Dale A. Quattrochi

Application of High-Resolution Thermal Infrared Remote Sensing and GIS to Assess the Urban Heat Island Effect

Abstract Day and night airborne thermal infrared image data at 5 m spatial resolution acquired with the 15-channel (0.45mum-12.2mum) Advanced Thermal and Land Applications Sensor (ATLAS) over Alabama, Huntsville on 7 September, 1994 were used to study changes in the thermal signatures of urban land cover types between day and night. Thermal channel number 13 (9.60 mum-10.2mum) data with the best noise-equivalent temperature change (NEDeltaT) of 0.25 C after atmospheric corrections and temperature calibration were selected for use in this analysis. This research also examined the relation between land cover irradiance and vegetation amount, using the Normalized Difference Vegetation Index (NDVI), obtained by ratioing the difference and the sum of the red (channel number 3: 0.60-0.63mum) and reflected infrared (channel number 6: 0.76-0.90mum) ATLAS data. Based on the mean radiance values, standard deviations, and NDVI extracted from 351 pairs of polygons of day and night channel number 13 images for the cit...

Land-Use and Land-Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

Land-use and land-cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973, 1979, 1983, 1987, 1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred, with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119 percent between 1973 and 1997. These land-use and land-cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect at both the urban canopy and urban boundary layers as well as an increase in ground level ozone production to such an extent that Atlanta has violated EPA’s ozone level standard in recent years. Using canonical correlation analysis, surface temperatures and NDVI, extracted from Landsat TM images, were found to correlate strongly with volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, but only weakly with the rates of cardiovascular and chronic lower respiratory diseases, which also did not exhibit strong correlation with VOC and NOx emissions, possibly because other factors such as demographic and socio-economic may also be involved. Further research is therefore needed to understand the health geography and its relationship to landuse and land-cover change. This paper illustrates the usefulness of a remote sensing approach for this purpose.

Thermal Infrared Remote Sensing for Analysis of Landscape Ecological Processes: Methods and Applications

Thermal infrared (TIR) remote sensing data can provide important measurements of surface energy fluxes and temperatures, which are integral to understanding landscape processes and responses. One example of this is the successful application of TIR remote sensing data to estimate evapotranspiration and soil moisture, where results from a number of studies suggest that satellite-based measurements from TIR remote sensing data can lead to more accurate regional-scale estimates of daily evapotranspiration. With further refinement in analytical techniques and models, the use of TIR data from airborne and satellite sensors could be very useful for parameterizing surface moisture conditions and developing better simulations of landscape energy exchange over a variety of conditions and space and time scales. Thus, TIR remote sensing data can significantly contribute to the observation, measurement, and analysis of energy balance characteristics (i.e., the fluxes and redistribution of thermal energy within and across the land surface) as an implicit and important aspect of landscape dynamics and landscape functioning.The application of TIR remote sensing data in landscape ecological studies has been limited, however, for several fundamental reasons that relate primarily to the perceived difficulty in use and availability of these data by the landscape ecology community, and from the fragmentation of references on TIR remote sensing throughout the scientific literature. It is our purpose here to provide evidence from work that has employed TIR remote sensing for analysis of landscape characteristics to illustrate how these data can provide important data for the improved measurement of landscape energy response and energy flux relationships. We examine the direct or indirect use of TIR remote sensing data to analyze landscape biophysical characteristics, thereby offering some insight on how these data can be used more robustly to further the understanding and modeling of landscape ecological processes.

Measurement and analysis of thermal energy responses from discrete urban surfaces using remote sensing data

Abstract This study employs data from the airborne Thermal Infrared Multispectral Scanner (TIMS) to measure thermal (i.e., longwave) energy responses, emitted or upwelling, from discrete surfaces that are typical of the city landscape within Salt Lake City, Utah, over a single diurnal time period (i.e., a single day/night-time sequence). These data are used to quantify the disposition of thermal energy for selected urban surfaces during the daytime and night-time, and the amount of change in thermal response or flux recorded between day and night. An analysis is presented on the thermal interrelationships observed for common urban materials for day, night, and flux, as identified from the TIMS data through the delineation of discrete surface type polygons. The results from the study illustrate that such factors as heat capacity, thermal conductivity, and the amount of soil moisture available have a profound impact on the magnitude of thermal energy emanating from a specific surface and on the dynamics of ...

Implementation and operation of three fractal measurement algorithms for analysis of remote-sensing data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomena. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. The purpose of this paper is to introduce and implement three algorithms in C code for deriving fractal measurement from remotely sensed data. These three methods are: the line-divider method, the variogram method, and the triangular prism method. Remote-sensing data acquired by NASAs Calibrated Airborne Multispectral Scanner (CAMS) are used to compute the fractal dimension using each of the three methods. These data were obtained as a 30 m pixel spatial resolution over a portion of western Puerto Rico in January 1990. A description of the three methods, their implementation in PC-compatible environment, and some results of applying these algorithms to remotely sensed image data are presented.

The impact of distinct anthropogenic and vegetation features on urban warming

We investigate the direct relationship between detailed urban land cover classes, derived from fine resolution QuickBird satellite data, and land surface temperatures (Celsius), generated from ASTER imagery, over Phoenix, Arizona. Using daytime and nighttime temperatures in both winter and summer and all observation points (nxa0=xa011,025), we develop linear, non-linear and multiple regression models to explore the relationship. Conventional wisdom suggests that all urban features result in increased temperatures. Rather, our results show that a mass of buildings is not necessarily or holistically responsible for extreme heat in desert cities. It is the construction of other impervious dark surfaces (i.e., asphalt roads) associated with buildings that result in extreme heat. Moreover, our results suggest that buildings, especially commercial buildings with high albedo roofs, actually reduce temperatures. The addition of trees and shrubs, as opposed to grass, around buildings can further mitigate extreme heat by providing more cooling during the summer and increasing nighttime temperatures in the winter. In conclusion, the compositional design of and avoidance of dark impervious materials in desert cities help mitigate extreme temperatures. It is important to note, however, that design choices that reduce extreme heat must be made within the broader context of tradeoffs and unintended consequences to ensure the sustainability of these cities.

Analysis of Vegetation Within A Semi-Arid Urban Environment Using High Spatial Resolution Airborne Thermal Infrared Remote Sensing Data

Abstract High spatial resolution (5 m) remote sensing data obtained using the airborne Thermal Infrared Multispectral Scanner (TIMS) sensor for daytime and nighttime have been used to measure thermal energy responses for 2 broad classes and 10 subclasses of vegetation typical of the Salt Lake City, Utah urban landscape. Polygons representing discrete areas corresponding to the 10 subclasses of vegetation types have been delineated from the remote sensing data and are used for analysis of upwelling thermal energy for day, night, and the change in response between day and night or flux, as measured by the TIMS. These data have been used to produce three-dimensional graphs of energy responses in W m−2 for day, night, and flux, for each urban vegetation land cover as measured by each of the six channels of the TIMS sensor. Analysis of these graphs provides a unique perspective for both viewing and understanding thermal responses, as recorded by the TIMS, for selected vegetation types common to Salt Lake City. A descriptive interpretation is given for each of the day, night, and flux graphs along with an analysis of what the patterns mean in reference to the thermal properties of the vegetation types surveyed in this study. From analyses of these graphs, it is apparent that thermal responses for vegetation can be highly varied as a function of the biophysical properties of the vegetation itself, as well as other factors. Moreover, it is also seen where vegetation, particularly trees, has a significant influence on damping or mitigating the amount of thermal radiation upwelling into the atmosphere across the Salt Lake City urban landscape.

A comparison of local variance, fractal dimension, and Moran's I as aids to multispectral image classification

The accuracy of traditional multispectral maximum‐likelihood image classification is limited by the multi‐modal statistical distributions of digital numbers from the complex, heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Morans I index of spatial autocorrelation in segmenting multispectral satellite imagery with the goal of improving urban land cover classification accuracy. Tools available in the ERDAS ImagineTM software package and the Image Characterization and Modeling System (ICAMS) were used to analyse Landsat ETMu2009+ imagery of Atlanta, Georgia. Images were created from the ETMu2009+ panchromatic band using the three texture indices. These texture images were added to the stack of multispectral bands and classified using a supervised, maximum likelihood technique. Although each texture band improved the classification accuracy over a multispectral only effort, the addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per‐pixel spectral classification techniques.

On the Seasonal Occurrence and Abundance of the Zika Virus Vector Mosquito Aedes Aegypti in the Contiguous United States.

Introduction: An ongoing Zika virus pandemic in Latin America and the Caribbean has raised concerns that travel-related introduction of Zika virus could initiate local transmission in the United States (U.S.) by its primary vector, the mosquito Aedes aegypti. Methods: We employed meteorologically driven models for 2006-2015 to simulate the potential seasonal abundance of adult Aedes aegypti for fifty cities within or near the margins of its known U.S. range. Mosquito abundance results were analyzed alongside travel and socioeconomic factors that are proxies of viral introduction and vulnerability to human-vector contact. Results: Meteorological conditions are largely unsuitable for Aedes aegypti over the U.S. during winter months (December-March), except in southern Florida and south Texas where comparatively warm conditions can sustain low-to-moderate potential mosquito abundance. Meteorological conditions are suitable for Aedes aegypti across all fifty cities during peak summer months (July-September), though the mosquito has not been documented in all cities. Simulations indicate the highest mosquito abundance occurs in the Southeast and south Texas where locally acquired cases of Aedes-transmitted viruses have been reported previously. Cities in southern Florida and south Texas are at the nexus of high seasonal suitability for Aedes aegypti and strong potential for travel-related virus introduction. Higher poverty rates in cities along the U.S.-Mexico border may correlate with factors that increase human exposure to Aedes aegypti. Discussion: Our results can inform baseline risk for local Zika virus transmission in the U.S. and the optimal timing of vector control activities, and underscore the need for enhanced surveillance for Aedes mosquitoes and Aedes-transmitted viruses.

Impact of urbanization on US surface climate

We combine Landsat and MODIS data in a land model to assess the impact of urbanization on US surface climate. For cities built within forests, daytime urban land surface temperature (LST) is much higher than that of vegetated lands. For example, in Washington DC and Atlanta, daytime mean temperature differences between impervious and vegetated lands reach 3.3 and 2.0 °C, respectively. Conversely, for cities built within arid lands, such as Phoenix, urban areas are 2.2 °C cooler than surrounding shrubs. We find that the choice and amount of tree species in urban settings play a commanding role in modulating cities LST. At continental and monthly scales, impervious surfaces are 1.9 °C ± 0.6 °C warmer than surroundings during summer and expel 12% of incoming precipitation as surface runoff compared to 3.2% over vegetation. We also show that the carbon lost to urbanization represents 1.8% of the continental total, a striking number considering urbanization occupies only 1.1% of the US land. With a small areal extent, urbanization has significant effects on surface energy, water and carbon budgets and reveals an uneven impact on surface climate that should inform upon policy options for improving urban growth including heat mitigation and carbon sequestration.