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At least 37 records · Page 2

Lidar Observation of Aerosol and Temperature Stratification over Urban Area During the Formation of a Stable Atmospheric PBL

In recent years, the processes in the atmospheric planetary boundary layer (PBL) over urban areas were intensely investigated, due to ecological problems related to the air, soil, and water pollution. New pollution sources in new residential districts, when in contradiction to the microclimate and topography requirements of that region, create a number of considerable hazards and problems. The present study is a continuation of our preceding investigations and aims at revealing the aerosol structure and stratification during the transition after sunset as measured by two lidars. Such observation of the nocturnal, stable PBL formation over an urban area in Bulgaria has not been reported before. The lidars' high time and spatial resolutions allow the changes of the internal structure of the PBL's part located above the surface layer to be observed.

Kolev, I.↗

2000 Knoxville Urban Area Household Travel Behavior Survey

This survey, conducted by NuStats, was a comprehensive study of travel behavior in Knox and Blount counties in the Knoxville urban area. The purpose of the survey was to collect weekday travel characteristics of household members (ages five and older) in the counties during a 24-hour timeframe. The data will be used by the Knoxville Urban Area Metropolitan Planning Organization and local agencies to update transportation and air quality models and to identify transportation needs in the region. The survey was conducted between November 2000 and February 2001. In total, 2,674 households were recruited to participate in the survey. Of these, 1,538 households reported data from a one-day travel log, totaling 12,631 trips by 3,522 persons. Of all trips originating in the study area, three-fourths were made by persons residing in Knox County.

1Hz data↗

Urban area delineation and detection of change along the urban-rural boundary as derived from LANDSAT digital data

LANDSAT digital multispectral scanner data, in conjunction with supporting ground truth, were investigated to determine their utility in delineation of urban-rural boundaries. The digital data for the metropolitan areas of Washington, D. C.; Austin, Texas; and Seattle, Washingtion; were processed using an interactive image processing system. Processing focused on identification of major land cover types typical of the zone of transition from urban to rural landscape, and definition of their spectral signatures. Census tract boundaries were input into the interactive image processing system along with the LANDSAT single and overlayed multiple date MSS data. Results of this investigation indicate that satellite collected information has a practical application to the problem of urban area delineation and to change detection.

Christenson, J. W.↗

Assessing urbanized area expansion through the integration of Landsat and conventional data /79052/

An image base information system (IBIS) is utilized to integrate Landsat and census data for the purpose of mapping urban land and updating urbanized-area outer lines. IBIS is a subset of the video image communication and retrieval digital image processing system developed at JPL. IBIS is used to analyze three urban areas: Orlando, Florida; Seattle, Washington; and Boston, Massachusetts. In all three applications the primary objective is to map the expansion of urban land cover in the urban fringe. Pertinent tabular reports are produced.

Davis, J. B.↗

High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP3 and SSP5 [Updated simulations based on population-driven urban intensity transitions]

These data (v3) are updated from previous versions (1 and 2) in that they include consider the effects of population on transitions in urban land intensity. This leads to more reasonable differences in urban land projections under variant SSPs. For the present dataset, both SSP3 and SSP5 are provided. These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Dataset (NLCD) classification. NLCD 21-24 correspond to open developed, low developed, medium developed, and high developed urban land classes, respectively. Only urban land cover classes (NLCD class 21, 22, 23, and 24) are dynamic over time; however, all NLCD classes are included in the final product. Therefore, NLCD classes that do not convert to an urban class will be similar to year 2000. The products were developed using a hybridized statistical and cellular automata approach. Linear mixed models (LMMs) were used to estimate future urban land budgets based on 1-km urban land fraction projections from Gao and Pesaresi (2021), whereas separate generalized linear mixed models (GLMMs) were used to estimate shifts in urban land intensities based on retrospective shifts in NLCD urban class intensities over a 20- year period. Based on urban land allocations from the statistical models, a cellular-automata and downscaling routine was used to simulate dynamic urban land expansion at a 30-m resolution based on suitability criteria. Scenarios of future urban landcover change projections include variant solutions for the Shared Socioeconomic Pathway 5 (SSP5) and SSP 3 based on different population assumptions, different land use intensification assumptions, variable land zoning constraints, and iterative adjustments to correct for over allocation of urban expansion across decadal time periods from 2010 to 2100. This results in 320 raster products.

Land↗

Airborne surveys of USA urban areas at 121.5/243 MHz

In situ, aircraft flight measurements were made in 1976 and 1977 by NASA of the radio-frequency environment over USA urban areas within the emergency distress search and rescue frequency bands at 121.5 and 243.0 MHz. This paper analyzes test results reported previously for USA East Coast and Midwest flight surveys; presented also are test results obtained in May 1977 for the USA West Coast during the NASA, ASSESS-II, Space Shuttle/Spacelab simulation aircraft flights. The USA West Coast flight include data at 121.5/243 MHz during an extensive series of aircraft passes for the Los Angeles urban area. The USA East Coast/Midwest measurements show correlation with population count.

Taylor, R. E.↗

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Shepherd, J. Marshall↗

Comparison of Surface and Column Variations of CO2 Over Urban Areas for Future Active Remote CO2 Sensors

High resolution in-situ CO2 measurements were recorded onboard the NASA P-3B during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) Field Campaign, to investigate the ability of space-based observations to accurately assess near surface conditions related to air quality. This campaign includes, Washington DC/Baltimore, MD (July 2011), San Joaquin Valley, CA (January - February 2013), Houston, TX (September 2013), and Denver, CO (July-August 2014). Each of these campaigns consisted of missed approaches and approximately two hundred vertical soundings of CO2 within the lower troposphere (surface to about 5 km). In this study, surface (0 - 1 km) and column-averaged (0 - 3.5 km) CO2 mixing ratio values from the vertical soundings in the four geographically different urban areas are used to investigate the temporal and spatial variability of CO2 within the different urban atmospheric emission environments. Tracers such as CO, CH2O, NOx, and NMHCs are used to identify the source of CO2 variations in the urban sites. Additionally, we apply nominal CO2 column weighting functions for potential future active remote CO2 sensors operating in the 1.57-microns and 2.05-microns measurement regions to convert the in situ CO2 vertical mixing ratio profiles to variations in CO2 column optical depths, which is what the active remote sensors actually measure. Using statistics calculated from the optical depths at each urban site measured during the DISCOVER-AQ field campaign and for each nominal weighting function, we investigate the natural variability of CO2 columns in the lower troposphere; relate the CO2 column variability to the urban surface emissions; and show the measurement requirements for the future ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) in the continental U.S. urban areas.

Choi, Yonghoon↗

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and TRMM Satellite

The urban heat island (UHI) has become a widely acknowledged, observed, and researched phenomena because of its broad implications. It is estimated that by the year 2025, 80% of the world's population will live in cities (UNFP, 1999). The UHI has been documented in the literature to affect local and regional temperature distributions, wind patterns and air quality. The UHI can also impact the development of clouds and precipitation in and around cities. This paper will focus primarily on the UHI's impact on precipitation. In the past 30 years, several observational and climatological studies have theorized that the UHI can have a significant influence on mesoscale circulations and resulting precipitation (see Shepherd et al. 2002 for a thorough review). More recent studies have continued to validate and extend the findings from pre and post-METROMEX investigations. Shepherd et al. (2002) was one of the first (and possibly the first) attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Using a 15-month (spanning three years) analysis of mean rainfall rates, the cities of Atlanta, Montgomery, Dallas, Waco, and San Antonio were examined. Shepherd et al. (2002) found that the average percentage increase in mean rainfall rate in a hypothesized "downwind maximum impact area" over an "upwind control area" was 28.4% with a range of 14.6 to 51%. The typical distance of the downwind rainfall rate anomaly from the urban center was 30-60 km, consistent with earlier studies. This fact provides confidence that UHI-rainfall effects are real and detectable by TRMM satellite estimates.

Shepherd, J. Marshall↗

Investigations of an urban area and its locale using ERTS-1 data supported by U-photography

An urban area in central Pennsylvania and the surrounding locality were investigated separately at first by photointerpretation of ERTS-1 imagery and by computer processing of MSS tapes. Next the photointerpretation and processing were coordinated. The results of the cooperative effort of photointerpreters and computer processing analysts were much improved over independent efforts. It was found that single frames of U-2 photography could be projected onto printer output maps with little recognizable distortion in areas 10 to 25 cm square. In this way targets could be identified for use as training areas for computer processed signature identification. In addition, at any stage of category mapping, the level of success in correct classification could be assessed by this method. The results of the classification of the study area are discussed.

Weeden, H. A.↗

Determining Surface Roughness in Urban Areas Using Lidar Data

An automated procedure has been developed to derive relevant factors, which can increase the ability to produce objective, repeatable methods for determining aerodynamic surface roughness. Aerodynamic surface roughness is used for many applications, like atmospheric dispersive models and wind-damage models. For this technique, existing lidar data was used that was originally collected for terrain analysis, and demonstrated that surface roughness values can be automatically derived, and then subsequently utilized in disaster-management and homeland security models. The developed lidar-processing algorithm effectively distinguishes buildings from trees and characterizes their size, density, orientation, and spacing (see figure); all of these variables are parameters that are required to calculate the estimated surface roughness for a specified area. By using this algorithm, aerodynamic surface roughness values in urban areas can then be extracted automatically. The user can also adjust the algorithm for local conditions and lidar characteristics, like summer/winter vegetation and dense/sparse lidar point spacing. Additionally, the user can also survey variations in surface roughness that occurs due to wind direction; for example, during a hurricane, when wind direction can change dramatically, this variable can be extremely significant. In its current state, the algorithm calculates an estimated surface roughness for a square kilometer area; techniques using the lidar data to calculate the surface roughness for a point, whereby only roughness elements that are upstream from the point of interest are used and the wind direction is a vital concern, are being investigated. This technological advancement will improve the reliability and accuracy of models that use and incorporate surface roughness.

Holland, Donald↗

On Rainfall Modification by Major Urban Areas: Observations from Space-borne Rain Radar Aboard TRMM - Part 1

A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

Shepherd, J. Marshell↗

Urban Area Unmanned Aerial Systems Sensor Capabilities for Ensuring Ground Hazards Safety

Unmanned aerial systems (UASs) in urban areas can pose significant safety risks to dynamic ground objects (DGOs) such as people, pets, and bikes; especially for off-nominal emergency traverses and landings. This paper will examine a framework for evaluating the UAS safety benefits which can be achieved by classifying DGO hazards, modeling their behavior, and assigning collision costs. DGOs are assumed to be any ground objects which are either moving or capable of moving. Safety benefits will be assessed by analyzing metrics computed from UAS and DGO trajectories which take into account intent and uncertainties. This paper will establish the theoretical relationships mapping these trajectories and DGO classifications to safety levels. Sensor capabilities will be mapped to DGO trajectory uncertainties, so that safety can be directly estimated from the sensor specifications for a given UAS trajectory.

Bouyssounouse, Xavier↗

Analysis of urban area land cover using SEASAT Synthetic Aperture Radar data

Digitally processed SEASAT synthetic aperture raar (SAR) imagery of the Denver, Colorado urban area was examined to explore the potential of SAR data for mapping urban land cover and the compatability of SAR derived land cover classes with the United States Geological Survey classification system. The imagery is examined at three different scales to determine the effect of image enlargement on accuracy and level of detail extractable. At each scale the value of employing a simplistic preprocessing smoothing algorithm to improve image interpretation is addressed. A visual interpretation approach and an automated machine/visual approach are employed to evaluate the feasibility of producing a semiautomated land cover classification from SAR data. Confusion matrices of omission and commission errors are employed to define classification accuracies for each interpretation approach and image scale.

Henderson, F. M.↗