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NASA NTRS1990

Chronological evaluation of urban growth and area expansion in Aguascalientes, Mexico using remotely sensed and ancillary mapped data

The study describes some efforts to assist the mapping procedure of Mexican towns and cities by focusing on the analysis of urban changes that have occurred in the city of Aguascalientes. To evaluate urban growth trends in Aguascalientes, historic maps of land cover, aerial photography, and SPOT data were reviewed between the period of 1857 and 1988 to determine urban boundaries. Additional analyses focused on identifying the extent and pattern of growth in reference to urban development plans initiated in 1978, and on assessing the impact of relocating people and industry after the Mexico City earthquake. Results from the study indicate a steady growth in areal expansion and population in the Aguascalientes area between 1978 and 1988.

Falquier, Leticia G.↗

NASA NTRS2000

A Decision Support Information System for Urban Landscape Management Using Thermal Infrared Data

In this paper, we describe efforts to use remote sensing data within the purview of an information support system, to assess urban thermal landscape characteristics as a means for developing more robust models of the Urban Heat Island (UHI) effect. We also present a rationale on how we have successfully translated the results from the study of urban thermal heating and cooling regimes as identified from remote sensing data, to decision-makers, planners, government officials, and the public at large in several US cities to facilitate better understanding of how the UHI affects air quality. Additionally, through the assessment of the spatial distribution of urban thermal landscape characteristics using remote sensing data, it is possible to develop strategies to mitigate the UHI that hopefully will in turn, drive down ozone levels and improve overall urban air quality. Four US cities have been the foci for intensive analysis as part of our studies: Atlanta, GA, Baton Rouge, LA, Salt Lake City, UT, and Sacramento, CA. The remote sensing data for each of these cities has been used to generate a number of products for use by "stakeholder" working groups to convey information on what the effects are of the UHI and what measures can be taken to mitigate it. In turn, these data products are used to both educate and inform policy-makers, planners, and the general public about what kinds of UHI mitigation strategies are available.

Quattrochi, Dale A.↗

NASA NTRS2012

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown.

Shen, Suhung↗

NASA NTRS2004

Analysis of Upper Air, Ground and Remote Sensing Data For the ATLAS Field Campaign in San Juan, Puerto Rico

The Atlas San Juan Mission was conducted in February 2004 with the main objectives of observing the Urban Heat Island of San Juan, providing high resolution data of the land use for El Yunque Rain Forest and for calibrating remote sensors. The mission was coordinated with NASA staff members at Marshall, Stennis, Goddard, and Glenn. The Airborne Thermal and Land Applications Sensor (ATLAS) from NASA/Stennis, that operates in the visual and IR bands, was used as the main sensor and was flown over Puerto Rico in a Lear 23 jet plane. To support the data gathering effort by the ATLAS sensor, remote sensing observations and upper air soundings were conducted along with the deployment of a number of ground based weather stations and temperature sensors. This presentation focuses in the analysis of this complementary data for the Atlas San Juan Mission. Upper air data show that during the days of the mission the Caribbean mid and high atmospheres were relatively dry and highly stable reflecting positive surface lifted index, a necessary condition to conduct this suborbital campaign. Surface wind patterns at levels below 850mb were dominated by the easterly trades, while the jet stream at the edge of the troposphere dominated the westerly wind at levels above 500mb. The jet stream remained at high latitudes reducing the possibility of fronts. In consequence, only 8.4 mm of precipitation were reported during the entire mission. Observation of soundings located about 150 km apart reflected minimum variations of the boundary layer across the island for levels below 850 meters and a uniform atmosphere for higher levels. The weather stations and the temperature sensors were placed at strategic locations to observe variations across the urban and rural landscapes. Time series plot of the stations' data show that heavily urbanized commercial areas have higher air temperatures than urban and suburban residential areas, and much higher temperatures than rural areas. Temperature differences [dT(U-R)] were obtained by subtracting the values of several stations from a reference urban station, located in the commercial area of San Juan. These time series show that the UHI peaks during the morning between 10:00am and noon to an average of 4.5 C, a temporal pattern not previously observed in similar studies for continental cities. It is also observed a high variability of the UHI with the precipitation patterns even for short events. These results may be a reflection of a large land use density by low level buildings with an apparent absence of significant heat storage effects in the urban areas, and the importance of the surrounding soil and vegetation moisture in controlling the urban tropical climate. The ATLAS data was used to determine albedo and surface temperature patterns on a 10m scale for the study area. These data were used to calibrate the spatial distribution of the surface temperature when using remote sensing images from MODIS (Moderate Resolution Imaging Spectroradiometer). Surface temperatures were estimated using the land surface temperature product MOD11_L2 distributed by the Land Process Distributed Active Archive Center (LP DAAC). These results show the maximum, minimum and average temperatures in San Juan and in the entire Island at a resolution of 1 km. The information retrieved from MODIS for land surface temperatures reflected similar temporal and spatial variations as the weather stations and ATLAS measurements with a highest absolute offset of about 5 C due to the differences between surface and air temperatures.

Gonzalez, J. E.↗

NASA NTRS2005

Analysis of Upper Air, Ground and Remote Sensing Data for the ATLAS Field Campaign in San Juan, Puerto Rico

The Atlas San Juan Mission was conducted in February 2004 with the main objectives of observing the Urban Heat Island of San Juan, providing high resolution data of the land use for El Yunque Rain Forest and for calibrating remote sensors. The mission was coordinated with NASA staff members at Marsha& Stennis, Goddard, and Glenn. The Airborne Thermal and Land Applications Sensor (ATLAS) from NASA/Stennis, that operates in the visual and IR bands, was used as the main sensor and was flown over Puerto Rico in a Lear 23 jet plane. To support the data gathering effort by the ATLAS sensor, remote sensing observations and upper air soundings were conducted along with the deployment of a number of ground based weather stations and temperature sensors. This presentation focuses in the analysis of this complementary data for the Atlas San Juan Mission. Upper air data show that during the days of the mission the Caribbean mid and high atmospheres were relatively dry and highly stable reflecting positive surface lifted index, a necessary condition to conduct this suborbital campaign. Surface wind patterns at levels below 850mb were dominated by the easterly trades, while the jet stream at the edge of the troposphere dominated the westerly wind at levels above 500mb. The jet stream remained at high latitudes reducing the possibility of fronts. In consequence, only 8.4 mm of precipitation were reported during the entire mission. Observation of soundings located about 150 km apart reflected minimum variations of the boundary layer across the Island for levels below 850 meters and a uniform atmosphere for higher levels. The weather stations and the temperature sensors were placed at strategic locations to observe variations across the urban and rural landscapes. Time series plot of the stations' data show that heavily urbanized commercial areas have higher air temperatures than urban and suburban residential areas, and much higher temperatures than rural areas. Temperature differences [dT(U-R)] were obtained by subtracting the values of several stations h m a reference urban station, located m the commercial area of San Juan. These time series show that the UHI peaks during the morning between 10:00am and noon to an average of 4.5 C, a temporal pattern not previously observed in similar studies for continental cities. It is also observed a high variability of the UHI with the precipitation patterns even for short events. These results may be a reflection of a large land use density by low level buildings with an apparent absence of significant heat storage effects in the urban areas, and the importance of the surrounding soil and vegetation moisture in controlling the urban tropical climate. The ATLAS data was used to determine albedo and surface temperature patterns on a 10m scale for the study area. These data were used to calibrate the spatial distribution of the surface temperature when using remote sensing images from MODIS (Moderate Resolution Imaging Spectradiometer). Surface temperatures were estimated using the land surface temperature product MODII-L2 distributed by the Land Process Distributed Active Archive Center(LP DAAC). These results show the maximum, minimum and average temperatures in San Juan and in the entire Island at a resolution of 1 km. The information retrieved from MODIS for land surface temperatures reflected similar temporal and spatial variations as the weather stations and ATLAS measurements with a highest absolute offset of about 5 C due to the differences between surface and air temperatures.

Gonzalez, Jorge E.↗

NASA NTRS1998

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

Source record↗

NASA NTRS2006

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Quattrochi, Dale A.↗

NASA NTRS2000

The Urban Fabric of the City as Its Affects Thermal Energy Responses Derived from Remote Sensing Data

The physical geography of the city affects numerous aspects of its interlinked biophysical, social, and land-atmosphere characteristics - those attributes that come together to form the total urban environment. One approach to studying the multitude of interactions that occur as a result of urbanization is to view the city from a systems ecology perspective, where energy and material cycle into and out of the urban milieu. Thus, the urban ecosystem is synergistic in linking land, air, water, and living organisms in a vast network of interrelated physical, human, and biological process. Given the number and the shear complexity of the exchanges and, ultimately, their effects, that occur within the urban environment, we are focusing our research on looking at how the morphology or urban fabric of the city, drives thermal energy exchanges across the urban landscape. The study of thermal energy attributes for different cities provides insight into how thermal fluxes and characteristics are partitioned across the city landscape in response to each city's morphology. We are using thermal infrared remote sensing data obtained at a high spatial resolution from aircraft, along with satellite data, to identify and quantify thermal energy characteristics for 4 U.S. cities: Atlanta, GA, Baton Rouge, LA, Salt Lake City, UT, and Sacramento, CA. Analysis of how thermal energy is spatially distributed across the urban landscapes for these cities provides a unique perspective for understanding how the differing morphology of cities forces land-atmosphere exchanges, such as the urban heat island effect, as well as related meteorological and air quality interactions. Keyword: urban ecosystems, remote sensing, urban heat island

Quattrochi, Dale A.↗

NASA NTRS1976

An analysis of metropolitan land-use by machine processing of earth resources technology satellite data

A successful application of state-of-the-art remote sensing technology in classifying an urban area into its broad land use classes is reported. This research proves that numerous urban features are amenable to classification using ERTS multispectral data automatically processed by computer. Furthermore, such automatic data processing (ADP) techniques permit areal analysis on an unprecedented scale with a minimum expenditure of time. Also, classification results obtained using ADP procedures are consistent, comparable, and replicable. The results of classification are compared with the proposed U. S. G. S. land use classification system in order to determine the level of classification that is feasible to obtain through ERTS analysis of metropolitan areas.

Mausel, P. W.↗

NASA NTRS1999

Measuring Thermal Characteristics of Urban Landscapes

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other man-made materials. The temperatures of these artificial surfaces can be 20 to 40 C higher than vegetated surfaces. Materials such as asphalt store much of the sun's energy and remains hot long after sunset. This produces a dome of elevated air temperatures 5 to 8 C greater over the city, compared to the air temperatures over adjacent rural areas. This effect is called the "urban heat island". Urban landscapes are a complex mixture of vegetated and nonvegetated surfaces. It is difficult to take enough temperature measurements over a large city area to characterize the complexity of urban radiant surface temperature variability. However, the use of remotely sensed thermal data from airborne scanners are ideal for the task. In a study funded by NASA, a series of flights over Huntsville, Alabama were performed in September 1994 and over Atlanta, Georgia in May 1997. Analysis of thermal energy responses for specific or discrete surfaces typical of the urban landscape (e.g., asphalt, building rooftops, vegetation) requires measurements at a very fine spatial scale (i.e., <15 m) to adequately resolve these surfaces and their attendant thermal energy regimes. Additionally, very fine scale spatial resolution thermal infrared data, such as that obtained from aircraft, are very useful for demonstrating to planning officials, policy makers, and the general populace, what the benefits are of the urban forest in both mitigating the urban heat island effect, in making cities more aesthetically pleasing and more habitable environments, and in overall cooling of the community. In this presentation we will examine the techniques of analyzing remotely sensed data for measuring the effect of various urban surfaces on their contribution to the urban heat island effect.

Luvall, Jeffrey C.↗

NASA NTRS2023

Portland Urban Development: Quantifying and Visualizing Urban Heat with Compounding Vulnerabilities to Support Community Depaving Initiatives

Urban heat is a pressing concern in Portland, Oregon as climate change induced heat waves increase. Cities experience higher temperatures due to the urban heat island effect (UHI), and environmental injustice and disenfranchisement in minority communities expose low-income and Black, Indigenous, and People of Color (BIPOC) residents to more extreme and debilitating heat events. Our team identified Portland’s communities on the frontlines of urban heat impacts by overlapping environmental and social vulnerabilities using NASA Earth observations. We partnered with Depave, a Portland-based nonprofit that works alongside communities to replace pavement with greenspace in historically disenfranchised areas. Using Landsat 8 Thermal Infrared Sensor (TIRS) imagery, we mapped Land Surface Temperature (LST) and developed a heat-specific Social Vulnerability Index (SVI) through a Principal Component Analysis (PCA) to identify Portland’s communities with the highest potential heat vulnerability. Then, we calculated the temperature change of depaving in six case studies to quantify Depave's efforts in heat mitigation and environmental justice. Our analysis demonstrated that, throughout Portland, there are frontline communities experiencing high potential social vulnerability to extreme temperatures due to environmental injustices and over-pavement. Finally, Depave’s impact on urban heat is observable and quantifiable using remote-sensing data and tools, with an average of 1ºF LST decrease across the six case studies. We illustrated the significance of local urban heat mitigation efforts and propose next steps for conducting inclusive and intentional research that highlights the lived experiences and resilience of frontline communities.

Environmental justice↗

NASA NTRS2012

Assessment of Urbanization on the Integrated Land-Ocean-Atmosphere Environment in Coastal Metropolis in Preparation for HyspIRI

The need for comprehensive studies of the relationships between past and projected changes of regional climate and human activity in comple x urban environments has been well established. The HyspIRI preparato ry airborne activities in California, associated science and applicat ions research, and eventually HyspIRI itself provide an unprecedented opportunity for development and implementation of an integrated data and modeling analysis system focused on coastal urban environments. We will utilize HyspIRI preparatory data collections in developing ne w remote sensing-based tools for investigating the integrated urban e nvironment, emphasizing weather, climate, and energy demands in compl ex coastal cities.

Sequera, Pedro↗

NASA NTRS2018

NASA’s Mid-Atlantic Communities and Areas at Intensive Risk Demonstration: Translating Compounding Hazards to Societal Risk

Remote sensing provides a unique perspective on our dynamic planet, tracking changes and revealing the course of complex interactions. Long term monitoring and targeted observation combine with modeling and mapping to provide increased awareness of hydro-meteorological and geological hazards. Disasters often follow hazards and the goal of NASA’s Disasters Program is to look at the earth as a highly coupled system to reduce risk and enable resilience. Remote sensing and geospatial science are used as tools to help answer critical questions that inform decisions. Data is not the same as information, nor does understanding of processes necessarily translate into decision support for disaster preparedness, response and recovery. Accordingly, NASA is engaging the scientific and decision-support communities to apply remote sensing, modeling, and related applications in Communities and Areas at Intensive Risk (CAIR). In 2017, NASA’s Applied Sciences Disasters Program hosted a regional workshop to explore these issues with particular focus on coastal Virginia and North Carolina. The workshop brought together partners in academia, emergency management, and scientists from NASA and partnering federal agencies to explore capabilities among the team that could improve understanding of the physical processes related to these hazards, their potential impact to changing communities, and to identify methodologies for supporting emergency response and risk mitigation. The resulting initiative, the mid-Atlantic CAIR project, demonstrates the ability to integrate satellite derived earth observations and physical models into actionable, trusted knowledge. Severe storms and associated storm surge, sea level rise, and land subsidence coupled with increasing populations and densely populated, aging critical infrastructure often leave coastal regions and their communities extremely vulnerable. The integration of observations and models allow for a comprehensive understanding of the compounding risk experienced in coastal regions and enables individuals in all positions make risk-informed decisions. This initiative uses a representative storm surge case as a baseline to produce flood inundation maps. These maps predict building level impacts at current day and for sea level rise (SLR) and subsidence scenarios of the future in order to inform critical decisions at both the tactical and strategic levels. To accomplish this analysis, the mid-Atlantic CAIR project brings together Federal research activities with academia to examine coastal hazards in multiple ways: 1) reanalysis of impacts from 2011 Hurricane Irene, using numerical weather modeling in combination with coastal surge and hydrodynamic, urban inundation modeling to evaluate combined impact scenarios considering SLR and subsidence, 2) remote sensing of flood extent from available optical imagery, 3) adding value to remotely sensed flood maps through depth predictions, and 4) examining coastal subsidence as measured through time-series analysis of synthetic aperture radar observations. Efforts and results are published via ArcGIS story maps to communicate neighborhoods and infrastructure most vulnerable to changing conditions. Story map features enable time-aware flood mapping using hydrodynamic models, photographic comparison of flooding following Hurricane Irene, as well as visualization of heightened risk in the future due to SLR and land subsidence.

Rogers, Laura↗

NASA NTRS2007

Impacts of Urbanization in the Coastal Tropical City of San Juan, Puerto Rico

Urban sprawl in tropical locations is rapidly accelerating and it is more evident in islands where a large percentage of the population resides along the coasts. This paper focuses on the analysis of the impacts of land use and land cover for urbanization in the tropical coastal city of San Juan, in the Caribbean island of Puerto Rico. A mesoscale numerical model, the Regional Atmospheric Modeling System (RAMS), is used to study the impacts of land use for urbanization in the environment including specific characteristics of the urban heat island in the San Juan Metropolitan Area (SJMA), one of the most noticeable urban cores of the Caribbean. The research also makes use of the observations obtained during the airborne San Juan Atlas Mission. Surface and rawinsonde data from the mission are used to validate the atmospheric model yielding satisfactory results. Airborne high resolution remote sensing data are used to update the model's surface characteristics in order to obtain a more accurate and detailed configuration of the SJMA and perform a climate impact analysis based on land cover/land use (LCLU) changes. The impact analysis showed that the presence of the urban landscape of San Juan has an impact reflected in higher air temperatures over the area occupied by the city, with positive values of up to 2.5 C, for the simulations that have specified urban LCLU indexes in the model's bottom boundary. One interesting result of the impact analysis was the finding of a precipitation disturbance shown as a difference in total accumulated rainfall between the present urban landscape and with a potential natural vegetation, apparently induced by the presence of the urban area. Results indicate that the urban enhanced cloud formation and precipitation development occur mainly downwind of the city, including the accumulated precipitation. This spatial pattern can be explained by the presence of a larger urbanized area in the southwest sector of the city, and of the approaching northeasterly trade winds. No significant impacts were found in the sea breeze patterns of the city.

Comarazamy, Daniel E.↗

NASA NTRS2007

Impacts of Urbanization in the Coastal Tropical City of San Juan, Puerto Rico

Urban sprawl in tropical locations is rapidly accelerating and it is more evident in islands where a large percentage of the population resides along the coasts. This paper focuses on the analysis of the impacts of land use and land cover for urbanization in the tropical coastal city of San Juan, in the Caribbean island of Puerto Rico. A mesoscale numerical model, the Regional Atmospheric Modeling System (RAMS), is used to study the impacts of land use for urbanization in the environment including specific characteristics of the urban heat island in the San Juan Metropolitan Area (SJMA), one of the most noticeable urban cores of the Caribbean. The research also makes use of the observations obtained during the airborne San Juan Atlas Mission. Surface and raw insonde data from the mission are used to validate the atmospheric model yielding satisfactory results. Airborne high resolution remote sensing data are used to update the model's surface characteristics in order to obtain a more accurate and detailed configuration of the SJMA and perform a climate impact analysis based on land cover/land use (LCLU) changes. The impact analysis showed that the presence of the urban landscape of San Juan has an impact reflected in higher air temperatures over the area occupied by the city, with positive values of up to 2.5 degrees C, for the simulations that have specified urban LCLU indexes in the model's bottom boundary. One interesting result of the impact analysis was the finding of a precipitation disturbance shown as a difference in total accumulated rainfall between the present urban landscape and with a potential natural vegetation, apparently induced by the presence of the urban area. Results indicate that the urban-enhanced cloud formation and precipitation development occur mainly downwind of the city, including the accumulated precipitation. This spatial pattern can be explained by the presence of a larger urbanized area in the southwest sector of the city, and of the approaching northeasterly trade winds.

Comarazamy, Daniel E.↗

NASA NTRS1971

Studies in remote sensing of Southern California and related environments

A summary is presented of the research activities in southern California to determine whether meaningful geographic information was obtainable by use of remote sensing in an area already well documented or if the techniques and methodology could be transferred to related environments. Several broad characteristics of the regional geography were investigated with regards to their feasibility to be studied by aircraft and spacecraft sensors to improve the inventory and understanding of resources and environmental circumstances and to serve as models for future geographic analysis of other regions when using remote sensing devices. Sample activities are described in detail and three experiments producing worthwhile results are highlighted: mapping montane vegetation with color IR imagery, analysis of urban residual environment using color IR aerial photography, and regional agricultural land use mapping tested against color IR photography.

Bowden, L. W.↗

NASA NTRS1994

A GIS approach to urban heat island research: The case of Huntsville, Alabama

The urban heat island represents a case of inadvertent human modification of climate in an urban environment. Urbanization changes the nature of the surface and atmospheric properties of a region. As a result, radiation balance in the urban areas is altered and sensible heat is added to the point that urban areas are warmer than surrounding rural areas. At the boundary between the rural and urban area, a sharp rise in temperature occurs, culminating to a peak temperature at the central business district of the city, hence the name 'urban heat island'. The extent and intensity of the urban heat island are a function of population size, land use, and topography. Because the urban heat island exhibits spatial variations of temperatures, the use of Geographic Information System (GIS) is appropriate. The research on the urban heat island focuses on the acquisition of 15 bands of visible and thermal infrared data (ranging from 0.45 to 12.2 microns) from an aerial platform using NASA's ATLAS (Airborne Thermal/Visible Land Application Sensor) over Huntsville, Alabama. The research reported in this paper is an analysis of the impact of population, land use, and topography on the shape of the urban heat island that could be developed in Huntsville using the GIS approach. The outcome of this analysis can then be verified using the acquired remotely sensed data.

Lo, Chor Pong↗

NASA NTRS1975

Urban environmental health applications of remote sensing, summary report

Health and its association with the physical environment was studied based on the hypothesis that there is a relationship between the man-made physical environment and health status of a population. The statistical technique of regression analysis was employed to show the degree of association and aspects of physical environment which accounted for the greater variation in health status. Mortality, venereal disease, tuberculosis, hepatitis, meningitis, shigella/salmonella, hypertension and cardiac arrest/myocardial infarction were examined. The statistical techniques were used to measure association and variation, not necessarily cause and effect. Conclusions drawn show that the association still exists in the decade of the 1970's and that it can be successfully monitored with the methodology of remote sensing.

Rush, M.↗