Studying Surface and Canopy Layer Urban Heat Island at Micro-Scale Using Multi-Sensor Data in Geographic Information Systems
01 Oct 2018-International Journal of Applied Geospatial Research (IGI Global)-Vol. 9, Iss: 4, pp 36-56
TL;DR: The article progresses from initially traversing through the city of Greater Noida to continuous manual data collection on an academic campus and later by automating it with integrated sensors on a microcontroller while achieving the objective of the collection of continuous high spatio-temporal scale data.
Abstract: Variations of Urban Heat Island (UHI) effect within urban areas cannot be studied in detail using traditional combination of satellite images with thermal infrared (IR) bands and local weather station data due to their limited spatio-temporal scale. In this article, a system has been built to supplement the current infrastructure and enhance the high spatio-temporal scale. The article progresses from initially traversing through the city of Greater Noida to continuous manual data collection on an academic campus and later by automating it with integrated sensors on a microcontroller while achieving the objective of the collection of continuous high spatio-temporal scale data. Geographic information systems (GISs) were used to integrate and visualize these data with land surface temperature (LST) and air temperature data. The system provided the diurnal cycle of urban materials and insights into nighttime UHI at micro-scale. Overall the low-cost sensing technology presented has the potential to monitor citywide UHI.
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TL;DR: In this article , the feasibility of using CORINE Land Cover (CLC) land use and land cover data and alternative high-resolution global coverage land use/land cover (LULC) data from Copernicus Global Land Service Land Cover Map (CGLS-LC100) V2.0 in high resolution weather research and forecasting (WRF) simulations (100 × 100 m).
Abstract: Increased computing power has made it possible to run simulations of the Weather Research and Forecasting (WRF) numerical model in high spatial resolution. However, running high-resolution simulations requires a higher-detail mapping of landforms, land use, and land cover. Often, higher-resolution data have limited coverage or availability. This paper presents the feasibility of using CORINE Land Cover (CLC) land use and land cover data and alternative high-resolution global coverage land use/land cover (LULC) data from Copernicus Global Land Service Land Cover Map (CGLS-LC100) V2.0 in high-resolution WRF simulations (100 × 100 m). Global LULC data with a resolution of 100 m are particularly relevant for areas not covered by CLC. This paper presents the method developed by the authors for reclassifying land cover data from CGLS-LC100 to MODIS land use classes with defined parameters in the WRF model and describes the procedure for their implementation into the model. The obtained simulation results of the basic meteorological parameters from the WRF simulation using CLC, CGLS-LC100 and default geographical data from MODIS were compared to observations from 13 meteorological stations in the Warsaw area. The research has indicated noticeable changes in the forecasts of temperature, relative humidity wind speed, and direction after using higher-resolution LULC data. The verification results show a significant difference in weather predictions in terms of CLC and CGLS-LC100 LULC data implementation. Due to the fact that better results were obtained for CLC simulations than for CGLS-LC100, it is suggested that CLC data are first used for simulations in numerical weather prediction models and to use CGLS-LC100 data when the area is outside of CLC coverage.
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TL;DR: Results of observational studies suggest that in many areas that have been analyzed, changes in total precipitation are amplified at the tails, and changes in some temperature extremes have been observed.
Abstract: One of the major concerns with a potential change in climate is that an increase in extreme events will occur. Results of observational studies suggest that in many areas that have been analyzed, changes in total precipitation are amplified at the tails, and changes in some temperature extremes have been observed. Model output has been analyzed that shows changes in extreme events for future climates, such as increases in extreme high temperatures, decreases in extreme low temperatures, and increases in intense precipitation events. In addition, the societal infrastructure is becoming more sensitive to weather and climate extremes, which would be exacerbated by climate change. In wild plants and animals, climate-induced extinctions, distributional and phenological changes, and species' range shifts are being documented at an increasing rate. Several apparently gradual biological changes are linked to responses to extreme weather and climate events.
4,379 citations
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.
2,013 citations
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...Traditionally, satellite data having thermal infrared bands provide land surface temperature (Weng, 2009), which are used to study urban climate with various limitations (Voogt and Oke, 2003)....
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TL;DR: In this article, the authors present a survey of methods, techniques, and applications of remotely sensed TIR data used in urban climate and environmental studies, mainly for analyzing land surface temperature (LST) patterns and its relationship with surface characteristics, assessing urban heat island (UHI), and relating LSTs with surface energy fluxes.
Abstract: Thermal infrared (TIR) remote sensing techniques have been applied in urban climate and environmental studies, mainly for analyzing land surface temperature (LST) patterns and its relationship with surface characteristics, assessing urban heat island (UHI), and relating LSTs with surface energy fluxes to characterize landscape properties, patterns, and processes. This paper examines current practices, problems, and prospects in this particular field of study. The emphasis is placed in the summarization of methods, techniques, and applications of remotely sensed TIR data used in urban studies. In addition, some future research directions are outlined. This literature review suggests that the majority of previous research have focused on LST patterns and their relationships with urban surface biophysical characteristics, especially with vegetation indices and land use/cover types. Less attention has been paid to the derivation of UHI parameters from LST data and to the use of remote sensing techniques to estimate surface energy fluxes. Major recent advances include application of sub-pixel quantitative surface descriptors in examining LST patterns and dynamics, derivation of key UHI parameters based on parametric and non-parametric models, and integration of remotely sensed variables with in situ meteorological data for urban surface energy modeling. More research is needed in order to define better “urban surface” from the remote sensing viewpoint, to examine measurement and modeling scales, and to differentiate modeled and measured fluxes.
884 citations
Additional excerpts
...Traditionally, satellite data having thermal infrared bands provide land surface temperature (Weng, 2009), which are used to study urban climate with various limitations (Voogt and Oke, 2003)....
[...]
TL;DR: In this paper, the authors used remote sensing for comparative assessment of surface urban heat island (UHI) in 18 mega cities in both temperate and tropical climate regions and applied a Gaussian approximation to quantify spatial extents and magnitude of individual UHIs for inter-city comparison.
712 citations
TL;DR: In this paper, the surface radiant temperature heat islands of Vancouver, British Columbia, Seattle, Washington, and Los Angeles, California were used to display the surface temperature heat island data.
Abstract: NOAA AVHRR satellite infra-red data are used to display the surface radiant temperature heat islands of Vancouver, British Columbia, Seattle, Washington, and Los Angeles, California. Heat island intensities are largest in the day-time and in the warm season. Day-time intra-urban thermal patterns are strongly correlated with land-use; industrial areas are warmest and vegetated, riverine or coastal areas are coolest. Nocturnal heat island intensities and the correlation of the surface radiant temperature distribution with land use are less. This is the reverse of the known characteristics of near-surface air temperature heat islands. Several questions relating to the interpretation and limitations of satellite data in heat island analysis and urban climate modelling are addressed.
695 citations