sensing has been widely adopted to map post-fire burn severity over large forested areas. Statistical regression based on linear or simple non-linear assumptions is typically used link forest reflectance with the degree of severity. However, this linkage becomes complicated if forests experienced severe mortality caused by pre-fire disease insect outbreaks, which likely occur more frequently as a result rapid climate change. In an effort improve understanding relationship...
The first goal of this study is to quantify the magnitude and spatial variability air quality changes in USA during COVID-19 pandemic. We focus on two pollutants that are federally regulated, nitrogen dioxide (NO
Social vulnerability is a key component of the risk equation alongside context hazard and exposure. Increasingly, social indices are used to better understand predict consequences disasters, support development improved disaster management policies. Humanitarian organisations particularly strive capture in their decision processes relative prioritisation actions before disasters occur. This research supports Ecuadorian Red Cross generating flood-specific index inform flash flood early action...
Nutrition, food systems, and the biodiversity of agriculture (agrobiodiversity) are rapidly changing among indigenous smallholders in Andean countries, across Latin America, globally. Urgent calls for sovereignty recognize global transformations nutrition, agriculture, climate change amid geographically uneven development vulnerability to these shocks that recently include coronavirus/Covid-19 pandemic. Collaborating with a praxis-oriented institution focused on social nutrition public...
<title>Abstract</title> Globally, populations are increasingly located in areas at high risk of frequent, extreme weather events. Some exposed have the ability to move safer places; others unable get out harm’s way. The climate risks facing these involuntary immobile not often addressed by local and national authorities, despite increasing recognition international development agencies humanitarian actors. Here we discuss when how events lead immobility considering influence political,...
Achieving the seventeen United Nations Sustainable Development Goals (SDGs) requires accurate, consistent, and accessible population data. Yet many low- middle-income countries lack reliable or recent census data at sufficiently fine spatial scales needed to monitor SDG progress. While increasing abundance of Earth observation-derived gridded products provides analysis-ready estimates, end users clear use criteria track SDGs indicators. In fact, comparisons identify wide variation across...
The analysis of historical disaster events is a critical step towards understanding current risk levels and changes in over time. Disaster databases are potentially useful tools for exploring trends, however, criteria inclusion associated descriptive characteristics not standardized. For example, some include only primary types, such as ‘flood’, while others subtypes, ‘coastal flood’ ‘flash flood’. Here we outline method to identify candidate assignment specific subtype—namely, floods’—from...
Hurricane Sandy made landfall in one of the most populated areas United States, and affected almost 8 million people. The event provides a unique opportunity to study power outages because data available large impact densely area. Satellite nightlight imagery "before" "after" hurricane is used quantify light dimming caused by outages. Geolocated tweets filtered keywords provide valuable information on human activity at high temporal spatial resolution during event. Analysis brightness change...
Crowdsourced environmental data have the potential to augment traditional sources during disasters. Traditional sensor networks, satellite remote sensing imagery, and models are all faced with limitations in observational inputs, forecasts, resolution. This study integrates flood depth derived from crowdsourced images U.S. Geological Survey (USGS) ground-based observation a product, model Hurricane Florence. The compared using cross-sections assess areas impacted by Automated methods can be...
Abstract Particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) increases mortality and morbidity.1,2 PM2.5 is composed of a mixture chemical components that vary across space time.3 Due to limited hyperlocal data availability, known about health risks components, their US-wide exposure disparities, or which species are driving the biggest intra-urban changes in mass. Here, we developed first national super-learned models US for estimation annual mean elemental carbon (EC),...
This article introduces an experimental methodology to identify proxy indicators that are conceptually consistent with the processes of Climate Gentrification ("CG"), in which a change demand preferences among consumers and investors drives increased consumption for real estate, part, on lower measures physical risk from climate change. Evaluated through case studies state Florida, this builds integration multiple datasets concerning rental properties, evictions, socioeconomic data, as well...
This study explores the relationship between wildfire exposure, social vulnerability, and community resilience across 26 states east of Mississippi River. work centers around one research question: are there spatial differences in exposure that disproportionately impact disadvantaged communities Eastern United States over recent period (2000–2020)? Employing remotely sensed data ancillary datasets, we analyze map extensive compare it with metrics vulnerability to examine burdens U.S. A...
Assessing the impact of climate change on vulnerable populations and implications such impacts is a critical step toward environmental justice. In general, indices or metrics that aim at studying linkages between climatic lack housing information. Financially relevant real estate data (e.g., mortgages, evictions) alongside other socioeconomic physical risk information can, however, provide crucial lens to assess addition, standard demographic variables aggregated census units granularity...
Data relevant to flood vulnerability is minimal and infrequently collected, if at all, for much of the world. This makes it difficult highlight areas humanitarian aid, monitor changes, support communities in need. It time consuming resource intensive do an exhaustive study multiple variables using a field survey. We use mixed methods approach develop survey on interest utilize open-source crowdsourcing technique remotely collect data with human-machine interface high-resolution satellite...
Data are vital for and creating knowledge-based solutions to development challenges facing Africa. As a result of gaps in government-funded data collection, the interest promoting community engagement, there is global movement towards consideration nontraditional sources data, including citizen science (CS) data. These particularly valuable when collected at high resolution over large spatial extents long time periods. CS projects infrastructure abundant well documented Global North, while...
Abstract Particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) is a multi-million human silent killer worldwide and contains numerous trace elements (TEs). Understanding TEs relative toxicity largely limited by lack of data. Here, we used ensembles machine learning models to generate ~163 billion predictions estimating annual means ten TEs, namely bromine, calcium, copper, iron, potassium, nickel, lead, silicon, vanadium, zinc across 3,535 contiguous US urban areas at 50-m...
Agrobiodiversity—the biodiversity of food, agriculture, and land use—is essential to U.N. Sustainable Development Goal 2 by providing crucial food nutritional quality diets combined with strengthening agroecological sustainability. Focusing on the agrobiodiversity nexus SDG 2, current study utilized interdisciplinary Agrobiodiversity Knowledge Framework (AKF), household-level surveys, sampling crop fields home gardens in a case Huánuco, Peru, 2017. Statistical measures estimated ( n = 268...