Modelling the diurnal variations of urban heat islands with multi-source satellite data

Examination of the diurnal variations in surface urban heat islands (UHIs) has been hindered by incompatible spatial and temporal resolutions of satellite data. In this study, a diurnal temperature cycle genetic algorithm (DTC-GA) approach was used to generate the hourly 1 km land-surface temperature (LST) by integrating multi-source satellite data. Diurnal variations of the UHI in ‘ideal’ weather conditions in the city of Beijing were examined. Results show that the DTC-GA approach was applicable for generating the hourly 1 km LSTs. In the summer diurnal cycle, the city experienced a weak UHI effect in the early morning and a significant UHI effect from morning to night. In the diurnal cycles of the other seasons, the city showed transitions between a significant UHI effect and weak UHI or urban heat sink effects. In all diurnal cycles, daytime UHIs varied significantly but night-time UHIs were stable. Heating/cooling rates, surface energy balance, and local land use and land cover contributed to the diurnal variations in UHI. Partial analysis shows that diurnal temperature range had the most significant influence on UHI, while strong negative correlations were found between UHI signature and urban and rural differences in the normalized difference vegetation index, albedo, and normalized difference water index. Different contributions of surface characteristics suggest that various strategies should be used to mitigate the UHI effect in different seasons.     

Comparing surface- and canopy-layer urban heat islands over Beijing using MODIS data

The canopy-layer urban heat island (CLHI) and the surface-layer urban heat island (SLHI) of Beijing, the capital city of China, were compared on the spatial scale of a city and the temporal scale of a year in this study. A differential temperature vegetation index (DTVX) method was improved by suggesting a new parameterization scheme for estimating daytime air temperature (T_a); a binary linear regression equation was developed for estimating night-time T_a from Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (T_s) and vegetation indices data during 2009–2010. Validations using weather station observations show that the spatially distributed T_a can be obtained with an accuracy of approximately 2 K. Comparisons between the CLHI and the SLHI indicate that the CLHI agrees well with the SLHI during night-time, but they have a greater difference during daytime either in heat island intensity or in spatial distribution pattern. The SLHI?CLHI intensity difference during daytime has a noticeable seasonal variation, which is small and negative in cold seasons, but large and positive in warm seasons, whereas that at night-time has no significant seasonal variations. The difference in the evapotranspiration cooling effects between urban and rural areas may be the predominant factor that drives the SLHI?CLHI difference.     

Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures

The term urban heat island describes the phenomenon of altered temperatures in urban areas compared to their rural hinterlands. A surface urban heat island encompasses the patterns of land surface temperatures in urban areas. The classical indicator to describe a surface urban heat island is the difference between urban and rural surface temperatures. However, several other indicators for this purpose have been suggested in the literature. In this study, we compared the eleven different indicators for quantifying surface urban heat islands that were most frequently used in recent publications on remote sensing-based urban heat island assessments. The dataset used here consists of 263 European cities with monthly mean temperatures from MODIS data products for July 2002, January 2003 and July 2003. We found that (i) the indicators individually reveal diurnal and seasonal patterns but show rather low correlations over time, and (ii) for single points in time, the different indicators show only weak correlations, although they are supposed to quantify the same phenomenon. Differentiating cities according to thermal climate zones increased the relationships between the indicators. Thus, we can identify temporal aspects and indicator selection as important factors determining the estimation of urban heat islands. We conclude that research should take into account the differences and instabilities of the indicators chosen for quantifying surface urban heat islands and should use several indicators in parallel for describing the surface urban heat island of a city.     

Mapping micro-urban heat islands using NOAA/AVHRR images and CORINE Land Cover: an application to coastal cities of Greece

Land Surface Temperature (LST) is a significant parameter for identifying micro-climatic changes, their spatial distribution and intensities in relation to the urban environment. In this study, LST is estimated using thermal infrared data as acquired by the Advanced Very High Resolution Radiometer (AVHRR) instrument onboard the National Oceanic and Atmospheric Administration (NOAA) satellite and by using a split window algorithm that is adjusted to account for the region of Greece. For the assignment of the surface emissivity, a new methodology based on the Coordination of Information on the Environment (CORINE) Land Cover database for Greece is used. The algorithm is applied to a night-time series of NOAA/AVHRR images of Greece in order to produce surface temperature maps of an enhanced spatial resolution of 250?m for the cities of Thessaloniki, Patra, Volos and Iraklion, which are the most significant harbour cities of Greece. Results indicate the presence of urban heat islands (UHIs) in each case study, with highest temperatures detected along the coastal zone of the harbour cities resulting from denser urban fabric and road network as well as intense human activity.     

Remote-sensing image-based analysis of the patterns of urban heat islands in rapidly urbanizing Jinan,China

According to the UN Population Reference Bureau, 1.4 billion more people will have settled in urban areas by 2030. One of the key environmental effects of rapid urbanization is the urban heat island (UHI) effect. Understanding the mechanism of surface UHIs associated with land-use/land-cover (LULC) change patterns is important for improving the ecology and sustainability of cities. In this article, time series Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) data were used to extract LULC data and land surface temperature (LST) data for the city of Jinan, China, from 1987 to 2011, a period during which the city experienced rapid urbanization. With the aid of a geographical information system (GIS) and remote sensing (RS) approach, the changes in this urban area’s LULC were explored, and the impact of these changes on the spatiotemporal patterns and underlying driving forces of the surface UHI effect were further quantitatively characterized. The results show that significant changes in land use and land cover occurred over the study period, with loss of farmland, forest, and shrub vegetation to urban use, leading to spatial growth of impervious surfaces. Consequently, the land surface characteristics and spatiotemporal patterns of the UHI have changed drastically. According to the seasonal and inter-annual variations in intensity of UHIs, mean differences in UHI intensity between city centre, peri-urban, and nearby rural areas were stronger during summer and spring and weaker during winter and autumn. Spatially, there were significant LST gradients from the city centre to surrounding rural areas. The city centre exhibited higher LSTs and remarkable variation in LSTs, while the surrounding rural areas exhibited lower LSTs and lower variation in LSTs. Moreover, the analysis of LSTs and indices showed that great differences of temperature even existed in a LULC type except for variations between different LULC types. In addition, a local-level analysis revealed that the intensity of the UHI effect is proportional to the size of the urban area, the population density, and the frequent occurrence of certain activities.     

Quantifying urban growth in 10 post-Soviet cities using Landsat data and machine learning

ABSTRACT

Urbanization is one of the most irreversible anthropogenic forms of land use. Unplanned and rapid urban growth can result in environmental degradation, sprawl, and unsustainable production and consumption practices. The unique challenges facing the post-Soviet countries throughout the transition period highlight the critical need for a quantitative assessment of urban dynamics. Total of 32 Level-1 precision terrain corrected (L1T) Landsat scenes with 30 m resolution and auxiliary population and economic data were utilized to quantify the urban expansion dynamics in 10 cities across nine post-Soviet republics. Land cover was classified by using Support Vector Machine (SVM) learning algorithm with overall accuracies ranging from 87% to 97% for 29 classification maps over three time steps. The initial time step was the year 1989 ± 2, the middle time step was the year 2000 ± 2, and the final time step was the year 2015 ± 2. The results demonstrated several spatial and temporal urban expansion patterns across the post-Soviet region. The urban land area in several cities increased significantly over the study period. The average annual urban expansion rate was 1.6 ± 0.7 % per year for 10 cities over the study period and the average area of land converted to new urban environment was 227 ± 224 km² with a corresponding average per cent increase of 54.5 ± 26.7%. Furthermore, the results demonstrated significant decrease in overall population densities across the 10 cities with an average decrease of ?26.9 ± 14.8% over the study period. The urban expansion rates considerably outpaced the urban population growth rates in all 10 cities during the last quarter of a century, indicating more expansive urban growth patterns.     

Mitigating urban heat islands: A method to identify potential wind corridor for cooling and ventilation

In summer, the urban heat island effect causes unbearable warmth in the cities of Taiwan. This study maps out ventilation paths that are expected to draw in breezes from suburban areas and the sea to mitigate the urban heat island effect. Wind corridors are estimated based on the concept that wind moves along paths of low urban roughness, as defined by the frontal area index (FAI) and the least cost path (LCP) methodology followed in this study. The primary wind corridor was proposed with a main function of identifying wind that minimizes net daytime heating through a redistribution of the total surface heat flux. Land use that affects urban temperature is discussed by indicating the areas of potential rises and drops in air temperature in order to describe the temperature influences in both windward and leeward areas. The horizontal resolution of the calculation unit was a hundred meters, which is called an urban block scale in this study. At that resolution, detailed analyses can be discussed in a detailed plan scheme. A slightly more sophisticated CFD model confirms the more simplistic GIS-based mode, and thus, these results have the potential to guide urban wind corridor planning efforts. The land use map of potential temperature influences is superimposed with the current wind corridors to determine the exact areas in which to execute the mitigation strategies. Four sites are recommended for urban surface improvement according to their land uses, respectively. Furthermore, a potential cooling route on the east side of the study area was suggested for the FAI reduction strategy.     

Monitoring of urban heat island effect in Beijing combining ASTER and TM data

This paper focuses on the monitoring of the urban heat island (UHI) effect with temporal and spatial variation, combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Thematic Mapper (TM) data. Our study area is located in the central urban area of Beijing, which mainly refers to the areas within the fifth ring road. For detecting UHI changes over the years 2002–2006, three ASTER images in the summers of 2003, 2004 and 2006 and two TM datasets in the summers of 2002 and 2005 were collected. For monitoring UHI changes with the seasons, three ASTER images and one TM image in 2004 in winter, spring, summer and autumn, respectively, were employed. To calculate the urban heat island intensity, the land surface temperatures were retrieved iteratively for ASTER data and using a generalized single-channel method for the TM image. Four separated regions located in four directions outside the fifth ring road were selected as representing rural comparative regions. Their averaged land surface temperature was regarded as the rural comparative temperature. The UHI intensity was computed by the difference between the pixel urban land surface temperature in the urban area and the comparative temperature in the rural area. Detection of the UHI effect over 2002 to 2006 indicated that most of the areas with high UHI effect were the industrial land use regions and the areas having a high density of buildings, roads, transportations and residents; and the areas without UHI effect were located around the regions with large areas of grassland, trees and water bodies. Our results also showed that the UHI effect was not proportional to urbanization over time. Statistical UHI data during 20 July to 20 September in 2003–2008 also support this point. The monitoring of the UHI effect over seasons (winter, spring, summer and autumn) showed that the urban area of Beijing city had a high UHI effect except in winter, when the urban area of Beijing was in an urban heat sink; the UHI effect increased in spring, summer and autumn.     

Estimation of storage heat flux in an urban area using ASTER data

The urban heat island phenomenon occurs as a result of the mixed effects of anthropogenic heat discharge, increased use of artificial impervious surface materials, and decreased vegetation cover. These factors modify the heat balance at the land surface and eventually raise the atmospheric temperature. It is important to quantify the surface heat balance in order to estimate the contributions of these factors. The present authors propose the use of storage heat flux to represent the heat flux between the land surface and the inside of the canopy for the heat balance analysis based on satellite remote sensing data. Surface heat fluxes were estimated around the city of Nagoya, Japan using Terra ASTER data and meteorological data. Seasonal and day-night differences in heat balance were compared using ASTER data acquired in the daytime on July 10, 2000, and January 2, 2004 and in the nighttime on September 26, 2003. In the central business and commercial districts, the storage heat flux was higher than those in the surrounding residential areas. In particular, in winter, the storage heat flux in the central urban area was 240 to 290 W m^− 2, which was much larger than the storage heat fluxes in residential areas, which ranged from 180 to 220 W m^− 2. Moreover, the negative storage heat flux in the central urban area was greater at night. This tendency implies that the urban surface stores heat during the daytime and discharges it at night. Extremely large negative storage heat flux occurred primarily in the industrial areas for both daytime and nighttime as a result of the enormous energy consumption by factories.     

Mapping bottom depth and albedo in coastal waters of the South China Sea islands and reefs using Landsat TM and ETM+ data

Optical models for the retrieval of shallow water bottom depth and albedo using multispectral data usually require in situ water depth data to tune the model parameters. In the South China Sea (SCS), however, such in situ data are often lacking or obsolete (perhaps from half a century ago) for most coastal waters around its islands and reefs. Here, we combine multispectral data collected by MODIS and Landsat to estimate bottom depth and albedo for four coral reef regions in the SCS, with results partially validated by some scarce in situ data. The waters in these remote regions are oligotrophic whose optical properties can be well derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements when the waters are optically deep. The MODIS-derived optical properties are used to estimate the water column attenuation to the Landsat measurements over shallow waters, thus eliminating the requirement of model tuning using field measured water depths. The model is applied to four Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images covering Pratas Atoll, Woody Island, Scarborough Shoal, and North Danger Reefs. The retrieved bathymetry around Pratas Atoll and North Danger Reefs are validated with some in situ data between 1 and 25 m. The relative difference and root mean square difference between the two measurements were 17% and 1.6 m, for Pratas Atoll and 11% and 1.1 m for North Danger Reefs, respectively. These results suggest that the approach developed here may be extended to other shallow, clear waters in the SCS.     

Satellite-derived parameters for biological modelling in coastal waters: Illustration over the eastern continental shelf of the Bay of Biscay

In biological modelling of the coastal phytoplankton dynamics, the light attenuation coefficient is often expressed as a function of the concentrations of chlorophyll and mineral suspended particulate matter (SPM). In order to estimate the relationship between these parameters over the continental shelf of the northern Bay of Biscay, a set of in situ data has been gathered for the period 1998-2003 when SeaWiFS imagery is available. These data comprise surface measurements of the concentrations of total SPM, chlorophyll, and irradiance profiles from which is derived the attenuation coefficient of the photosynthetically available radiation, K_PAR. The performance of the IFREMER look-up table used to retrieve the chlorophyll concentration from the SeaWiFS radiance is evaluated on this new set of data. The quality of the estimated chlorophyll concentration is assessed from a comparison of the variograms of the in situ and satellite-derived chlorophyll concentrations. Once the chlorophyll concentration is determined, the non living SPM, which is defined as the SPM not related to the dead or alive endogenous phytoplankton, is estimated from the radiance at 555 nm by inverting a semi-analytic model. This method provides realistic estimations of concentrations of chlorophyll and SPM over the continental shelf all over the year. Finally, a relationship, based on non living SPM and chlorophyll, is proposed to estimate K_PAR on the continental shelf of the Bay of Biscay. The same formula is applied to non living SPM and chlorophyll concentrations, observed in situ or derived from SeaWiFS radiance.     

Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China

Urbanization is taking place at an unprecedented rate around the world, particularly in China in the past few decades. One of the key impacts of rapid urbanization on the environment is the effect of urban heat island (UHI). Understanding the effects of landscape pattern on UHI is crucial for improving the ecology and sustainability of cities. This study investigated how landscape composition and configuration would affect UHI in the Shanghai metropolitan region of China, based on the analysis of land surface temperature (LST) in relation to normalized difference vegetation index (NDVI), vegetation fraction (Fv), and percent impervious surface area (ISA). Two Landsat ETM+ images acquired on March 13 and July 2, 2001 were used to estimate LST, Fv, and percent ISA. Landscape metrics were calculated from a high spatial resolution (2.5 × 2.5 m) land-cover/land-use map. Our results have showed that, although there are significant variations in LST at a given fraction of vegetation or impervious surface on a per-pixel basis, NDVI, Fv, and percent ISA are all good predictors of LST on the regional scale. There is a strong negative linear relationship between LST and positive NDVI over the region. Similar but stronger negative linear relationship exists between LST and Fv. Urban vegetation could mitigate the surface UHI better in summer than in early spring. A strong positive relationship exists between mean LST and percent ISA. The residential land is the biggest contributor to UHI, followed by industrial land. Although industrial land has the highest LST, it has limited contribution to the overall surface UHI due to its small spatial extend in Shanghai. Among the residential land-uses, areas with low- to-middle-rise buildings and low vegetation cover have much high temperatures than areas with high-rise buildings or areas with high vegetation cover. A strong correlation between the mean LST and landscape metrics indicates that urban landscape configuration also influences the surface UHI. These findings are helpful for understanding urban ecology as well as land use planning to minimize the potential environmental impacts of urbanization.     

The influence of socioeconomic and topographic factors on nocturnal urban heat islands: a case study in Shenzhen,China

Earlier studies on urban heat islands (UHIs) focused mostly on the phenomenon during the daytime, when temperature peaks could usually be observed. However, for people living and working in tropical and subtropical cities, night-time air temperatures are also important. Several studies have focused primarily on the impact of biophysical and meteorological factors on nocturnal land surface temperatures (LSTs). Less attention has been paid to study of the influence of socioeconomic and topographic factors on nocturnal UHIs within a city. In this study, the integration of remote sensing (RS), geographic information system (GIS) and landscape ecology methods was used to investigate the relationships between nocturnal UHIs and socioeconomic or topographic factors based on a case study of Shenzhen, China. Nocturnal Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and daytime Landsat Thematic Mapper (TM) images were used to derive and analyse night- and daytime LSTs, respectively. Land-use data were generated by onscreen digitizing, and an abundance of impervious surfaces was produced through a normalized spectral mixture analysis (NSMA) method with TM data. Socioeconomic variables were derived from the China 2000 census data. A 30 m digital elevation model (DEM) was used to calculate elevation and slope grids. The relationships between nocturnal UHIs and socioeconomic or topographic factors were analysed using traditional regression analysis. The results show that the nocturnal and daytime LST patterns in different land-use areas were significantly different. Nocturnal LSTs were closely related to socioeconomic and topographic factors. An increase of 5 K on nocturnal LST of sub-districts was associated with an increase of 66.0% on their impervious surface abundance, 39 810 people per km², 1000 Yuan per month on housing rent, 9.5 km per km² on road density or a decline of 217.5 m on elevation and 17.0° on slope.     

Underwater bottom topography in coastal areas from TerraSAR-X data

In this article, wave refraction and shoaling in coastal areas were investigated and used to derive the bathymetry. With its high spatial resolution, which can achieve up to 1 m in SpotLight mode, and its low cut-off wavelength, the TerraSAR-X satellite provides images that are particularly suitable for the observation of wave behaviour in transient and shallow waters. By computing the two-dimensional (2D) spectra, shoaling waves were tracked from the open sea to the shoreline. The observed wave refraction and shoaling were compared with wave refraction laws and first-order wave theory (Airy theory). The retrieved bathymetry was compared against depth data from other sources such as ETOPO1, the US Coastal Relief Model and sea charts from the British Admiralty. A further aim of this article was the investigation of breaking waves showing up as near-shore image patterns. A theory is presented of how to derive the height of breaking waves by use of this pattern. Synthetic aperture radar (SAR) images with azimuth as well as range travelling waves were investigated. As test sites, we chose the entrance of Port Phillip near Melbourne (Australia) and the Duck Research Pier in North Carolina (USA).     

Monitoring urban population and energy utilization patterns from satellite Data

Urban population trends in China and energy utilization patterns in the United States have been assessed from LANDSAT and Defense Meteorological Satellite Program (DMSP) images. Regression models developed from population (P) data and urban area (A) measurements on LANDSAT images are of the form P = αA^b and provide insights into the success of Chinese urban planning policies for cities with populations of 500,000 to 2,000,000 people. Studies of the relationships between population, urban area, and electric-energy utilization patterns have been conducted from DMSP images of the United States. Microdensitometer profiles of illuminated cities recorded on nighttime (visual band) images are used in combination with the map boundaries of the built-up areas to create unique three-dimensional representations of the urban centers. The volumes of these three-dimensional figures may be computed and plotted with respect to population and/or energy utilization data to model regional patterns of use. Improvements in the quality of sensor data should increase the potential for monitoring urban energy demands and populations.     

Analysis of freshwater flux climatology over the Indian Ocean using the HOAPS data

Estimation of freshwater flux over a certain region is very difficult, as it needs both accurate evaporation and precipitation rates over the study area. Over the Indian Ocean (IO), the precipitation estimates are totally lacking or unknown due to the lack of in-situ measurements. In the present study, we examine the climatology and the annual cycle of the freshwater flux over the IO using the newly available Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data (HOAPS). This data set has been derived from passive microwave and infrared satellite data utilising the data from the Special Sensor Microwave/Imager (SSM/I) and the Advanced Very High Resolution Radiometer (AVHRR). We have compared the freshwater flux estimates from HOAPS data set with the earlier estimates to see how they differ from the older estimates. The evaporation rates from HOAPS are significantly different from the earlier estimates. The annual cycle of freshwater flux shows that the Bay of Bengal (BB) is a moisture convergence region most of the year as compared to the Arabian Sea (AS), which is a moisture flux divergence region. Further, the build-up of moisture in the southern Indian Ocean (SIO) is also clearly seen from March to June, indicating its major role in the summer monsoon activity over the Indian subcontinent. An analysis of monthly mean freshwater flux indicates that a small part of the southwest coast of India and southern parts of the BB region receives freshwater in April almost 2 months ahead of the onset of the summer monsoon.     

An urban data framework for assessing equity in cities: Comparing accessibility to healthcare facilities in Cascadia

As cities continue to grow worldwide, policymakers and urban planners face the dual task of meeting rising demand for essential services while ensuring that benefits accrue to their citizens equitably. We propose a framework for assessing inclusivity and equity in cities, which leverages open data and machine learning techniques to inform urban infrastructure investment strategies. The framework is applied at a regional scale to compare differential access to healthcare facilities (public hospitals and clinics) via public transit in Vancouver, Seattle and Portland. We find important distributional impacts on vulnerable populations across the three cities. Portland displays the highest inequity in hospital and clinic access, and Vancouver the least, owing to Vancouver's relatively compact geographic area and high population density. For seniors, over 75% are socially excluded from hospitals and over 50% from clinics in Portland, compared to 30% and 3% respectively in Vancouver. In all three cities, significantly more residents of low-income neighborhoods are excluded from healthcare compared to their counterparts in high-income neighborhoods. This translates into proportionally higher transportation costs for low-income area residents compared with high-income area residents, regardless of whether they are socially excluded or not. Transportation costs are notably high for low-income seniors in Seattle and Vancouver. These findings pose a challenge for inclusive planning, since low-income and senior populations may require specialized services and are more reliant on public transportation than the average population. Our evaluation framework provides a systematic approach for municipalities to account for the distributional effects of transportation and service infrastructure planning, to integrate equity into their decision-making, and to learn from the successes and pitfalls of each other's urban policies.     

Defining and characterizing urban boundaries: A fractal analysis of theoretical cities and Belgian cities

In this paper we extract the morphological boundaries of urban agglomerations and characterize boundary shapes using eight fractal and nonfractal spatial indexes. Analyses were first performed on six archetypal theoretical cities, and then on Belgium’s 18 largest towns. The results show that: (1) the relationship between the shape of the urban boundary (fractal dimension, dendricity, and compactness) and the built morphology within the urban agglomeration (fractal dimension, proportion of buildings close to the urban boundary) is not straightforward; (2) each city is a unique combination of the morphological characteristics considered here; (3) due to their different morphological characteristics, the planning potential of Flemish and Walloon cities seems to be very different.     

Correcting brightness gradients in hyperspectral data from urban areas

The analysis of airborne hyperspectral data is often affected by brightness gradients that are caused by directional surface reflectance. For line scanners these gradients occur in across-track direction and depend on the sensor's view-angle. They are greatest whenever the flight path is perpendicular to the sun-target-observer plane. A common way to correct these gradients is to normalize the reflectance factors to nadir view. This is especially complicated for data from spatially and spectrally heterogeneous urban areas and requires surface type specific models. This paper presents a class-wise empirical approach that is adapted to meet the needs of such images.Within this class-wise approach, empirical models are fit to the brightness gradients of spectrally pure pixels from classes after a spectral angle mapping (SAM). Compensation factors resulting from these models are then assigned to all pixels of the image, both in a discrete manner according the SAM and in a weighted manner based on information from the SAM rule images. The latter scheme is designed in consideration of the great number of mixed pixels.The method is tested on data from the Hyperspectral Mapper (HyMap) that was acquired over Berlin, Germany. It proves superior to a common global approach based on a thorough assessment using a second HyMap image as reference. The weighted assignment of compensation factors is adequate for the correction of areas that are characterized by mixed pixels.A remainder of the original brightness gradient cannot be found in the corrected image, which can then be used for any subsequent qualitative and quantitative analyses. Thus, the proposed method enables the comparison and composition of airborne data sets with similar recording conditions and does not require additional field or laboratory measurements.     

Advances in portable sensing for urban environments: Understanding cities from a mobility perspective

Portable sensing, in which lightweight mobile sensors are used to measure stimuli, events, and human behavior, is a new and disruptive data collection paradigm. It has several methodological advantages compared to traditional methods and is suitable for investigating the dynamism of increasingly mobile and urban societies. In this article, we discuss the motivations behind the use of portable sensing and reflect upon the advances, limitations, and future of the field. Although portable sensing is still in its infancy, we foresee that its utilization will grow in the coming years. For portable sensing to become a prevalent and legitimate methodological approach, it is essential to have conceptually strong study designs that are grounded in suitable ethical procedures and comply with data protection regulations.