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At least 397 records · Page 22

Modeling the Urban Impact on Semiarid Surface Climate: A Case Study in Marrakech, Morocco

We combine Landsat and MODIS data in the Simple Biosphere Model to assess the impact of urbanization on surface climate in a semiarid city in North Africa. The model simulates highest temperatures in urban class, with spring average maximum temperature differences to other land cover classes ranging between 1.6 C and 6.0 C. During summer, these maximum temperature differences are smallest (0.5 C) with barelands and highest (8.3 C) with irrigated lawns. This excess heating is simulated above and beyond a seasonal temperature average of about 30 C during spring and 44 C during summer. On annual mean, a full urbanization scenario decreases the carbon fixation by 0.13 MtC and increases the daytime mean surface temperature by 1.3 C. This may boost the city energy consumption by 5.72%. Under a 'smart growth' scenario, whereby the city expands on barelands to cover 50% of the study region and all remaining barelands converted to orchards, the carbon fixation is enhanced by 0.04 MtC with a small daytime temperature increase of 0.2 C. Our results indicate that vegetation can mitigate the urban heating. The hydrological cycle indicates that highest ratio of surface runoff to precipitation (43.8%) occurs in urban areas, versus only 16.7 % for all cover types combined.

Lachir, Asia↗

Regional Impacts of Urbanization in the United States

We simulate the impact of impervious surface areas (ISA) on the U.S. local and regional climate. At a local scale, we find the urban area warmer than the surrounding vegetation in most cities, except in arid climate cities where urban temperature is cooler for much of the daytime. For all 9 regions studied, simulated results show that the growing season maximum surface temperature difference between urban and the dominant vegetation occurs around mid-day and is strongest in the northern regions. Regional temperature differences of 3.0 C, 3.4 C, and 3.9 C were simulated in the Northeast, Midwest, and Northwest, respectively. In these regions evaporative cooling, during the growing season, creates a stronger urban heat island (UHI). The UHI is less pronounced during winter when vegetation is dormant. Our results suggest that the ISA temperature is set by building material's characteristics and its departure from that of the surrounding vegetation is essentially driven by evaporative cooling. Except when rainfall is small, the highest surface runoff to precipitation ratios are simulated in most cities, especially when precipitation events occur as heavy downpours. In terms of photosynthesis, we provide a detailed distribution of maximum production in the U.S., a needed product for policy and urban planners.

Bounoua, Lahouari↗

A Method for Mapping Future Urbanization in the United States

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Bounoua, Lahouari↗

The connection between forest degradation and urban energy demand in sub-Saharan Africa: a characterization based on high-resolution remote sensing data

Charcoal is a key energy source for urban households in sub-Saharan Africa and charcoal production is the main cause of forest degradation across the region. We used multitemporal high-resolution remote sensing optical imagery to quantify the extent and intensity of forest degradation associated with charcoal production and its impact on forest carbon stocks for the main supplying area of an African capital. This analysis documents the advance of forest degradation and quantifies its aboveground biomass removals over a seven-year period, registering that, between 2013 and 2016, the average annual area under charcoal production was 103 sq.km and the annual aboveground biomass removals reached 1081 000 (SD = 2461) Mg. Kiln densities in the study area rose to 2 kilns-ha, with an average of 90.7 Mg ha^(−1) of extracted aboveground biomass. Charcoal production was responsible for the degradation of 55.5% of the mopane woodlands in the study area between 2013 and 2019. We estimated post-disturbance recovery times using an ecosystem model calibrated for the study area. The simulations showed that recovery times could require up to 150 years for current aboveground biomass extraction rates. The results of the remote sensing analysis and the simulations of the ecosystem model corroborate the unsustainability of the present patterns of charcoal production. The detailed characterization of the spatial and temporal patterns of charcoal production was combined with household survey information to quantify the impact of the urban energy demand of the Maputo urban area on forest carbon stocks. The analysis shows that Maputo charcoal demand was responsible for the annual degradation of up to 175.3 sq.km and that the contribution of the study area to this demand fluctuated between 75% and 33% over the study period. The extent, advance pace and distance from urban centers documented in this study support the idea that forest degradation from charcoal production cannot merely be considered a peri-urban process. The intensity of the aboveground biomass (AGB) removals and its contribution to forest carbon stocks changes is significant at the national and regional levels.

F Sedano↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

NASA is conducting investigations into Advanced Air Mobility (AAM) concepts, aircraft, and operations. One of the most challenging scenarios for AAM will be enabling safe routine access into densely populated urban centers. To address challenges in the urban environment, a moderately high-fidelity simulation capability is needed to investigate AAM flight operations over a regional area for the development and evaluation of autonomy technologies. This paper describes a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (10's-100's of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to accurately simulate all phases of flight. Glass cockpit displays have been developed for monitoring aircraft operation over a detailed simulated urban environment. Simulation models have been integrated to simulate air and ground-based sensors, such as radar and LIDAR. The commercial X-Plane software package is used as a rendering engine to mimic vision-based sensors (such as onboard and ground-based cameras) at various times of day and in various weather conditions over a relatively detailed graphical model of the city. The paper presents a detailed illustration of the simulation and software architecture used for traffic over this urban region. This system is enabling the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward aircraft flight test evaluation.

Keerthana Kannan↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

distributed sensing↗

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

Distributed sensing↗

Evaluating the Effects of Urban Expansion on Social and Environmental Vulnerability in Guatemala and Panama

Central America is one of the fastest urbanizing regions in the world, with the urban population expected to double by 2050. This growth is driving multiple societal issues, including infrastructure inequities, lack of accessible housing, and environmental degradation. This project partnered with NASA SERVIR, Sistema de la Integración Centroamericana (SICA), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), and Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPRENEDAC) to examine changes in urban extent and vulnerability in Guatemala City, Guatemala and Panama City, Panama. The team identified urban extent using Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 OLI-2 within Google Earth Engine’s LandTrendr algorithm. Next, they assessed urban vulnerability between formal and informal settlements by classifying different types of roof material using high-resolution Maxar Worldview 2 and 3 imagery and comparing it to socioeconomic and environmental risks. While both cities have expanded outward and become denser since 2000, Guatemala City has grown at a faster rate. The most vulnerable communities of both cities were located in the northwestern regions. These case studies can be used to inform similar methodologies in other Central American cities and help leaders identify the most vulnerable communities within their areas.

Aaron Whittemore↗

Impact of Anthropogenic Activity, Climate Change, and Urbanization on Wetland Habitat in the Platte River Basin​

The Platte River Basin (PRB) is a dynamic ecosystem where wetlands play a pivotal role as essential habitats for various flora and fauna, including local and migratory birds. It provides many crucial ecosystem services that benefit humans directly and indirectly. However, anthropogenic activity, climate change, and urbanization have resulted in decline in wildlife habitat, elevated flood risk, and wetland loss. To address this issue, NASA DEVELOP partnered with Audubon Great Plains (AGP) to address the vital habitats within urban areas to protect bird species, reduce flood hazards, and analyze the potential impact of future development on wetlands. We utilized remotely sensed data from Landsat 8 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR) to assess land use and land cover (LULC) change. Nighttime lights data from Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) as well as NASA Socioeconomic Data and Applications Center (SEDAC) population data were also used as inputs to simulate urban growth potential up to 2050 using the open-source FUTure Urban-Regional Environment Simulation (FUTURES) model. A broad scale analysis across 13 focal cities showed varied changes in land use patterns across the PRB, with the most notable being a decrease in agricultural land coverage and an increase in vegetation and grassland coverage. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under AGP’s Urban Woods and Prairies Initiative. The results for two proposed scenarios showed that at least 51 counties out of 81 in the PRB would experience growth by year 2050. The first scenario (all wetlands are protected) showed that there will be no loss of wetlands by 2050. However, the second scenario (no wetlands are protected) showed a decrease in wetland area and loss of habitat for bird conservation. The results will help AGP to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies in the future.​

Nancee Uniyal↗

A global urban heat island intensity dataset: Generation, comparison, and analysis

The urban heat island (UHI) effect, a phenomenon of local warming over urban areas, is the most well-known impact of urbanization on climate. Globally consistent estimates of the UHI intensity (UHII) are crucial for examining this phenomenon across time and space. However, publicly available UHII datasets are limited and have several constraints: (1) they are for clear-sky surface UHII, not all-sky surface UHII and canopy (air temperature) UHII; (2) the estimation methods often neglect anthropogenic disturbance, introducing uncertainties in the estimated UHII. To address these issues, this study proposes a new dynamic equal-area (DEA) method that can minimize the influence of various confounding factors on UHII estimates through a dynamic cyclic process. Utilizing the DEA method and leveraging various gridded temperature data, we develop a global-scale (>10,000 cities), long-term (over 20 years by month), and multi-faceted (clear-sky surface, all-sky surface, and canopy) UHII dataset. Further, based on these estimates, we provide a comprehensive analysis of the UHII and its trends in global cities. The UHII is found to be greater than zero in >80% of cities, with global annual average magnitudes around 1.0 °C (day) and 0.8 °C (night) for surface UHII, and close to 0.5 °C for canopy UHII. Furthermore, an interannual upward trend in UHII is observed in >60% of cities, with global annual average trends exceeding 0.1 °C/decade (day) and over 0.06 °C/decade (night) for surface UHII, and slightly surpassing 0.03 °C/decade for canopy UHII. Notably, there exists a positive correlation between the magnitude and trend of UHII, suggesting that cities with stronger UHII tend to experience faster growth in UHII. Additionally, discrepancies in UHII are found between different temperature data, stemming not only from distinctions in data types (surface or air temperature) but also from differences in data acquisition times (Terra or Aqua), weather conditions (clear-sky or all-sky), and processing methodologies (with or without gap filling). Overall, our proposed method, dataset, and analysis results have the potential to provide valuable insights for future urban climate studies. The UHII dataset is publicly available at https://doi.org/10.6084/m9.figshare.24821538.

54 ENVIRONMENTAL SCIENCES↗

Assessing Impacts of Environmental Perturbations on Urban Biogenic Carbon Exchange in the Chicago Region

Carbon dioxide (CO 2 ) quantification is critical for assessing city-level carbon emissions and sustainable urban development. While urban vegetation has the potential to provide environmental benefits, such as heat and carbon mitigation, the CO 2 exchange from biogenic sectors and its impact from the environmental perturbations are often overlooked. It is also challenging to simulate the plant functions in the complex urban terrain. This study presents a processed-based modeling approach to assess the biogenic carbon fluxes from the vegetated areas over the Chicago Metropolitan Area (CMA) using the Weather Research and Forecast—Urban Biogenic Carbon exchange model. We investigate the change of CO 2 sink power in CMA under heatwaves and irrigation. The results indicate that the vegetation plays a significant role in the city's carbon portfolio and the landscaping management has the potential to reduce carbon emissions significantly. Furthermore, based on the competing mechanisms in the biogenic carbon balance identified in this study, we develop a novel Environmental Benefit Score metrics framework to identify the vulnerability and mitigation measures associated with nature-based solutions (NbS) within CMA. By using the generalized portable framework and our science-policy confluence analysis presented in this study, global cities can maximize the effectiveness of NbS and accelerate carbon neutrality.

54 ENVIRONMENTAL SCIENCES↗

Nonlinear behavior of urban flood peaks in the U.S. Mid-Atlantic region

Urbanization, i.e., increasing urban development areas in a watershed, is well known as a major cause of increasing flood magnitudes. This study analyzes the observed flood peaks at 262 watersheds in the U.S. Mid-Atlantic region with varying levels of urban development and free from reservoir impacts. Our analysis reveals an interesting, V-shaped nonlinear behavior: flood peaks first decrease and then increase with increasing percentage of urban development area at the watershed scale (PDAW), with the shift occurring at a PDAW threshold of around 10%. Regression analyses suggest that the V-shaped pattern primarily results from complex interactions among climate conditions (e.g., storm-event rainfall) and landscape properties (e.g., elevation, distance to the coast). A neural network model was then developed to capture such interactions, satisfactorily reproducing the V-shaped pattern with an R-squared value of 0.58, RMSE of 6.72 mm/day, and NSE of 0.55. These findings highlight the need to account for nonlinear dynamics in flood prediction and management in the coastal environment.

flood peaks↗

Platte River Basin Water Resources II: Predicting Land Cover Change in the Platte River Basin to Select Wetland Protection Sites Vulnerable to Urban Encroachment

The Platte River Basin (PRB) represents a critical dynamic ecosystem where wetlands play a pivotal role as essential habitats for local and migratory birds, as well as various flora and fauna. It also provides many crucial ecosystem services that directly and indirectly benefit human welfare. However, it is threatened by anthropogenic activity, climate change, and urbanization. Our team partnered with Audubon Great Plains, the regional office of a national non-profit organization (NGO), to analyze the future potential development of the region and its potential impact on the wetlands. We utilized remotely sensed data, such as Landsat 8 Operational Land Imager (OLI) and Suomi National Polar Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), as well as NASA Socioeconomic Data and Application Center (SEDAC) data, to simulate urban growth potential up to 2050 using the open-source model FUTure Urban-Regional Environment Simulation (FUTURES) model. Our results for two proposed scenarios (all wetlands are protected, and no wetlands are protected) revealed that at least 56 counties out of 81 in the PRB would experience growth by the year 2050. The results for the first scenario show that there will be no loss of wetlands in the future. However, the results for the second scenario indicate a basin-wide reduction of 43.22 square kilometers (0.58%) in wetland areas, leading to a significant loss of bird habitat, critical for conservation. The results will help Audubon Great Plains' Urban Woods and Prairies Initiative to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies.

FUTURES↗

Winter Warming in North America Induced by Urbanization in China

Rapid urbanization in China in the past several decades has been shown to affect surface air temperature (SAT) locally, but its global impact is unclear. Using a global climate model, we have investigated the potential impact of urbanization in China on SAT at the global scale. The expansion of urban areas in China from 1985 to 2017 leads to winter surface air warming by as much as 0.8°C in North America (NA), largely caused by warm temperature advection due to global-scale atmospheric circulation changes. The East Asian jet stream moves northward in eastern and northeastern China where the expansion of urban areas has increased SAT and sensible heat flux, forcing change of the atmospheric stationary waves and so the structure of the jet streams.

54 ENVIRONMENTAL SCIENCES↗

Urban Versus Lake Impacts on Heat Stress and Its Disparities in a Shoreline City

Abstract Shoreline cities are influenced by both urban‐scale processes and land‐water interactions, with consequences on heat exposure and its disparities. Heat exposure studies over these cities have focused on air and skin temperature, even though moisture advection from water bodies can also modulate heat stress. Here, using an ensemble of model simulations covering Chicago, we find that Lake Michigan strongly reduces heat exposure (2.75°C reduction in maximum average air temperature in Chicago) and heat stress (maximum average wet bulb globe temperature reduced by 0.86°C) during the day, while urbanization enhances them at night (2.75 and 1.57°C increases in minimum average air and wet bulb globe temperature, respectively). We also demonstrate that urban and lake impacts on temperature (particularly skin temperature), including their extremes, and lake‐to‐land gradients, are stronger than the corresponding impacts on heat stress, partly due to humidity‐related feedback. Likewise, environmental disparities across community areas in Chicago seen for skin temperature are much higher (1.29°C increase for maximum average values per $10,000 higher median income per capita) than disparities in air temperature (0.50°C increase) and wet bulb globe temperature (0.23°C increase). The results call for consistent use of physiologically relevant heat exposure metrics to accurately capture the public health implications of urbanization.

54 ENVIRONMENTAL SCIENCES↗

Significant Rural Contributions to Severe Coastal Urban Flooding Through Flow Connectivity

Coastal cities are increasingly threatened by hurricane-induced compound flooding. However, the relative contributions of rainfall-surge interactions and other flood drivers, such as runoff from surrounding rural and local impervious areas, in shaping urban flooding remain unclear. Here, we use a multi-scale Earth system modeling framework to disentangle the contributions of diverse flooding drivers. The results show that urban flooding is primarily affected by topographic factors (low elevation, flat slopes, and localized flow constrictions), rather than increased runoff from their impervious surfaces. Importantly, runoff from rural areas contributes more to severely flooded urban areas with inundation depth exceeding 1.7 m than local runoff. Although rainfall–surge interactions and sea-level rise exacerbate inundation along the coastline, over 90% of the compounding effects are absorbed by wetlands. By resolving flooding processes across scales and components, this study emphasizes the role of runoff from surrounding rural areas in shaping zones of severe urban flooding.

58 GEOSCIENCES↗

Impacts of climate change, population growth, and power sector decarbonization on urban building energy use

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Deciphering the sensitivity of urban canopy air temperature to anthropogenic heat flux with a forcing-feedback framework

Abstract The sensitivity of urban canopy air temperature ( T a ) to anthropogenic heat flux ( Q A H ) is known to vary with space and time, but the key factors controlling such spatiotemporal variabilities remain elusive. To quantify the contributions of different physical processes to the magnitude and variability of Δ T a / Δ Q A H (where Δ represents a change), we develop a forcing-feedback framework based on the energy budget of air within the urban canopy layer and apply it to diagnosing Δ T a / Δ Q A H simulated by the Community Land Model Urban over the contiguous United States (CONUS). In summer, the median Δ T a / Δ Q A H is around 0.01 K W m − 2 − 1 over the CONUS. Besides the direct effect of Q A H on T a , there are important feedbacks through changes in the surface temperature, the atmosphere–canopy air heat conductance ( c a ), and the surface–canopy air heat conductance. The positive and negative feedbacks nearly cancel each other out and Δ T a / Δ Q A H is mostly controlled by the direct effect in summer. In winter, Δ T a / Δ Q A H becomes stronger, with the median value increased by about 20% due to weakened negative feedback associated with c a . The spatial and temporal (both seasonal and diurnal) variability of Δ T a / Δ Q A H as well as the nonlinear response of Δ T a to Δ Q A H are strongly related to the variability of c a , highlighting the importance of correctly parameterizing convective heat transfer in urban canopy models.

54 ENVIRONMENTAL SCIENCES↗