High Spatial, Temporal, and Spectral Resolution Instruments for Modeling Monitoring Urban Areas
No abstract available
spatial resolution↗
Engineering topics
Quattrochi, Dale
Publications and source records attributed to Quattrochi, Dale.
Impacts of Extreme Events on Human Health
Increased Exposure to Extreme Events Key Finding 1: Health impacts associated with climate-related changes in exposure to extreme events include death, injury, or illness; exacerbation of underlying medical conditions; and adverse effects on mental health[High Confidence]. Climate change will increase exposure risk in some regions of the United States due to projected increases in the frequency and/or intensity of drought, wildfires, and flooding related to extreme precipitation and hurricanes [Medium Confidence].Disruption of Essential Infrastructure Key Finding 2: Many types of extreme events related to climate change cause disruption of infrastructure, including power, water, transportation, and communication systems, that are essential to maintaining access to health care and emergency response services and safeguarding human health [High Confidence].Vulnerability to Coastal Flooding Key Finding 3: Coastal populations with greater vulnerability to health impacts from coastal flooding include persons with disabilities or other access and functional needs, certain populations of color, older adults, pregnant women and children, low-income populations, and some occupational groups [High Confidence].Climate change will increase exposure risk to coastal flooding due to increases in extreme precipitation and in hurricane intensity and rainfall rates, as well as sea level rise and the resulting increases in storm surge.
floods↗
Modeled Forecasts of Dengue Fever in San Juan, PR Using NASA Satellite Enhanced Weather Forecasts
Dengue virus is transmitted between humans and mosquitoes of the genus Aedes and causes approximately 96 million cases of disease (dengue fever) each year (Bhatet al. 2013). Symptoms of dengue fever include fever, headache, nausea, vomiting, and eye, muscle and joint pain (CDC). More sever manifestations such as abdominal pain, bleeding from nose and gums, vomiting of blood, and clammy skin occur in rare cases of dengue hemorrhagic fever (CDC). Dengue fever occurs throughout tropical and sub-tropical regions worldwide, however, the geographical range and size of epidemics is increasing. Weather and climate are drivers of dengue virus transmission dynamics (Morin et al. 2013) by affecting mosquito proliferation and the virus extrinsic incubation period (i.e. required time for the virus to replicate and disseminate within the mosquito before it can retransmit the virus).
vector↗
Health and Environment Linked for Information Exchange in Atlanta (HELIX-Atlanta)
No abstract available
Environmental↗
Environmental Public Health Applications Using Remotely Sensed Data
No abstract available
Public Health↗
Relationships Between Excessive Heat and Daily Mortality over the Coterminous United States
No abstract available
heat↗
Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model
Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.
Morin, Cory↗
Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model
Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground‐based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010‐2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.
Morin, Cory↗
NASA 2014 The Hyperspectral Infrared Imager (HyspIRI) - Science Impact of Deploying Instruments on Separate Platforms
The Hyperspectral Infrared Imager (HyspIRI) mission was recommended for implementation by the 2007 report from the U.S. National Research Council Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, also known as the Earth Science Decadal Survey. The HyspIRI mission is science driven and will address a set of science questions identified by the Decadal Survey and broader science community. The mission includes a visible shortwave infrared (VSWIR) imaging spectrometer, a multispectral thermal infrared (TIR) imager and an intelligent payload module (IPM). The IPM enables on-board processing and direct broadcast for those applications with short latency requirements. The science questions are organized as VSWIR-only, TIR-only and Combined science questions, the latter requiring data from both instruments. In order to prepare for the mission NASA is undertaking pre-phase A studies to determine the optimum mission implementation, in particular, cost and risk reduction activities. Each year the HyspIRI project is provided with feedback from NASA Headquarters on the pre-phase A activities in the form of a guidance letter which outlines the work that should be undertaken the subsequent year. The 2013 guidance letter included a recommendation to undertake a study to determine the science impact of deploying the instruments from separate spacecraft in sun synchronous orbits with various time separations and deploying both instruments on the International Space Station (ISS). This report summarizes the results from that study. The approach taken was to evaluate the impact on the combined science questions of time separations between the VSWIR and TIR data of <3 minutes, <1 week and a few months as well as deploying both instruments on the ISS. Note the impact was only evaluated for the combined science questions which require data from both instruments (VSWIR and TIR). The study concluded the impact of a separation of <3 minutes was minimal, e.g. if the instruments were on separate platforms that followed each other in a train. The impact of a separation of <1 week was strongly dependent on the question that was being addressed with no impact for some questions and a severe impact for others. The impact of a time separation of several months was severe and in many cases it was no longer possible to answer the sub-question. The impact of deploying the instruments on the ISS which is in a precessive (non-sun synchronous) orbit was also very question dependent, in some cases it was possible to go beyond the original question, e.g. to examine the impact of the diurnal cycle, whereas in other cases the question could not be addressed for example if the question required observations from the polar regions. As part of the study, the participants were asked to estimate, as a percentage, how completely a given sub-question could be answered with 100% indicating the question could be completely answered. These estimations should be treated with caution but nonetheless can be useful in assessing the impact. Averaging the estimates for each of the combined questions the results indicate that 97% of the questions could be answered with a separation of < 3 minutes. With a separation of < 1 week, 67% of the questions could be answered and with a separation of several months only 21% of the questions could be answered.
Turpie, Kevin↗
NASA 2014 The Hyperspectral Infrared Imager (HyspIRI) – science impact of deploying instruments on separate platforms
The Hyperspectral Infrared Imager (HyspIRI) mission was recommended for implementation by the 2007 report from the U.S. National Research Council Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, also known as the Earth Science Decadal Survey. The HyspIRI mission is science driven and will address a set of science questions identified by the Decadal Survey and broader science community. The mission includes a visible shortwave infrared (VSWIR) imaging spectrometer, a multispectral thermal infrared (TIR) imager and an intelligent payload module (IPM). The IPM enables on-board processing and direct broadcast for those applications with short latency requirements. The science questions are organized as VSWIR-only, TIR-only and Combined science questions, the latter requiring data from both instruments.
Quattrochi, Dale↗
Downscaling MODIS Land Surface Temperature for Urban Public Health Applications
This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.
Al-Hamdan, Mohammad↗
Downscaling MODIS Land Surface Temperature for Urban Public Health Applications
This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.
Al-Hamdan, Mohammad↗
How Cities Breathe: Ground-Referenced, Airborne Hyperspectral Imaging Precursor Measurements To Space-Based Monitoring
Methane's (CH4) large global warming potential (Shindell et al., 2012) and likely increasing future emissions due to global warming feedbacks emphasize its importance to anthropogenic greenhouse warming (IPCC, 2007). Furthermore, CH4 regulation has far greater near-term climate change mitigation potential versus carbon dioxide CO2, the other major anthropogenic Greenhouse Gas (GHG) (Shindell et al., 2009). Uncertainties in CH4 budgets arise from the poor state of knowledge of CH4 sources - in part from a lack of sufficiently accurate assessments of the temporal and spatial emissions and controlling factors of highly variable anthropogenic and natural CH4 surface fluxes (IPCC, 2007) and the lack of global-scale (satellite) data at sufficiently high spatial resolution to resolve sources. Many important methane (and other trace gases) sources arise from urban and mega-urban landscapes where anthropogenic activities are centered - most of humanity lives in urban areas. Studying these complex landscape tapestries is challenged by a wide and varied range of activities at small spatial scale, and difficulty in obtaining up-to-date landuse data in the developed world - a key desire of policy makers towards development of effective regulations. In the developing world, challenges are multiplied with additional political access challenges. As high spatial resolution satellite and airborne data has become available, activity mapping applications have blossomed - i.e., Google maps; however, tap a minute fraction of remote sensing capabilities due to limited (three band) spectral information. Next generation approaches that incorporate high spatial resolution hyperspectral and ultraspectral data will allow detangling of the highly heterogeneous usage megacity patterns by providing diagnostic identification of chemical composition from solids (refs) to gases (refs). To properly enable these next generation technologies for megacity include atmospheric radiative transfer modeling the complex and often aerosol laden, humid, urban microclimates, atmospheric transport and profile monitoring, spatial resolution, temporal cycles (diurnal and seasonal which involve interactions with the surrounding environment diurnal and seasonal cycles) and representative measurement approaches given traffic realities. Promising approaches incorporate contemporaneous airborne remote sensing and in situ measurements, nocturnal surface surveys, with ground station measurement
Leifer, Ira↗
Geocarto International-Special Issue on NASA Earth Science Satellite Data for Applications to Public Health
No abstract available
Quattrochi, Dale↗
Public Health Applications of Remotely-sensed Environmental Datasets for the Conterminous United States
NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics to address issues of environmental health and enhance public health decision-making using NASA remotely-sensed data and products. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid using the US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Incoming Solar Radiation (Insolation) and heat-related products using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets were linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental datasets and the results of the public health linkage analyses will be disseminated to end-users for decision-making through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer-reviewed publications respectively. The linkage of these data with the CDC WONDER system substantially expands public access to NASA data, making their use by a wide range of decision makers feasible. By successful completion of this research, decision-making activities, including policy-making and clinical decision-making, can be positively affected through utilization of the data products and analyses provided on the CDC WONDER system.
Al-Hamdan, Mohammad↗