Search NASA⌕ Search

SEARCH · Search NASA

Results for “urban environments”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Estimating and Evaluating Roughness Length and Displacement Height in Heterogeneous Urban Environments

The roughness length (z 0 ) and displacement height (z d ) are essential surface-layer parameters in numerical models (e.g., weather, climate, wall-modeled LES, etc.). This work evaluates the consistency of z 0 and z d estimates from morphometric and anemometric methods using data from two eddy-covariance flux towers (AmeriFlux US-INg and US-INc) in Indianapolis, IN. Results show inconsistencies in estimated z 0 and z d values depending on the chosen method. The two evaluated anemometric methods estimate non-physical values of z d when compared to roughness elements surrounding both towers. Additionally, predictions of mean wind speed using surface-layer similarity theory with morphometric estimates exhibit a bias during near-neutral and stable conditions relative to observations. The overestimation of mean wind speed by surface layer similarity theory is consistent with previous observational and modeling studies in urban areas, suggesting that the application of similarity theories to urban environments may have limitations. Differentiation of vegetation from built structures appears to impact morphometric z 0 and z d estimates, particularly where vegetation is abundant; however, it has little impact on correcting biases in the similarity theory. Specifically, we find that existing similarity theories using morphometric estimates underestimate integral velocity and length scales, and the degree of underestimation depends on the stability conditions. Accounting for the degree of anisotropy in surface-layer turbulence helps reduce the biases between similarity theories and observations during unstable conditions, but not in near-neutral cases. Future work is needed to identify the cause of such biases for near-neutral conditions.

Aerodynamic roughness length↗
NASA NTRS2024

An On-Board Off-Board Framework for Online Replanning: Applied to UAVs in Urban Environments

Autonomous systems are being used in a multitude of areas at an increasing rate and require a high level of adaptivity and intelligence to operate safely, especially under faulty conditions. This paper introduces a novel genetic algorithm tailored for UAV trajectory replanning, with an improved execution time via search space reduction based on the operating conditions of the UAV and its remaining mission. A unique characteristic of the replanning agent is its fast-start and adaptive properties, pre-seeding candidates with partial solutions and dynamically tuning elitism, crossover, and mutation rates in correspondence to the average fitness and diversity of the population. A population restart mechanism and early stopping mechanism are evaluated as well to assess their effect on solution quality and runtime. Previous work on genetic algorithms for UAV replanning were conducted with short trajectories in a small state space. Our UAV operates in a 56,000 square meter simulated urban environment, with static obstacles and a total of 53 possible waypoints. The agent increases the safety and reliability of UAV autonomy when operating under faulty conditions and when replanning is required.

Machine Learning↗
NASA NTRSDate not supplied

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗
NASA NTRSDate not supplied

Multipath Mitigation via Clustering for Position Estimation Refinement in Urban Environments

Position estimation using global navigation satellite systems (GNSS) suffers from poor accuracy within urban canyons due to significant signal disruption caused by tall buildings. This issue can be attributed to the GNSS signals reflecting off buildings resulting in severe multipath reflections which degrade the receiver's performance. In this paper, we introduce an innovative approach to filter GNSS satellite measurements to improve the accuracy of the estimated position by leveraging a clustering algorithm. This approach utilizes a predictive GNSS availability service to filter out non-line-of-sight measurements. Then, a subset of line-of-sight satellite measurement combinations are evaluated using a clustering algorithm. When combined, results show these techniques can reduce the mean horizontal error measured in an urban canyon by nearly an order of magnitude, from ~ 18 meters to ~ 2 meters when using a single point positioning solver.

GPS↗
NASA NTRS1974

Remote sensing utility in a disaster struck urban environment

A project to determine the ways in which remote sensing can contribute to solutions of urban public health problems in time of natural disaster is discussed. The objectives of the project are to determine and describe remote sensing standard operating procedures for public health assistance during disaster relief operations which will aid the agencies and organizations involved in disaster intervention. Proposed tests to determine the validity of the remote sensing system are reported.

Rush, M.↗
DOE OSTI2025

Extreme heat vulnerability of manufactured housing in arid urban environments

This article explores the role of land cover in relation to housing type and tenure in shaping exposure to extreme urban heat, focusing on residents of mobile and manufactured housing (MH). We hypothesize that MH residents will experience greater exposure to extreme heat than those living in other housing types due to lower levels of proximate vegetation. This hypothesis is based on the unique property relations and tenure regimes that characterize MH, which may disincentivize investments in planting and maintaining trees and vegetation in arid environments. To test this hypothesis, we compare the amount of vegetation on properties across housing types, within-type tenure arrangements and between three urbanized areas in Arizona with different levels of exposure to extreme heat. To conduct this comparison, we combine multispectral land cover data for 1.7 million parcels with tax assessor data and building footprints to measure land cover at a high resolution. We find that MH units have significantly less vegetation than single-family residential properties, and that MH units in MH parks have less vegetation than those on individual lots. We conclude that municipalities should promote (e.g. through incentives or other policy interventions) the planting of more vegetation around MH units where there is a risk of extreme heat exposure. Future research can expand this analysis with a closer examination of how municipal ordinances and policies affect land cover by housing type and tenure.

heat↗
NASA NTRS2000

Urban Dynamics: Analyzing Land Use Change in Urban Environments

In FY99, the Earth Resource Observation System (EROS) staff at Ames continued managing the U.S. Geological Survey's (USGS) Urban Dynamics Research program, which has mapping and analysis activities at five USGS mapping centers. Historic land use reconstruction work continued while activities in geographic analysis and modeling were expanded. Retrospective geographic information system (GIS) development - the spatial reconstruction of a region's urban land-use history - focused on the Detroit River Corridor, California's Central Valley, and the city of Sioux Falls, South Dakota.

Acevedo, William↗
NASA NTRSDate not supplied

Sim to Flight: Evaluating Flight Path Management Automation in High Density Urban Environments

Combined simulation and flight testing enable the study of single- and multi-aircraft performance of onboard automation systems for dynamic flight path management (FPM). The National Aeronautics and Space Administration (NASA) is investigating system performance and functional capabilities of such automation for immersion into complex, high density, future operations such as Urban Air Mobility (UAM). This paper provides an overview of a series of interdependent sim-to-flight research activities involving large-scale batch simulations, human-in-the-loop verification, and flight-test validation of a research prototype FPM automation system. Together, they significantly contributed to a functional assessment of FPM automation functionality in a live-virtual-constructive (LVC) operating environment characterized by two live aircraft and hundreds of virtual aircraft interacting in a modeled complex urban airspace. Initial simulation and flight test results, future work, and conclusions are presented.

Advanced Air Mobility↗
NASA NTRSDate not supplied

A Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

The emergence and development of advanced technologies and vehicle types has created a growing demand for the introduction of new forms of flight operations. These new and increasingly complex operational paradigms such as Advanced and Urban Air Mobility (AAM/UAM) present regulatory authorities and the aviation community with several design and implementation challenges – particularly for highly autonomous vehicles. An overarching and daunting task is finding methods to integrate these emerging operations without compromising safety or disrupting traditional airspace operations. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. This paper focus on the development and testing of a prognostic service aimed at estimating the quality of Global Navigation Satellite System (GNSS) performance for an autonomous aircraft in complex environments. The intent of this function is to proactively reduce a flight operations risk of exposure to states that may induce poor or unacceptable navigation system performance by factoring in estimates of GNSS quality into pre-flight and/or in-flight route planning. Methodologies for producing quality estimates are specified and results are provided for selected simulation and flight test cases.

GNSS↗
DOE OSTI2025

Detection of local-scale changes in greenhouse gas emissions in urban environments using micrometeorological methods and comparison to a high-resolution inventory

We used the Monin–Obukhov similarity theory (MOST) flux-variance relationship to estimate greenhouse gas (GHG) fluxes from high-precision mole fraction measurements at 3 instrumented urban communication towers over several years, demonstrating the ability of this method to detect and quantify changes in emissions. Depending on data availability, we used carbon dioxide (CO 2 ) and carbon monoxide (CO) measurements and/or tracer ratios to estimate fluxes at 1 urban site (Site 3) and 1 suburban site (Site 7) in Indianapolis, IN, USA, and 1 urban site (COM) in Los Angeles, CA, USA. We also compared the estimated fluxes of CO 2 from fossil fuel sources (CO 2 ff) at Sites 3 and 7 and the total CO 2 fluxes at Site 3 to 20 m, hourly resolution subdomains of the high-resolution CO 2 emissions inventory, Hestia, for the year 2020, introducing a new way to evaluate emissions inventories at small spatial and temporal scales. Using the flux-variance relationship, we detected and quantified abrupt decreases in CO and CO 2 fluxes at Site 3 and COM in April 2020, coinciding with the stay-at-home order due to COVID-19 pandemic, as well as abrupt decreases in CO and CO 2 fluxes at Site 3 in July 2018 coinciding with a highway closure next to the site. The Hestia emissions inventory detected a decrease in emissions in April 2020 at Sites 3 and 7, but this decrease differed in magnitude from those detected in the atmospheric estimates. Seasonal trends in emissions are similar between Hestia and the atmospheric estimates at Site 7. We use differences in seasonal and spatial trends between the flux estimation methods to identify potential sources of uncertainty in both the atmospheric and inventory methods. The results from this study show that the flux-variance estimation method is a useful tool to monitor local-scale emissions and evaluate high-resolution emissions inventories.

Carbon dioxide↗
NASA NTRS2024

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗
NASA NTRS1998

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

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/ sq m 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. Published by Elsevier Science Ltd.

Quattrochi, Dale A.↗
NASA NTRSDate not supplied

Obtaining Public Opinion about sUAS Activity in an Urban Environment

The Unmanned Aircraft Systems (UAS) Traffic Management (UTM) research project has been developing and testing concept ideas for enabling small UAS (sUAS) operations in low altitude airspace (ground to 400 feet). To do this, a series of flight test demonstrations were organized over five years at seven test sites. Technology Capability Level-4 (TCL4), the most complex flight tests, were conducted in Texas, USA, during August 2019. This testing resulted in over 400 data collection flights using eight live rotorcraft, with nine flight crews flying pre-planned scenarios in the urban downtown and waterfront areas of Corpus Christi, Texas. Test scenarios were designed to include a variety of elements, including live and simulated vehicles, and personnel in many different roles, including flight crews and mission personnel. One group of people who did not have a role in the flight tests but will be affected by UAS operations as they become more ubiquitous, are the general public. What do the public think about sUAS operations in urban areas? In order to obtain a reference point that noted the public's view of the operations in the TCL4 demonstration, a short survey was developed and offered to members of the public who wished to comment on the sUAS activities they saw in their city during two weeks in August, 2019.Forty five people completed the online public opinion survey. Participants volunteered to take it, creating a self-selected sample. The survey included eleven questions that asked participants about their level of comfort and concerns with UAS activity; their knowledge of UAS operations; and, whether a traffic management system like UTM would increase their confidence in urban UAS activity. The general public in Corpus Christi showed a good level of knowledge of sUAS regulations, with almost half of their responses to the knowledge portion of the survey being correct. They expressed a moderate level of concern (x = 4.7 out of 7) at urban sUAS activity and, of those who cited a concern, the majority reported this was about privacy (54%), which are all responses in line with those reported in earlier research on public opinion. Views on UTM were mixed, with respondents indicating they thought the introduction of UTM will improve safety somewhat (5.2 out of 7) but it will also increase their concern a little (4.6 out of 7). This would indicate there needs to be more information and educational material about the UTM concept made available to the public with the aim to reduce public concerns about the system.

Caterina Grossi↗
NASA NTRSDate not supplied

Obtaining Public Opinion About sUAS Activity in an Urban Environment

The Unmanned Aircraft Systems (UAS) Traffic Management (UTM) research project has been developing and testing concept ideas for enabling small UAS (sUAS) operations in low altitude airspace (ground to 400 feet). To do this, a series of flight test demonstrations were organized over five years at seven test sites. Technology Capability Level-4 (TCL4), the most complex flight tests, were conducted in Texas, USA, during August 2019. This testing resulted in over 400 data collection flights using eight live rotorcraft, with nine flight crews flying pre-planned scenarios in the urban downtown and waterfront areas of Corpus Christi, Texas. Test scenarios were designed to include a variety of elements, including live and simulated vehicles, and personnel in many different roles, including flight crews and mission personnel. One group of people who did not have a role in the flight tests but will be affected by UAS operations as they become more ubiquitous, are the general public. What do the public think about sUAS operations in urban areas? In order to obtain a reference point that noted the public’s view of the operations in the TCL4 demonstration, a short survey was developed and offered to members of the public who wished to comment on the sUAS activities they saw in their city during two weeks in August, 2019. Forty five people completed the online public opinion survey. Participants volunteered to take it, creating a self-selected sample. The survey included eleven questions that asked participants about their level of comfort and concerns with UAS activity; their knowledge of UAS operations; and, whether a traffic management system like UTM would increase their confidence in urban UAS activity. The general public in Corpus Christi showed a good level of knowledge of sUAS regulations, with almost half of their responses to the knowledge portion of the survey being correct. They expressed a moderate level of concern (x = 4.7 out of 7) at urban sUAS activity and, of those who cited a concern, the majority reported this was about privacy (54%), which are all responses in line with those reported in earlier research on public opinion. Views on UTM were mixed, with respondents indicating they thought the introduction of UTM will improve safety somewhat (5.2 out of 7) but it will also increase their concern a little (4.6 out of 7). This would indicate there needs to be more information and educational material about the UTM concept made available to the public with the aim to reduce public concerns about the system.

UTM↗
NASA NTRS2011

Autonomous Landing and Ingress of Micro-Air-Vehicles in Urban Environments Based on Monocular Vision

Unmanned micro air vehicles (MAVs) will play an important role in future reconnaissance and search and rescue applications. In order to conduct persistent surveillance and to conserve energy, MAVs need the ability to land, and they need the ability to enter (ingress) buildings and other structures to conduct reconnaissance. To be safe and practical under a wide range of environmental conditions, landing and ingress maneuvers must be autonomous, using real-time, onboard sensor feedback. To address these key behaviors, we present a novel method for vision-based autonomous MAV landing and ingress using a single camera for two urban scenarios: landing on an elevated surface, representative of a rooftop, and ingress through a rectangular opening, representative of a door or window. Real-world scenarios will not include special navigation markers, so we rely on tracking arbitrary scene features; however, we do currently exploit planarity of the scene. Our vision system uses a planar homography decomposition to detect navigation targets and to produce approach waypoints as inputs to the vehicle control algorithm. Scene perception, planning, and control run onboard in real-time; at present we obtain aircraft position knowledge from an external motion capture system, but we expect to replace this in the near future with a fully self-contained, onboard, vision-aided state estimation algorithm. We demonstrate autonomous vision-based landing and ingress target detection with two different quadrotor MAV platforms. To our knowledge, this is the first demonstration of onboard, vision-based autonomous landing and ingress algorithms that do not use special purpose scene markers to identify the destination.

micro air vehicles (MAVs)↗
NASA NTRSDate not supplied

Enhancing In-Flight Structural Health Monitoring of Vertical Lift Vehicles Operating in an Urban Environment

In-situ airframe sensors have long been considered a potential solution for structural health monitoring that could change the design, certification, operation and maintenance paradigms of flight vehicles. In this approach, large networks of sensors covering the entire, or most of, an airframe throughout its operational lifetime would support real-time decisions on airworthiness and obviate the need to overbuild components or perform multiple cycles of structural qualification testing and inspections. This concept would go beyond the current practice of placing select sensors in strategic locations or relying on such sensors only during airframe qualification flights and inspections. For vehicles in the emerging urban air mobility space, reducing weight associated with overbuilds and shortening down-time associated with inspections are critical for improving safety and affordability. In practice, the wide-scale use of in-situ sensors as primary assurance for structural health has not been demonstrated to be feasible or the best solution. A sensor integration testbed was developed as a platform to evaluate the potential of multiple sensor types to enable decision making on airworthiness. We report on the initial runs of this testbed with multiple sensors attached to a common test article. Metal foil strain gauges, eddy current, fiber optic, guided wave (acoustic emission and ultrasonic)and carbon nanotube roving sensors were affixed to the test article. Baseline as well as post damage initiation and fatiguing data are presented and discussed. Despite the relative simplicity of the test article, the interpretation of the as-captured test data was generally not conclusive or did not have wide enough coverage. This result emphasizes the challenges and current limitations both in testing and the practical broad application of embedded sensors as the determinative elements in critical decision making on wide-scale structural health.

Vertical Lift Vehicles↗