Geology topics

Peter Christian Ibsen

Publications and source records attributed to Peter Christian Ibsen.

At least 19 recordsLinked to original sources

USGS2026

The influence of tree canopy cover data choices on urban ecosystem accounting

Because urban landscapes are heterogeneous, the methods and spatial resolution used to depict the land surface greatly influence the representation of urban features. Land cover products such as tree canopy cover (TCC) are particularly sensitive to the methodology and resolution used in their creation. Differences in TCC mapping have implications on the outcomes of ecosystem service (ES) models, including those underlying natural capital accounting. Here, we quantify the sensitivity of physical rainfall interception and local climate regulation ES models for 189 U.S. cities to TCC inputs from four TCC products: a) National Land Cover Database (NLCD), b) Enhanced NLCD TCC, c) aggregated city-specific composite, and d) global tree canopy height dataset. We find both city-level and aggregate differences in TCC estimates, from a 38% decrease to a 3% increase relative to an aggregated high-resolution product. These differences result in up to 3% overestimations and 27% underestimation of rainfall interception and 2–56% underestimation of local climate regulation ES. City size, population, and greenness in addition to climatic variation drove differences between TCC products, and this variation requires users to carefully consider the choice of input data for any planned analysis. Though high-resolution data can offer greater nuance and accuracy, more limited spatiotemporal availability can hinder their usefulness for long-term monitoring applications such as natural capital accounting. The differences found in this study provide valuable insights for making informed decisions on data inputs for use in urban ecosystem research and for contextualizing model outcomes.

Contiguous United States↗

USGS2026

Moving toward a more human-oriented analysis of urban heat: Examining differences of heat exposure intensity at busy commuting locations

Examining urban thermal environments has become a critical area of research spanning epidemiology, urban planning, and ecology. While traditional metrics like air temperature ( T air ) and satellite-derived surface temperature dominate urban heat studies, these measures often fail to reflect how people actually experience thermal exposure intensity. More human-oriented metrics, such as mean radiant temperature (MRT), and the wet bulb globe temperature (WBGT), better capture this lived experience, particularly at locations where people are likely to encounter outdoor heat, such as bus stops. Human demographics further complicate heat exposure, as access to cooling resources like trees and greenspaces can vary by neighborhood income. Our study addresses these complications by collecting thermal data across 60 commuting locations in Denver, Colorado in the summer. We evaluate (1) the extent to which more human-oriented metrics capture thermal exposure compared to T air and LST, and (2) how heat exposure varies by neighborhood income levels. We observed that bus stops in low-income neighborhoods had an MRT increase 2.8 °C compared wealthier neighborhoods, and that income-driven differences in MRT and WBGT strongly depended on bus stop aspect. After accounting for solar orientation, differences in MRT increased to as much as 6.3 °C at north-facing stops. Our results suggest tree canopy shade explains some observed heat exposure patterns, with south facing bus stops seeing a MRT and WBGT decrease of 0.42 °C and 0.11 °C from a percent increase in tree canopy. Interestingly, depending on bus stop aspect, nearby buildings can increase MRT and WBGT (facing east), or decrease MRT and WBGT (facing south) If planners aim to address this issue, consideration of bus stops, and land covers configuration may help.

Colorado↗

USGS2026

Density dependence and habitat selection affect overwintering abundance of monarch butterflies at regional and site scales in California

The monarch butterfly ( Danaus plexippus ) is a species of iconic cultural interest. Thanks to annual overwintering monarch counts at hundreds of locations in coastal California, we are able to track fluctuations with high temporal and spatial resolution. Between 1997 and 2024, monarch populations at overwintering sites in the western United States experienced severe dips, at times (2018–2020, 2023–2024) giving the appearance of a population collapse. From 2018 to present, the Pismo State Beach Overwintering Monarch Grove has conducted multiple counts during overwintering and geolocated counts of individual monarch clusters to specific trees within the site. This study determined how annual monarch population variability is influenced by both climate and prior year population density at the state, region, and overwintering-site scale. Furthermore, through a machine-learning process, we investigated how overwintering site configuration and structure drive monarch winter space-use dynamics within the Pismo Beach site. Our approach found monarchs exhibit a preference for specific overwintering sites in California, and that 64% of annual variability of counts across sites can be explained by climate and density dependence, with density dependence explaining 50% of total variability. Within the site we found very little regional climate effect, but individual trees, tree size, distance to boundary, and the amount of shade were all strong indicators of monarch presence. Additionally, only 11 out of 320 trees at the Pismo Beach site accounted for 83.6% of all counts over 6 years, highlighting how monarchs use specific trees and how tree structure may create preferred microclimates for clustering.

California↗

USGS2026

The surface is not superficial: Utilizing hyper-local thermal photogrammetry for pedestrian thermal comfort inquiry

The scale and magnitude of urban heating are often assessed using Satellite-Derived Land Surface Temperature (SD-LST). Yet, discrepancies in spatial resolution limit SD-LST’s ability to reflect pedestrian thermal experience, potentially leading to ineffective mitigation strategies. Hyper-local measurements of urban heat, defined as surface temperatures (T S ) at the scale of pedestrian activity (e.g., bus stops or street segments), may provide more accurate insights into thermal comfort. This study compares hyper-local ~0.01 m resolution T S collected via consumer-grade Forward-Looking Infrared (FLIR) thermography with resampled 30 m resolution SD-LST from Landsat 8 and 9 images to evaluate their utility in predicting thermal comfort indices across 60 bus stops in Denver, Colorado. During the summer of 2023, 270 FLIR measurements were collected over 19 dates, with a four-day subset ( n = 33) coinciding with Landsat imagery. FLIR T S averaged 25.12 ± 5.39 °C, while SD-LST averaged 35.90 ± 12.56 °C, a significant 10.77 °C difference (95% CI: 6.81–14.73; p < 0.001). FLIR T S strongly correlated with biometeorological metrics such as air temperature and mean radiant temperature (r > 0.8; p < 0.001), while SD-LST correlations were weak (r < 0.3). Linear mixed-effects models using FLIR T S explained 50–66% of the variance in thermal comfort indices and met ISO 7726 standards. Each 1 °C increase in FLIR TS predicted a 0.75 °C rise in mean radiant temperature. These results highlight hyper-local thermography as a reliable, low-cost tool for urban heat resilience planning.

Colorado↗

USGS2026

Weathering the ride: Associations of heat, smoke, precipitation, and ozone with bus ridership in Colorado

Weather and climate variability increasingly shape urban travel behavior, yet the short-term temporal dynamics and contextual modifiers of weather-transit relationships remain poorly understood. We analyzed system-wide hourly bus ridership in the Denver metropolitan area from June 2022 through September 2023 using fixed-effects negative binomial distributed lag nonlinear models with lags up to 24 h. Nonlinear exposure-response and lag-response functions were specified for hourly Universal Thermal Climate Index (UTCI) and precipitation, with additional indicators for daily ozone exceedance and wildfire smoke. Models adjust for hour-of-day, day-of-week, and month-year fixed effects, with standard errors clustered by day. Stratified analyses assess heterogeneity by time period, season, fare policy, and shelter availability, with interaction evaluated using Wald tests. Cold thermal stress was associated with the largest, most persistent reductions in ridership, with cumulative declines of −15.7% (95% CI: −26.0%, −4.0%) over 0-24 h. Precipitation was associated with sharp but transient reductions concentrated within 3-6 h (−8.4% to −9.8%), with little evidence of longer-term displacement. Heat associations were weaker and context-dependent, with modest short-run increases, but net same-day declines. Associations varied by time of day and season, were attenuated during the free-fare period, and differed by shelter availability. In contrast, ozone exceedance and wildfire smoke exhibited limited and inconsistent associations, with measurable reductions primarily during morning commute during heavier smoke conditions. Overall, transit ridership is more strongly associated with short-term weather exposure, than with ambient air quality. Fare policy and stop-level infrastructure modify these associations, highlighting actionable strategies to enhance transit resilience under increasing climate variability.

Colorado↗

USGS2025

Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado

Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting at bus stops. Evaluating the contribution of traffic emissions at bus stops can provide important information on risks experienced by these populations. We measured PM 2.5 constituents at eight bus stops and one background reference site in Denver, in the summer of 2023. Source profiles, including gasoline emissions from traffic, were estimated using Positive Matrix Factorization (PMF) analysis of PM 2.5 constituents collected at a Chemical Speciation Network site in our study region. The contributions of the different sources at each bus stop were estimated by regressing the vector of species concentrations at each site (dependent variable) on the source-profile matrix from the PMF analysis (independent variables). Traffic-related emissions (~2.5–6.6 μg/m 3 ) and secondary organics (~3–5 μg/m 3 ) contributed to PM 2.5 at the bus stops in our dataset. The highest traffic-related emissions-derived PM 2.5 concentrations were observed at bus stops near local sources: a gas station and a car wash. The contribution of traffic-related emissions was lower at the background site (~1 μg/m 3 ).

Colorado↗

USGS2025

Urban trees and cooling: A review of the recent literature (2018 to 2024)

Urban trees mitigate extreme heat through shading and evapotranspiration, but cooling effectiveness varies with tree traits, spatial configurations, and climate. This systematic mapping review synthesizes findings from 115 studies (2018 to 2024) using RepOrting standards for Systematic Evidence Syntheses (ROSES) protocols. Studies were categorized based on geographic location, climate zone, and heat metric (e.g., land surface temperature or air temperature), highlighting a geographic skew toward North America and Asia and underrepresentation of arid and tropical zones. Findings show that urban trees consistently outperform other vegetation types in cooling, particularly in hotter, drier climates when water is available. Dense, tall canopies provide broad-scale cooling, while mixed plantings with shrubs or grass enhance local effects. However, conflicting conclusions arise from using land surface versus air temperature, as these metrics respond differently to tree canopy. Key knowledge gaps include the role of native versus non-native species in arid climates, the effect of urban morphology on cooling, and tree performance during extreme heat. Most studies remain small-scale and limited in generalizability, emphasizing the continued need for city-specific knowledge. This review highlights urban trees as vital for heat mitigation and the importance of harmonizing research objectives and methods to inform planning and practice effectively.

Arboriculture and Urban Forestry↗

USGS2025

A nationwide evaluation of crowd-sourced ambient temperature data

Growing concerns about heat in urban areas paired with the sparsity of weather stations have resulted in individuals drawing on data from citizen science sensor networks to fill in data gaps. The PurpleAir are the most widely-used low-cost air quality sensors in the contiguous United States with 14,777 deployed between 1 Jan 2017 and 20 July 2021. Although the air quality data from PurpleAir sensors have been widely studied, less attention has been paid to reported temperature. We compare temperature metrics reported by PurpleAir sensors with a gridded temperature product, the North American Land Data Assimilation System (NLDAS)-2, which although not a gold-standard measure of temperature, is widely used in epidemiologic research. We evaluate the lag between indoor and outdoor PurpleAir temperatures. We report associations of the difference between outdoor PurpleAir temperatures and NLDAS-2 temperatures, an indicator of degradation, and the duration of sensor operation. Finally, based on the temperature range recorded by the outdoor PurpleAir sensors vis.a.vis NLDAS-2 temperatures, we provide a list of 271 (2.5%) sensors potentially misclassified as outdoor and likely located indoors. We observed that outdoor PurpleAir sensors agreed well with NLDAS-2 (R2 > 0.82). This association broke down under warm conditions (daily average NLDAS ≥ 21.1oC). Landcover and climate zone were significant modifiers of the association between PurpleAir and NLDAS-2 temperature metrics with the poorest PurpleAir- NLDAS-2 agreement in urban areas. Indoor PurpleAir temperatures lagged hourly NLDAS temperatures by two hours across almost all climate zones. The mean difference in hourly PurpleAir and NLDAS-2 temperatures increased by 0.57oC for every operational year, suggesting that careful attention must be paid to degradation. Overall, we find for use in epidemiological studies, that the PurpleAir sensor data is a reliable metric of daytime mean air temperature, but researchers should be aware of its limitations when examining extreme heat, or when aggregating sensor data across multiple years.

Frontiers of Environmental Science and Engineering↗

USGS2025

An enhanced national-scale urban tree canopy cover dataset for the United States

Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R 2 ) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R 2 of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.

conterminous United States↗

USGS2025

Land-use and socioeconomic time-series reveal legacy of redlining on present-day gentrification within a growing United States city

Home Owners’ Loan Corporation (HOLC) maps illustrated patterns of segregation in United States cites in the 1930s. As the causes and drivers of demographic and land-use segregation vary over years, these maps provide an important spatial lens in determining how patterns of segregation spatially and temporally developed during the past century. Using a high-resolution land-use time series (1937-2018) of Denver, Colorado, USA, in conjunction with 80 years of U.S. Census data, we found divergent land-use and demographics patterns across HOLC categories were both pre-existent to the establishment of HOLC mapping and continued to develop over time. Over this period, areas deemed “declining” or “hazardous” had more diverse land use compared to “desirable” areas. “Desirable” areas were dominated by one land-use type (single-family residential), while single-family residential diminished in prominence in the “declining/hazardous” areas. This divergence became more established decades after HOLC mapping, with impact to racial metrics and low-income households. We found changes in these demographic patterns also occurred between 2000 and 2019, highlighting how processes like gentrification can develop from both rapid demographic and land-use changes. This study demonstrates how the legacy of urban segregation develops over decades and can simultaneously persist in some neighborhoods while providing openings for fast-paced gentrification in others.

Colorado↗

USGS2025

High-resolution multi-pollutant mapping in Denver, Colorado

Characterizing traffic-related air pollutants (TRAPs), which significantly impact health, and greenhouse gases (GHGs) can be challenging in urban environments. Mobile monitoring has the potential to capture the spatial distribution of these pollutants. We present results from a campaign using the Denver Mobile Monitoring Laboratory (DMML) in the summer of 2023 when we measured ultrafine particles (UFPs), black carbon (BC), ozone (O 3 ), methane (CH 4 ) , and carbon dioxide (CO 2 ) concentrations in Denver, CO. Despite our campaign being brief, we obtained several interesting results. We observed elevated UFP and BC concentrations on major roads. In contrast, O 3 concentrations were higher on neighborhood streets and roads and in the industrial neighborhood of Commerce City. We consistently observed elevated CH 4 concentrations (>2.5 ppm) on highway I-70, suggesting the presence of a previously unknown major source of CH 4 . The CH 4 concentrations measured in our campaign did not align with those from an overlapping aerial campaign, suggesting that mobile monitoring is crucial to capture important, potentially intermittent CH 4 hotspots in cities. We evaluated if trees mitigated pollution concentrations, as planting trees is a key policy initiative of the city of Denver. We observed significant negative associations between tree canopy coverage and UFPs, BC, and CH 4 , and a positive association with O 3 when using linear mixed-effects regression models. Our work highlights the importance of investigating the role of tree canopy coverage to mitigate TRAPs.

Colorado↗

USGS2025

Monitoring visitor activity and informal trail disturbance in Yosemite Valley meadows to assess temporal changes in use and impacts

Montane meadows provide vital habitat that supports ecosystems, regulate hydrological processes, and offer valuable recreational opportunities. Meadows account for 3 % of Yosemite National Park's area, including Yosemite Valley, and are particularly susceptible to human impacts such as formation of informal trails. We collected observational data on visitor activity and quantified social trail disturbance to compare with resource monitoring datasets and through similar parameters to Walden-Schreiner and Leung (2013) who studied visitor use and behavior in three Yosemite Valley meadows in 2011. We documented change in number of visitors per hour and primary activity pursued. We also compared trends of meadow disturbance (informal trail length and disturbed area) from the early 2000s - 2023. Informal trail length at El Capitan Meadow decreased from 2004 to 2018, followed by recent increases. Disturbed area for Cooks A, Sentinel A, Slaughterhouse B, Stoneman A, and Stoneman B sub-meadows increased from 2006 to 2023. Between 2011 and 2023, the proportion of those engaged in active versus stationary pursuits showed that visitors engaged in more active pursuits in two of three meadows. Moreover, there were >3.5 times more visitors per hour in Cooks, El Capitan, and Leidig meadows in 2023 compared to 2011, yet, most visitors utilized designated trails. Meadow locational context was linked to activity preference and types of impacts. Management strategies, such as fencing and signage have been effective at minimizing impacts in several meadows. Parsing nuances of informal trail use and drivers of disturbance for various meadows is crucial for informed park management decisions and actions.

California↗

USGS2025

Hot stops, cool looks: Aesthetic solutions for thermal comfort at transit stops

Increased urban heat intensifies thermal discomfort, particularly in critical public spaces such as transit stops. This study investigated the predictors of transit users' thermal perceptions in Denver, Colorado—a semi-arid city. Sixty bus stops spanning a gradient of land cover compositions were selected for study. Micrometeorological data, including thermal comfort indices, were collected alongside survey responses from 77 users at 31 unique stops. Survey responses captured thermal sensation votes (TSV) and thermal comfort votes (TCV) as well as aesthetic preference votes (APV) of bus stop structure. Ordinal forest analysis revealed that for both TSV and TCV, aesthetic preferences and thermal comfort indices were the most influential predictors of transit user thermal perception. Multiple ordered logistic regression further demonstrated that, for TSV, higher APV was associated with lower odds of rating a thermal environment as hot (OR = 0.664, p < 0.002) while increased Physiological Equivalent Temperature (PET) raised these odds (OR = 1.101, p < 0.006). An interaction analysis demonstrated that APV significantly moderated the effect of PET on TCV (interaction OR = 1.040, p < 0.041), suggesting that aesthetic preferences are significantly correlated with an alleviation of thermal discomfort under high heat stress. Bivariate analyses further indicated that bus stops with greater tree canopy cover (OR = 1.032, p < 0.025) and higher visible vegetation view factors (OR = 10.350, p < 0.022) were more likely to be rated as aesthetically pleasing. These findings underscore the importance of aesthetic preferences in transit stop planning for urban heat resiliency.

Colorado↗

USGS2024

Sequoia groves of Yosemite: Visitor use and impacts monitoring

Despite being long-lived and massive, giant sequoias ( Sequoiadendron giganteum (Lindl.) J. Bucholz) are susceptible to erosion given their relatively shallow root structure. Human-caused soil compaction and vegetation loss through social trails are primary drivers of erosion in giant sequoia groves, particularly for trees that are near formal trails and access roads. We develop a method to observe and quantify the near-tree impacts from park visitors and to relate the overall amount of use with ground cover impact parameters to assess whether the desired conditions of each grove are being met for the park to maintain a spectrum of recreational opportunities. We collected data on visitation, ground cover, soil compaction, and social trailing using a combination of targeted surveys and observations at the three giant sequoia groves in Yosemite National Park. The Mariposa Grove receives the most visitation, and use levels among groves were consistent with relative size and facilities available. Selected parameters for ground cover data were analyzed by comparing values within undisturbed versus trampling-disturbed subplots at both 0–2 m and 2–8 m. Exposed soil cover and compaction were generally higher in anthropogenically disturbed subplots versus undisturbed subplots, and vegetation cover was reduced in some disturbed subplots. Each grove had one surveyed tree where average soil compaction was ≥2.2 kg/cm 2 , which may limit root growth and impact seedling regeneration. Each of the three groves had some trees with social trail presence, yet less than 7% of mature trees within any grove were impacted by social trails, and most social trails were rated as having low impairment. Coupling soil compaction measurements and estimates of trampling-disturbed areas with mapping of social trail conditions within groves provides a general assessment of visitor-associated impacts to sequoia groves and can facilitate a relatively rapid way to track hotspot (i.e., increasingly impacted) trees over time.

California↗

USGS2024

Intra-urban variations in land surface phenology in a semi-arid environment

Urban vegetation is growing in importance as cities use 'green infrastructure' to mitigate the impacts of climate change, reduce extreme heat, and improve human health and comfort. However, due to the heterogeneity of city landscapes, urban vegetation experiences a diverse range of environmental conditions, potentially leading to differences in growing season timing and length within cities. Here, we investigate physical drivers of urban land surface phenology and timing within a semi-arid city (Denver, CO, USA) using four years (2018–2021) of remotely sensed vegetation indices, modelled air temperature, and land cover datasets. Within the metropolitan region study area, satellite-based vegetation index measurements indicate that growing season length is variable on sub-neighborhood spatial scales. This variability is largely due to differences in the timing of fall senescence, as opposed to early season growth. Areas with substantial fractions of irrigated land cover tend to remain greener for longer, while unirrigated and cooler areas are correlated with an earlier end to the growing season (up to ∼two months shorter). These findings complement those from non-arid cities where surface and air temperature are the dominant environmental control on phenological timing. Results here indicate the importance of soil moisture for phenology in semi-arid regions and suggest unique semi-arid urban growing season dynamics and temperature-vegetation feedbacks. These interactions have implications for water, heat, and vegetation management strategies to maximize ecosystem services in water-limited environments.

Colorado↗

USGS2024

Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)

The decline of the iconic monarch butterfly ( Danaus plexippus ) in North America has motivated research on the impacts of land use and land cover (LULC) change and climate variability on monarch habitat and population dynamics. We investigated spring and fall trends in LULC, milkweed and nectar resources over a 20-year period, and ~ 30 years of climate variables in Mexico and Texas, U.S. This region supports spring breeding, and spring and fall migration during the annual life cycle of the monarch. We estimated a − 2.9% decline in milkweed in Texas, but little to no change in Mexico. Fall and spring nectar resources declined < 1% in both study extents. Vegetation greenness increased in the fall and spring in Mexico while the other climate variables did not change in both Mexico and Texas. Monarch habitat in Mexico and Texas appears relatively more intact than in the midwestern, agricultural landscapes of the U.S. Given the relatively modest observed changes in nectar and milkweed, the relatively stable climate conditions, and increased vegetation greenness in Mexico, it seems unlikely that habitat loss (quantity or quality) in Mexico and Texas has caused large declines in population size or survival during migration.

Scientific Reports↗

USGS2024

Urban tree cover provides consistent mitigation of extreme heat in arid but not humid cities

Urban land cover types influence the urban microclimates. However, recent work indicates the magnitude of land cover's microclimate influence is affected by aridity. Moreover, this variation in cooling and warming potentials of urban land cover types can substantially alter the exposure of urban areas to extreme heat. Our goal is to understand both the relative influences of urban land cover on local air temperature, as well as how these influences vary during periods of extreme heat. To do so we apply predictive machine learning models to an extensive in-situ microclimate and 1 m land cover dataset across eight U.S. cities spanning a wide aridity gradient during typical and extreme heat conditions. We demonstrate how the cooling influence of tree canopy and the warming influence of buildings on microclimate linearly scales with regional aridity, while the influence of turf and impervious surfaces does not. These interactions lead tree canopy to consistently mitigate to air temperature increases during periods extreme heat in arid cities, while the influence of urban tree canopy on extreme heat in humid regions is varied, suggesting that mitigation is possible, but tree canopy can also aggravate extreme heat or have no significant effect.

Sustainable Cities and Society↗

USGS2023

Limited role of absolute humidity in intraurban heat variability

Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks.

Journal of Applied Meteorology and Climatology↗