National Urban Database and Access Portal Tool

Ching, Jason; Brown, Michael J.; Burian, Steven J.; Chen, Fei; Cionco, Ron; Hanna, Adel; Hultgren, Torrin; McPherson, Timothy N.; Sailor, David J.; Taha, Haider; Williams, David J.

doi:10.1175/2009bams2675.1

Cited by 151 publications

(104 citation statements)

References 12 publications

(11 reference statements)

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“…A crosswalk between the two datasets was carried out [22] to increase the number of useful LULC categories. NUDAPT/WUDAPT datasets [31] were not used directly in this effort …”

Section: Model Inputmentioning

confidence: 99%

“…A crosswalk between the two datasets was carried out [22] to increase the number of useful LULC categories. NUDAPT/WUDAPT datasets [31] were not used directly in this effort because of their limited spatial coverage, but as templates, along with local climate zones [37] to map morphological characteristics onto LULC classes.…”

Section: Model Inputmentioning

confidence: 99%

“…Pursuant to the California Assembly Bill AB 296, which requires the quantification of the UHI, the California Environmental Protection Agency urbanized WRF modules such as UCM [27,28] and BEP / BEM [29], along with various boundary-layer schemes including Bougeault and Lacarrere [30] and NUDAPT/WUDAPT urban morphometric data [31]. Based on statewide data availability and model-performance evaluation results (see below), an approach by Taha [9,10,[18][19][20] was adopted, as discussed briefly in the following sections.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

Taha¹

2017

Climate

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Abstract:To further evaluate the factors influencing public heat and air-quality health, a characterization of how urban areas affect the thermal environment, particularly in terms of the air temperature, is necessary. To assist public health agencies in ranking urban areas in terms of heat stress and developing mitigation plans or allocating various resources, this study characterized urban heat in California and quantified an urban heat island index (UHII) at the census-tract level (~1 km 2 ). Multi-scale atmospheric modeling was carried out and a practical UHII definition was developed. The UHII was diagnosed with different metrics and its spatial patterns were characterized for small, large, urban-climate archipelago, inland, and coastal areas. It was found that within each region, wide ranges of urban heat and UHII exist. At the lower end of the scale (in smaller urban areas), the UHII reaches up to 20 degree-hours per day (DH/day; • C.hr/day), whereas at the higher end (in larger areas), it reaches up to 125 DH/day or greater. The average largest temperature difference (urban heat island) within each region ranges from 0.5-1.0 • C in smaller areas to up to 5 • C or more at the higher end, such as in urban-climate archipelagos. Furthermore, urban heat is exacerbated during warmer weather and that, in turn, can worsen the health impacts of heat events presently and in the future, for which it is expected that both the frequency and duration of heat waves will increase.

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“…A crosswalk between the two datasets was carried out [22] to increase the number of useful LULC categories. NUDAPT/WUDAPT datasets [31] were not used directly in this effort …”

Section: Model Inputmentioning

confidence: 99%

Section: Model Inputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

Taha¹

2017

Climate

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“…The reference substation service areas, which are polygonal in shape, were drawn up by an electric power system expert. Economic and population information derived from the 2010 LandScan dataset citeop7 is incorporated, along with the daytime/nighttime population information from [8,20].…”

Section: Assessment Methodologymentioning

confidence: 99%

Accuracy of Service Area Estimation Methods Used for Critical Infrastructure Recovery

Pala

Wilson

Bent

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Electric power, water, natural gas and other utilities are served to consumers via functional sources such as electric power substations, pumps and pipes. Understanding the impact of service outages is vital to decision making in response and recovery efforts. Often, data pertaining to the source-sink relationships between the service points and consumers is sensitive or proprietary, and is, therefore, unavailable to external entities. As a result, during emergencies, decision makers often rely on estimates of service areas produced by various methods. This paper, which focuses on electric power, assesses the accuracy of four methods for estimating power substation service areas, namely the standard and weighted versions of Thiessen polygon and cellular automata approaches. Substation locations and their power outputs are used as inputs to the service area calculation methods. Reference data is used to evaluate the accuracy in approximating a power distribution network in a mid-sized U.S. city. Service area estimation methods are surveyed and their performance is evaluated empirically. The results indicate that the performance of the approaches depends on the type of analysis employed. When the desired analysis includes aggregate economic or population predictions, the weighted version of the cellular automata approach has the best performance. However, when the desired analysis involves facility-specific predictions, the weighted Thiessen polygon approach tends to perform the best.

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“…In cities the sources of particles and hazardous gasses are packed on small areas together with a dense population exposed to health risks due to poor air quality (Ching, 2007). In order to assess the exposure of urban population and predict the dispersion of particles and hazardous emissions, air flow and its interaction with the urban landscape has to be modeled.…”

Section: Introductionmentioning

confidence: 99%

Extracting Urban Morphology for Atmospheric Modeling From Multispectral and Sar Satellite Imagery

Wittke

Karila

Puttonen

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission I, WG I/8KEY WORDS: Urban Morphology, Land Cover Classification, Digital Surface Model, Sentinel-2, TanDEM-X, Satellite Remote Sensing ABSTRACT:This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91%. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas.Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

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National Urban Database and Access Portal Tool

Cited by 151 publications

References 12 publications

Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

Characterization of Urban Heat and Exacerbation: Development of a Heat Island Index for California

Accuracy of Service Area Estimation Methods Used for Critical Infrastructure Recovery

Extracting Urban Morphology for Atmospheric Modeling From Multispectral and Sar Satellite Imagery

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