{"id":201987,"date":"2015-09-04T11:47:48","date_gmt":"2015-09-04T15:47:48","guid":{"rendered":"http:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/uncategorized\/project-atlanta-urban-heat-island-study.php"},"modified":"2015-09-04T11:47:48","modified_gmt":"2015-09-04T15:47:48","slug":"project-atlanta-urban-heat-island-study","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/nasa\/project-atlanta-urban-heat-island-study.php","title":{"rendered":"Project ATLANTA &#8211; Urban Heat Island Study"},"content":{"rendered":"<p><p>High Spatial Resolution Airborne Multispectral Thermal    Infrared Data to Support Analysis and Modeling Tasks in EOS IDS    Project ATLANTA<\/p>\n<p>    Dale A. Quattrochi (dale.quattrochi@msfc.nasa.gov),    NASA, Global Hydrology and Climate Center, Huntsville, AL  <\/p>\n<p>    Jeffrey C. Luvall (jeff.luvall@msfc.nasa.gov)    , NASA, Global Hydrology and Climate Center, Huntsville, AL<\/p>\n<p>    Background<\/p>\n<p>    Project ATLANTA (ATlanta Land-use ANalysis: Temperature and    Air-quality) as a newly-funded NASA EOS Interdisciplinary    Science (IDS) investigation in 1996, seeks to observe, measure,    model, and analyze how the rapid growth of the Atlanta, Georgia    metropolitan area since the early 1970's has impacted the    region's climate and air quality. The primary objectives for    this research effort are: 1) To investigate and model the    relationship between Atlanta urban growth, land cover change,    and the development of the urban heat island phenomenon through    time at nested spatial scales from local to regional; 2) To    investigate and model the relationship between Atlanta urban    growth and land cover change on air quality through time at    nested spatial scales from local to regional; and 3) To model    the overall effects of urban development on surface energy    budget characteristics across the Atlanta urban landscape    through time at nested spatial scales from local to regional.    Our key goal is to derive a better scientific understanding of    how land cover changes associated with urbanization in the    Atlanta area, principally in transforming forest lands to urban    land covers through time, has, and will, effect local and    regional climate, surface energy flux, and air quality    characteristics. Allied with this goal is the prospect that the    results from this research can be applied by urban planners,    environmental managers and other decision-makers, for    determining how urbanization has impacted the climate and    overall environment of the Atlanta area. It is our intent to    make the results available from this investigation to help    facilitate measures that can be applied to mitigate    climatological or air quality degradation, or to design    alternate measures to sustain or improve the overall urban    environment in the future. Project ATLANTA is a    multidisciplinary research endeavor and enlists the expertise    of 8 investigators: Dale Quattrochi (PI) (NASA\/Global Hydrology    Center); Jeffrey Luvall (NASA\/Global Hydrology and Climate    Center); C.P. Lo (University of Georgia); Stanley Kidder    (Colorado State University); Haider Taha (Lawrence Berkeley    National Laboratory); Robert Bornstein (San Jose State    University); Kevin Gallo (NOAA\/NESDIS); and Robert Gillies    (Utah State University).<\/p>\n<p>    Atlanta Urban Growth and Effects on Climate and Air    Quality<\/p>\n<p>    In the last half of the 20th century, Atlanta, Georgia has    risen as the premier commercial, industrial, and transportation    urban area of the southeastern United States. The rapid growth    of the Atlanta area, particularly within the last 25 years, has    made Atlanta one of the fastest growing metropolitan areas in    the United States. The population of the Atlanta metropolitan    area increased 27% between 1970 and 1980, and 33% between    1980-1990 (Research Atlanta, Inc., 1993). Concomitant with this    high rate of population growth, has been an explosive growth in    retail, industrial, commercial, and transportation services    within the Atlanta region. This has resulted in tremendous land    cover change dynamics within the metropolitan region, wherein    urbanization has consumed vast acreages of land adjacent to the    city proper and has pushed the rural\/urban fringe farther and    farther away from the original Atlanta urban core. An enormous    transition of land from forest and agriculture to urban land    uses has occurred in the Atlanta area in the last 25 years,    along with subsequent changes in the land-atmosphere energy    balance relationships.<\/p>\n<p>    Air quality has degenerated over the Atlanta area, particularly    in regard to elevations in ozone and emissions of volatile    organic compounds (VOCs), as indicated by results from the    Southern Oxidants Study (SOS) which has focused a major effort    on measuring and quantifying the air quality over the Atlanta    metropolitan region. SOS modeling simulations for Atlanta using    U.S. Environmental Protection Agency (EPA) State Implementation    Plan guidelines suggest that a 90% decrease in nitrogen oxide    emissions, one of the key elements in ozone production, will be    required to bring Atlanta into attainment with the present    ozone standard (SOS, 1995).<\/p>\n<p>    Project ATLANTA Science Approach<\/p>\n<p>    The scientific approach we are using in relating land cover    changes with modifications in the local and regional climate    and in air quality, is predicated on the analysis of remote    sensing data in conjunction with in situ data (e.g.,    meteorological measurements) that are employed to initialize    local and regional-level numerical models of land-atmosphere    interactions. Remote sensing data form the basis for    quantifying how land covers have changed within the Atlanta    metropolitan area through time from the mid-1970's, when    Atlanta's dramatic growth began in earnest, to the present.    These remotely sensed data will be used to provide input to    numerical models that relate land cover change through time    with surface energy flux and meteorological parameters to    derive temporal models of how land cover changes have impacted    both the climatology and the air quality over the Atlanta    region. Current remote sensing data (i.e., data obtained during    1997) will be used to calibrate the models and as baseline data    for extending the models to predict how prospective future land    cover changes will effect the local and regional climate and    air quality over the Atlanta-north Georgia region.    Additionally, remote sensing data will be used as an indirect    modeling method to describe urbanization and deforestation    parameters that can be used to assess, as well as predict, the    effects of land use changes on the local microclimate.<\/p>\n<p>    In concert with the remote sensing-based analysis and modeling    of land cover changes is an extensive numerically-based    modeling effort to better understand the cause-and-effect    relationships between urbanization and trends in climatology    and air quality. Sophisticated numerical meteorological models    can complement extensive field monitoring projects and help    improve our understanding of these relationships and the    evolution of the urban climate on a location-specific basis.    Measured data alone cannot resolve the relationships between    the many causes of urban heat islands\/urban climates and    observations. For example, measured data cannot directly    attribute a certain fraction of temperature rise to a certain    modification in land use patterns, change in energy    consumption, or release of anthropogenic heat into the    atmosphere. These are aspects that numerical modeling can help    resolve. Similarly, monitored air quality data cannot be used    to establish a direct cause-and-effect relationship between    emission sources, activities, or urbanization and observed air    quality (e.g., smog). In this sense, photochemical models can    be used in testing the sensitivity of ozone concentrations to    changes in various land-use components, emission modifications    and control, or other strategies. Thus, we are incorporating an    assessment of land cover\/land use change as measured from    remote sensing data, with temporal numerical modeling    simulations to better understand the effects that the growth of    Atlanta has had on local and regional climate characteristics    and air quality.<\/p>\n<p>    ATLAS Data: Role and Characteristics<\/p>\n<p>    To augment the quantitative measurements of land cover change    and land surface thermal characteristics derived from satellite    data (i.e, Landsat MSS and TM data for assessment of land cover    change; Landsat TM thermal, and AVHRR and GOES data for land    surface thermal characteristics), we are employing high spatial    resolution airborne multispectral thermal data to provide    detailed measurements of thermal energy fluxes that occur for    specific surfaces (e.g., pavements, buildings) across the    Atlanta urban landscape, and the changes in thermal energy    response for these surfaces between day and night. This    information is critical to resolving the underlying surface    responses that lead to development of local and regional-scale    urban climate processes, such as the urban heat island    phenomenon and related characteristics. (Quattrochi and Ridd,    1994, 1997). These aircraft data will also be used to develop a    functional classification of the thermal attributes of the    Atlanta metropolitan area to better understand the energy    budget linkages between the urban surface and the boundary    layer atmosphere. This will be performed using the Thermal    Response Number (TRN) (Luvall and Holbo, 1989; Luvall, 1997)    which is expressed as<\/p>\n<p>    Where Rn is total net radiation and T change in surface temperature for time    period t1 to t2.<\/p>\n<p>    Because urban landscapes are very complex in composition, the    partitioning of energy budget terms depends on surface type. In    natural landscapes, the partitioning is dependent on canopy    biomass, leaf area index, aerodynamic roughness, and moisture    status, all of which are influenced by the development stage of    the ecosystem. In urban landscapes, however, the distribution    of artificial or altered surfaces substantially modifies the    surface energy budget. Thus, one key component of Project    ATLANTA is to measure and model surface energy responses in    both space and time, to better understand the    processes-responses of urban climate and air quality    interactions across the Atlanta metropolitan area.<\/p>\n<p>    The airborne sensor used to acquire high spatial resolution    multispectral thermal infrared data over Atlanta is the    Advanced Thermal and Land Applications Sensor (ATLAS), which is    flown onboard a Lear 23 jet aircraft operated by the NASA    Stennis Space Center. The ATLAS is a 15-channel multispectral    scanner that basically incorporates the bandwidths of the    Landsat TM (along with several additional channels) and 6    thermal IR channels similar to that available on the airborne    Thermal Infrared Multispectral Scanner (TIMS) sensor (Table 1).    Of particular importance to the Atlanta study is the    multispectral thermal IR capability of the ATLAS instrument.    ATLAS thermal IR data, collected at a very high spatial    resolution, have been used to study urban surface energy    responses in a previous study over the Huntsville, Alabama    metropolitan area with excellent results (Lo et al., 1997).<\/p>\n<p>    ATLAS Data Collection<\/p>\n<p>    ATLAS data were collected over a 48 x 48 km2 area,    centered on the Atlanta Central Business District (CBD) on May    11 and 12, 1997. An early May data acquisition window was    selected to facilitate the collection of ATLAS data during the    spring when vegetation canopy was filled out, surface    temperatures were high enough to permit substantial heating of    the urban landscape, and there was a high probability that cool    fronts would still be moving through the Atlanta area to permit    clear skies, as opposed to later in the spring or summer when    increased cloud cover or convective storms become limiting    factors in obtaining aircraft data. ATLAS data were collected    at a 10m pixel spatial resolution during the daytime, between    approximately 11:00 a.m. and 3:00 p.m. local time (Eastern    Daylight Time) to capture the highest incidence of solar    radiation across the city landscape around solar noon. ATLAS    10m data were also obtained the following morning (May 12)    between 2:00-4:00 a.m. local time (Eastern Daylight Time) to    measure the Atlanta urban surface during the coolest time of    the diurnal energy cycle. Eleven flight lines were required to    cover the 48 x 48 km2 area at a 10m spatial    resolution. To permit the derivation of TRN values, all 11    daytime flight lines were flown and then repeated later at    about a 2 hour interval. Nighttime overflights were not    repeated because of the relative invariance in thermal energy    fluxes at night which obviated the need to calculate TRNs.<\/p>\n<p>    Sky conditions at the time of the daytime overflights were    mostly clear with some cirrus clouds present. The Lear jet    aircraft flew at an altitude of 5,063m above mean terrain to    achieve a 10m pixel resolution which was well below the cirrus    clouds. Cirrus clouds covered the entire Atlanta metropolitan    area during the night flights. The presence of cirrus cloud    cover at night did, to some extent, dampen the cooling effect    of thermal energy release to a clear sky, but air temperatures    were still sufficiently cool to provide ample difference with    daytime heating. Maximum air temperatures during the daytime    overflights were approximately 25oC, while air    temperature during the nighttime flights was around    10oC. Sample surface temperatures for tree-shaded    grass, tree canopy, and asphalt in full sunlight recorded with    a hand-held infrared thermometer (8-14 lm) during    the afternoon were 28oC, 21oC, and    50oC, respectively. Daytime temperatures for a    commercial building roof comprised of rock\/membrane coating    ranged from 49oC to 52oC. This    illustrates that although air temperatures were cooler than    optimal for development of the urban heat island effect, there    was still significant heating by artificial urban surfaces to    permit good contrast with nighttime cooling.<\/p>\n<p>    Atmospheric radiance must be accounted for in order to obtain    calibrated surface temperatures. Although the ATLAS thermal    channels fall within the atmospheric window for atmospheric    longwave transmittance (8.0-13.0 m), the maximum transmittance    is only about 80%. The amount of atmospheric radiance in the    atmospheric window is mostly dependent on the atmospheric water    vapor content, although there is an ozone absorption band    around 9.5 m. To assist in obtaining accurate thermal surface    energy response measurements from the ATLAS data, radiosonde    launches were made concurrently with both the daytime and    nighttime overflights. The atmospheric profiles obtained from    these radiosonde data are then incorporated into the MODTRAN3    model for calculation of atmospheric radiance (Berk et al.,    1989). The output from MODTRAN3 is combined with calibrated    ATLAS spectral response curves and blackbody information    recorded during the flight, using the Earth Resources    Laboratory Applications Software (ELAS) module TRADE (Thermal    Radiant Temperature) (Graham et al., 1986), to produce a    look-up table for pixel temperatures as a function of ATLAS    values (Anderson, 1992).<\/p>\n<p>    One pyranometer and one pyrgeometer were also stationed on a    rooftop within one of aircraft flight lines for use in    measuring incoming shortwave and longwave radiation within the    study area. Additionally, two shadowband radiometers were    placed in strategic locations within the flight path for use in    measuring shortwave visible radiation for determining    visibility parameters for input into MODTRAN3. The output from    MODTRAN3 is combined with calibrated ATLAS spectral response    curves and onboard calibration lamp information recorded during    the flight in TRADE to produce calibrated at-sensor radiance    for the visible wavelengths.<\/p>\n<p>    ATLAS Data: Some Examples<\/p>\n<p>    Approximately 5 Gb of raw (unprocessed) ATLAS data were    collected during the May 11-12 aircraft overflights. In    addition to the digital ATLAS data, color infrared aerial    photography at 1:32,000 scale was obtained during daytime    mission. Figure 1 illustrates daytime    thermal (channel 13 - 9.60-10.2 m) ATLAS data collected over    the Atlanta CBD area. Figure 2 provides    an example of ATLAS data (channel 13) acquired during the night    over the Atlanta CBD. Both images are oriented with north at    the top. Excluding the effects of the highly variable    emissivites of urban building materials, an empirical    observation of the images presented in Figures 1 and 2    illustrates the wide range of thermal energy responses present    across the Atlanta city landscape, as well as the detail that    can be discerned from the 10m data. The Georgia Dome, an    enclosed football stadium, appears as the large square-shaped    structure due west of the Atlanta city center. Interstate    highways 75\/85 which traverse in a north-south direction around    the city center, are seen as a dark \"ribbon\" on the day data    (Figure 1) just to the east of downtown Atlanta. Just south of    the city center, is the junction of Interstate Highways 75\/85    and 20. Shadows from tall buildings located in the Atlanta city    center can also be observed on the daytime data. In Figure 1,    the intense thermal energy responses from buildings, pavements    and other surfaces typical of the urban landscape, as well as    the heterogeneous distribution of these responses, stand in    significant contrast to the relative \"flatness\" of Atlanta    thermal landscape at night (Figure 2). Also, the damping effect    that the urban forest has on upwelling thermal energy responses    is evident, particularly in the upper right side of the daytime    image where residential tree canopy is extensive. In Figure 2,    there is still evidence, even in the very early morning, of    elevated thermal energy responses from buildings and other    surfaces in the Atlanta CBD and from streets and highways. It    appears that thermal energy responses for vegetation across the    image are relatively uniform at night, regardless of vegetative    type (e.g., grass, trees).<\/p>\n<p>    ATLAS Data Analysis: The Next Steps<\/p>\n<p>    From the images in Figures 1 and 2, it is apparent that high    resolution ATLAS data offer a unique opportunity to measure,    analyze and model the state and dynamics of thermal energy    responses across the Atlanta metropolitan landscape. In    addition to deriving energy balance measurements for day and    night, and TRN values for specific urban surfaces to better    understand the thermal characteristics that drive the    development of the urban heat island phenomena and the overall    Atlanta urban climate, these multispectral ATLAS data also    exist as database record of current land cover\/land use    conditions for the Atlanta metropolitan area. Along with the    extensive meteorological data available via a network of    mesonet stations that are currently operating across the    Atlanta area, the ATLAS data will be used to initialize and    calibrate the meteorological and air quality models that will    be run for the time period when the airborne data were    collected. Moreover, one of the key facets from Project ATLANTA    is to work with local planning agencies, such as the Atlanta    Regional Commission (ARC), to model how the continued growth of    Atlanta will impact the climate and air quality of the north    Georgia region. The ARC is currently developing a 20-year    growth plan for a 10 county area around Atlanta. Using the    ATLAS data obtained in May, 1997 as a baseline for land    cover\/land use, our objective is to perform some \"prospective\"    modeling on how meteorological conditions and air quality will    change, predicated on the ARC's 20-year plan. By doing so, we    hope to provide the ARC and other planning or decision-making    bodies, with model output that can be used to modify or revise    growth plans for the Atlanta metropolitan area, and to help    mitigate or ameliorate the expansion of the urban heat island    effect or the further deterioration in air quality.<\/p>\n<p>    References<\/p>\n<p>    Anderson, J. E., 1992. Determination of water surface    temperature based on the use of thermal infrared multispectral    scanner data. Geocarto International 3:3-8.<\/p>\n<p>    Berk, A., L. S. Bernstein, and D. C. Robertson., 1989: Modtran:    A Moderate Resolution Model for Lowtran 7. U.S. Air    Force Geophysics Laboratory, Environmental Research Papers    GL-TR-89-0122, Hanscom Air Force Base, MA, 37 pp.<\/p>\n<p>    Graham, M.H., B.G. Junkin, M.T. Kalcic, R.W. Pearson and B.R.    Seyfarth, 1986. ELAS - Earth resources laboratory    applications software. Revised Jan.1986. NASA\/NSTL\/ERL    Report No. 183.<\/p>\n<p>    Lo, C.P., D.A. Quattrochi, and J.C. Luvall, 1997. Application    of high-resolution thermal infrared remote sensing and GIS to    assess the urban heat island effect. International Journal    of Remote Sensing 18:287-304.<\/p>\n<p>    Luvall, J.C., and H. R. Holbo, 1989: Measurements of short-term    thermal responses of coniferous forest canopies using thermal    scanner data. Remote Sensing of Environment, 27,    1-10.<\/p>\n<p>    Luvall, J.C., 1997. The use of remotely sensed surface    temperatures from an aircraft-based thermal infrared    multispectral scanner (TIMS) to estimate the spatial and    temporal variability of latent heat fluxes and thermal response    numbers from a white pine (Pinus strobus L.) plantation.    In Scale in Remote Sensing and GIS, D.A. Quattrochi and    M.F. Goodchild, eds. CRC\/Lewis Publishers, Boca Raton, FL,    pp.169-185.<\/p>\n<p>    Quattrochi, D.A. and M.K. Ridd, 1994. Measurement and analysis    of thermal energy responses from discrete urban surfaces using    remote sensing data. International Journal of Remote    Sensing 15:1991-2022.<\/p>\n<p>    Quattrochi, D.A. and M.K. Ridd, 1997. Analysis of vegetation    within a semi-arid urban environment using high spatial    resolution airborne thermal infrared remote sensing data.    Atmospheric Environment (In press).<\/p>\n<p>    Research Atlanta, Inc., 1993: The Dynamics of Change: An    Analysis of Growth in Metropolitan Atlanta over the Past Two    Decades. Policy Research Center, Georgia State University,    Atlanta.<\/p>\n<p>    SOS, 1995. The State of the Southern Oxidants Study:    Policy-Relevant Findings in Ozone Pollution Research    1988-1994. Southern Oxidants Study: Raleigh, NC, 94 pp.  <\/p>\n<p>    Figure Captions<\/p>\n<p>    Figure 1. ATLAS daytime thermal image (channel 13 -- 9.60-10.2    m) of the Atlanta central business district area. These data    have not been geometrically or atmospherically corrected.<\/p>\n<p>    Figure 2. ATLAS nighttime thermal image (channel 13 --    9.60-10.2 m) of the Atlanta central business district area.    These data have not been geometrically or atmospherically    corrected.  <\/p>\n<p>    Global Hydrology and Climate    Center  <\/p>\n<p>    Responsible Official: Dr. Steven J. Goodman    (steven.goodman@nasa.gov)    Page Curator: Paul J. Meyer (paul.meyer@msfc.nasa.gov)<\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Read more:<\/p>\n<p><a target=\"_blank\" href=\"http:\/\/wwwghcc.msfc.nasa.gov\/atlanta\/\" title=\"Project ATLANTA - Urban Heat Island Study\">Project ATLANTA - Urban Heat Island Study<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> High Spatial Resolution Airborne Multispectral Thermal Infrared Data to Support Analysis and Modeling Tasks in EOS IDS Project ATLANTA Dale A. Quattrochi (dale.quattrochi@msfc.nasa.gov), NASA, Global Hydrology and Climate Center, Huntsville, AL Jeffrey C. Luvall (jeff.luvall@msfc.nasa.gov) , NASA, Global Hydrology and Climate Center, Huntsville, AL Background Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air-quality) as a newly-funded NASA EOS Interdisciplinary Science (IDS) investigation in 1996, seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/nasa\/project-atlanta-urban-heat-island-study.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[20],"tags":[],"class_list":["post-201987","post","type-post","status-publish","format-standard","hentry","category-nasa"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/201987"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=201987"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/201987\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=201987"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=201987"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=201987"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}