Spatio-temporal variability of urban heat islands in local climate zones of Delhi-NCR
04 Oct 2017-Vol. 10431, pp 1043110
TL;DR: In this paper, the authors focused on surface UHI conventionally studied using thermal band of the remotely sensed satellite images and determined the Land Surface Temperature (LST) for the year 2015 using Landsat 8 for Delhi National Capital Region (NCR).
Abstract: Land use change is at the nexus of human territory expansion and urbanization. Human intrusion disturbs the natural heat energy balance of the area, although a new equilibrium of energy flux is attained but with greater diurnal range and adversely affecting the geo/physical variables. Modification in the trend of these variables causes a phenomenon known as Urban Heat Island (UHI) i.e. a dome of heat is formed around the city which has 7-10 °C high temperature than the nearby rural area at night. The study focuses on Surface UHI conventionally studied using thermal band of the remotely sensed satellite images. Land Surface Temperature (LST) is determined for the year 2015 using Landsat 8 for Delhi National Capital Region (NCR). This region was chosen because it is the biggest urban agglomeration in India, many satellite cities are coming in periphery and it has temperate climate. Quantification of UHI is predictably done using UHI intensity that is the difference between representative Urban and rural temperature. Recently the definition of urban and rural has been questioned because of various kinds of configurations of urban spaces across the globe. Delhi NCR urban configurations vary spatially- thus one UHI intensity does not give a deep understanding of the micro-climate. Advancement was made recently to standardize UHI intensity by dividing city into Local Climate Zones (LCZ), comes with 17 broad categories. LCZ map of Delhi NCR has been acquired from World Urban Database. The seasonality in LST across LCZ has been determined along with identifying warmest and coolest LCZ.
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TL;DR: In this paper, the suitability of the Local Climate Zones (LCZ) scheme for surface urban heat islands (SUHI) studies based on 50 cities from across the globe is investigated.
Abstract: Assessment of surface urban heat islands (SUHI) has been hampered by the lack of a consistent framework to permit consistent interpretation between cities. Local Climate Zones (LCZ) are a universal description of local scale landscape types based on expected variation at neighbourhood scale (≥1km2) in and around cities. In this study, we investigate the suitability of the LCZ scheme for SUHI studies based on 50 cities from across the globe. For comparability we use an annual temperature cycle model for MODIS land surface temperature (LST) at different overpass times and multi-year mean Landsat 8 LST. The SUHI analysis shows significant differences in the intra-urban estimate of SUHI for different built LCZ types. Substantial variability of SUHI within LCZ classes and between cities exists and SUHI patterns vary by time of day. Landsat derived estimates have very high correlations to those from MODIS at a similar time. The use of an LCZ approach combined with annual SUHI estimates provides a promising approach for a consistent and comprehensive SUHI analysis framework subject to further work to assess the spatial scale of matching LST and LCZ data, filter for topographic effects, and include the phenological status.
137 citations
TL;DR: In this article, the authors examined the spatial-temporal changes of land cover and the surface urban heat island (SUHI) effect in the Pearl River Delta (PRD) region from 2000 to 2015.
Abstract: This study examines the spatial-temporal changes of land cover and the surface urban heat island (SUHI) effect in the Pearl River Delta (PRD) region from 2000 to 2015. The Local Climate Zone (LCZ) concept is used, given its standard but comprehensive classification scheme designed for urban climate studies. Firstly, historical LCZ maps of the PRD region were generated using the World Urban Database and Access Portal Tools (WUDAPT) protocol. Secondly, summer mean land surface temperature (LST) during daytime and night-time was retrieved from remote sensing data to analyze the SUHI. Thirdly, the correspondence between the spatial-temporal patterns of LCZ and LST were explored. The results show that urbanization in this region comprises transformation from natural land covers to built types and conversion in the built up, in particular densification and vertical enhancement of existing urban types. The LST in the region increased in general but the spatial pattern of LST increase is affected by the land cover change. LCZ 6 (open low-rise) and LCZ 8 (large low-rise) show the greatest increase in LST. LCZ 4 (open high-rise) and LCZ 8 are the two dominant LCZs in high SUHI zone and LCZ 8 keeps growing as the most principal LCZ type.
71 citations
TL;DR: It is argued that modern earth observation data can represent an important data source for research on environmental justice and health due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics.
Abstract: Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people’s physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using “essentially aspatial” data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of ’big earth data’ for future environmental justice analyses.
36 citations
TL;DR: In this paper, the suitability of the Local Climate Zone (LCZ) classification scheme for land surface temperature (LST) and surface urban heat island (SUHI) studies in different macroclimate regions was investigated.
Abstract: The Local Climate Zone (LCZ) classification scheme, initially designed to distinguish between standard built (urban) and non-built (land cover) types in terms of screen-level air temperature relevant for urban heat island (UHI) studies, has been widely used for land surface temperature (LST) and surface urban heat island (SUHI) studies. However, some concerns remain about the global suitability of the scheme for LST and SUHI studies in different macroclimate regions. By analyzing and comparing a large number of representative LCZ sites and multi-year remotely-sensed LST data, the aim of this work is twofold. Firstly, to study the suitability of the LCZ scheme, with a focus on the built types, for surface temperature studies in four distinct macroclimate regions, namely, the tropical, the arid, the temperate and the cold. Secondly, to understand the influence of the macroclimate region on the LST and SUHI characteristics of the standard LCZ built types. Results show that the urban LCZ standard scheme is applicable, with varying degrees, to all macroclimate regions other than the arid, where a LCZ subclassification might be essential. Also, it has been demonstrated that most LCZ built types exhibit significantly different LST and SUHI characteristics across the remaining macroclimate regions.
21 citations
TL;DR: Zhang et al. as discussed by the authors investigated the correlation between spatiotemporal changes of surface urban heat island (sUHI) and urbanization in Beijing, land surface temperature in summer from 2000 to 2017 and the distribution of local climate zones (LCZs) in 2003, 2005, 2010, and 2017 using remote sensing data and used to analyze the sUHI area and intensity change.
Abstract: The increasing degree of urbanization has continuously aggravated the surface urban heat island (sUHI) effect in China. To investigate the correlation between spatiotemporal changes of sUHI and urbanization in Beijing, land surface temperature in summer from 2000 to 2017 and the distribution of local climate zones (LCZs) in 2003, 2005, 2010, and 2017 was retrieved using remote sensing data and used to analyze the sUHI area and intensity change. The statistical method GeoDetector was utilized to investigate the explanatory ability of LCZs and population as the driving factors. The year of 2006 was identified as the main turning year for sUHI evolution. The variation the sUHI from 2000 showed first an increasing trend, and then a decreasing one. The sUHI pattern changed before and after 2009. Before 2009, the sUHI mainly increased in the suburbs, and then, the enhancement area moved to the central area. The sUHI intensity change under different LCZ conversion conditions showed that the LCZ conversion influences the sUHI intensity significantly. Based on population distribution data, we found that the relationship between population density and sUHI gets weaker with increasing population density. The result of GeoDetector indicated that the LCZ is the main factor influencing the sUHI, but population density is an important auxiliary factor. This research reveals the sUHI variation pattern in Beijing from 2000 and could help city managers plan thermally comfortable urban environments with a better understanding of the effect of urban spatial form and population density on sUHIs.
17 citations
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TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Abstract: Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, aaa, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.
79,257 citations
TL;DR: A new digital Koppen-Geiger world map on climate classification, valid for the second half of the 20 th century, based on recent data sets from the Climatic Research Unit of the University of East Anglia and the Global Precipitation Climatology Centre at the German Weather Service.
Abstract: The most frequently used climate classification map is that o f Wladimir Koppen, presented in its latest version 1961 by Rudolf Geiger. A huge number of climate studies and subsequent publications adopted this or a former release of the Koppen-Geiger map. While the climate classification concept has been widely applied to a broad range of topics in climate and climate change research as well as in physical geography, hydrology, agriculture, biology and educational aspects, a well-documented update of the world climate classification map is still missing. Based on recent data sets from the Climatic Research Unit (CRU) of the University of East Anglia and the Global Precipitation Climatology Centre (GPCC) at the German Weather Service, we present here a new digital Koppen-Geiger world map on climate classification, valid for the second half of the 20 th century. Zusammenfassung Die am haufigsten verwendete Klimaklassifikationskarte ist jene von Wladimir Koppen, die in der letzten Auflage von Rudolf Geiger aus dem Jahr 1961 vorliegt. Seither bildeten viele Klimabucher und Fachartikel diese oder eine fruhere Ausgabe der Koppen-Geiger Karte ab. Obwohl das Schema der Klimaklassifikation in vielen Forschungsgebieten wie Klima und Klimaanderung aber auch physikalische Geographie, Hydrologie, Landwirtschaftsforschung, Biologie und Ausbildung zum Einsatz kommt, fehlt bis heute eine gut dokumentierte Aktualisierung der Koppen-Geiger Klimakarte. Basierend auf neuesten Datensatzen des Climatic Research Unit (CRU) der Universitat von East Anglia und des Weltzentrums fur Niederschlagsklimatologie (WZN) am Deutschen Wetterdienst prasentieren wir hier eine neue digitale Koppen-Geiger Weltkarte fur die zweite Halfte des 20. Jahrhunderts.
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TL;DR: The Local Climate Zone (LCZ) classification system as discussed by the authors was developed to address the inadequacies of urban-rural description, and consists of 17 zone types at the local scale (102 to 104 m).
Abstract: The effect of urban development on local thermal climate is widely documented in scientific literature. Observations of urban–rural air temperature differences—or urban heat islands (UHIs)—have been reported for cities and regions worldwide, often with local field sites that are extremely diverse in their physical and climatological characteristics. These sites are usually described only as “urban” or “rural,” leaving much uncertainty about the actual exposure and land cover of the sites. To address the inadequacies of urban–rural description, the “local climate zone” (LCZ) classification system has been developed. The LCZ system comprises 17 zone types at the local scale (102 to 104 m). Each type is unique in its combination of surface structure, cover, and human activity. Classification of sites into appropriate LCZs requires basic metadata and surface characterization. The zone definitions provide a standard framework for reporting and comparing field sites and their temperature observations. The LCZ s...
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TL;DR: In this article, the authors review the use of thermal remote sensing in the study of urban climates, focusing primarily on the urban heat island effect and progress made towards answering the methodological questions posed by Roth et al.
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