Analysis of Urban Heat Island in Kochi, India, Using a Modified Local Climate Zone Classification

Thomas, George; Sherin, A.P.; Ansar, Shareekul; Zachariah, E. J.

doi:10.1016/j.proenv.2014.09.002

Cited by 96 publications

(37 citation statements)

References 4 publications

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“…The "Compact mid-rise" was the warmest (38.8 o C in the hot and 24.9 o C in the cool season) followed by the "Compact low-rise" (37.8 o C in the hot and 23.5 o C in the cool season) and the "Light weight low-rise" (37.5 o C in the hot and 23.3 o C in the cool season). Similarly, in Kochi India, maximum heat intensity was recorded in "Compact mid-rise" while intense cooling was recorded in "Sparsely built" areas in all seasons (Thomas, et al, 2014).…”

Section: Average Temperature For Lczmentioning

confidence: 88%

Retrieval of Local Climate Zones and Their Linkages to Land Surface Temperature Using Remote Sensing in Harare Metropolitan City, Zimbabwe

Mushore

2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> This study sought to determine Local Climate Zones (LCZs) in Harare metropolitan City, using Landsat 8 multi-spectral and multi-temporal data. The World Urban Database and Access Portal Tool (WUDAPT) and Support Vector Machine classifiers were applied. Training datasets were extracted from Google Earth as prescribed by the WUDAPT procedure. Before image classification, we tested the separability of the LCZs, using the Transformed Divergence Separability Index (TDSI) based on the digitized training datasets and Landsat 8 data. Derived LCZs were then linked with Landsat 8 derived Land Surface Temperature (LST) for the cool and hot seasons. TDSI values greater 1.9 were obtained indicating that LCZs were highly separable. Comparatively, the WUDAPT method produced more accurate LCZs results (Overall accuracy = 95.69%) than the SVM classifier (Overall accuracy = 89.86%) based on seasonal Landsat 8 data. However, SVM derived accuracies were within the acceptable range of at least 80% (overall accuracy) in literature. Further, LST was observed to be high in LCZs with high built-up density and low vegetation proportion, when compared to other zones. Due to high proportion of vegetation, sparsely built areas were at least 1&thinsp;&deg;C cooler. Although LCZs are usually linked at 2&thinsp;m air temperature, they also strongly explain LST distribution. This work provides insight into the importance of mapping LCZs in third world countries where such information remains scarce.</p>

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Section: Average Temperature For Lczmentioning

confidence: 88%

Retrieval of Local Climate Zones and Their Linkages to Land Surface Temperature Using Remote Sensing in Harare Metropolitan City, Zimbabwe

Mushore

2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…They are calculated using the wind speed profile exponent and wind speed profile boundary layer thickness of an area, which are considered input parameters [110][111][112] (Table 1). In Indian cities, the UHI effects are of varying intensities (approximately 0.8-10 °C rise) and periodicities [113,114]. However, this study does not directly explain the UHI effects considering the complexity to account for such effects within the TMY weather data.…”

Section: Climate and Micro-climatementioning

confidence: 96%

Influence of building design and control parameters on the potential of mixed-mode buildings in India

Gokarakonda

Treeck

Rawal

2019

Building and Environment

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The potential of mixed-mode office buildings with varying design and control parameters is examined by using an uncertainty analysis in the three climate zones of India. The analysis is in terms of cooling energy consumption, thermal comfort conditions, and natural ventilation hours. Furthermore, influential parameters are identified using sensitivity analysis. In this study, opening the windows enables natural ventilation. Night-time ventilation through the windows is not enabled because these are mostly closed at night. A maximum natural ventilation of 10% of the total building occupancy hours are observed in warm and humid, and hot and dry climates; however, they are slightly higher in the composite climate. A further increase in the number of natural ventilation hours leads to an increase in the occupancy hours outside the Indian Model for Adaptive Comfort model for mixed-mode buildings with at least 90% of occupants are satisfied. There are no occupancy hours outside of 80% of occupants are satisfied. The choice of thermal comfort band is crucial for determining the potential of mixed-mode buildings. The cooling setpoint temperature, building size, window solar heat gain coefficient, and surface properties of exterior surfaces are identified as the more influential parameters than the thermophysical properties of building envelope constructions. Although the building envelope which is in compliance with the Energy Efficient Building Code of India increases energy efficiency during airconditioning periods, whether it reduces natural ventilation hours, because of overheating during such period remains to be determined.

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“…The value of parameters considered for dispersion modeling is given in Table . The ground roughness is taken as 30 cm . The Gaussian dispersion model is given as

bold-italicC (|, bold-italicx, bold-italicy, bold-italicz) = \frac{bold-italicQ}{bold-italicπ {bold-italicσ}_{bold-italicz} {bold-italicσ}_{bold-italicy} bold-italicu} {bold-italice}^{({}|, - \frac{1}{2} ([]|, \frac{{bold-italicy}^{2}}{{bold-italicσ}_{bold-italicy}^{2}} + \frac{{bold-italicz}^{2}}{{bold-italicσ}_{bold-italicz}^{2}}))}

…”

Section: Dispersion Modelmentioning

confidence: 99%

“…The value of parameters considered for dispersion modeling is given in Table 1. The ground roughness is taken as 30 cm [31]. The Gaussian dispersion model is given as…”

Section: Dispersion Modelmentioning

confidence: 99%

Consequence assessment of anhydrous ammonia release using CFD‐probit analysis

Namboothiri

Soman

2018

Process Safety Progress

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An accidental release of hazardous chemical can happen in industries during its production, storage, and transportation. The consequence assessment is a method of analyzing the impact of hazardous chemical release into the environment. It includes the identification of threat zone and its impact on people. Consequence assessment is a primary part of risk assessment which is essential for the development of mitigation strategy. In this study, a consequence assessment of anhydrous ammonia release from a storage facility was conducted and the mitigation strategy was developed. A hypothetical accidental release of ammonia from a storage facility in a chemical process industry was assumed. The evaporation of ammonia pool formed by the release was estimated using CFD analysis and the dispersion of the ammonia was found out using ALOHA. Three different wind speed was taken for analyzing the consequences. Probability of death of people living in the threat zone was estimated by probit analysis. A mitigation strategy was developed based on adsorption principle using modified carbon nanoparticles. © 2018 American Institute of Chemical Engineers Process Saf Prog 37: 525–534, 2018

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Analysis of Urban Heat Island in Kochi, India, Using a Modified Local Climate Zone Classification

Cited by 96 publications

References 4 publications

Retrieval of Local Climate Zones and Their Linkages to Land Surface Temperature Using Remote Sensing in Harare Metropolitan City, Zimbabwe

Retrieval of Local Climate Zones and Their Linkages to Land Surface Temperature Using Remote Sensing in Harare Metropolitan City, Zimbabwe

Influence of building design and control parameters on the potential of mixed-mode buildings in India

Consequence assessment of anhydrous ammonia release using CFD‐probit analysis

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