Estimating Urban Heat Island Intensity using Remote Sensing Techniques in Dhaka City

Parvin, Nigar Sultana; Abudu, Dan

doi:10.14299/ijser.2017.04.009

Cited by 6 publications

(5 citation statements)

References 17 publications

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“…The rise of LST in Dhaka city has observed 3.2 0 C during the year 2002 to 2014 [18] and in case of Chittagong metropolitan area it is observed 3.81 0 C [20]. The change of average LST at the research study area was 3.43 0 C which is found almost same in the case of Dhaka, Chittagong, and Rajshahi City [21].…”

Section: Introductionmentioning

confidence: 53%

“…Several Studies [17,18,23,24] have shown that quantifying the LST's effects and spatial patterns involves a clear understanding of the LST's relationship with different types of land cover. These studies only explained the change in surface temperature because of the vegetation land cover transformation.…”

Section: Relationship Between Lst and Land Cover Changementioning

confidence: 99%

“…Many researchers have worked on the change of LST in Dhaka City in the literature [16,17,18,19]. Among all these researches, [16] calculated all the factors and indexes related to the change of the LST.…”

Section: Introductionmentioning

confidence: 99%

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Surface Temperature Dynamics in Response to Land Cover Transformation

Morshed

Fattah

Rimi

et al. 2020

JCEST

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This research assessed the micro-level Land Surface Temperature (LST) dynamics in response to Land Cover Type Transformation (LCTT) at Khulna City Corporation Ward No 9, 14, 16 from 2001 to 2019, through raster-based analysis in geo-spatial environment. Satellite images (Landsat 5 TM and Landsat 8 OLI) were utilized to analyze the LCTT and its influences on LST change. Different indices like Normalized Difference Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Buildup Index (NDBI) were adopted to show the relationship against the LST dynamics individually. Most likelihood supervised image classification and land cover change direction analysis shows that about 27.17%, 17.83% and 4.73% buildup area has increased at Ward No 9, 14, 16 correspondingly. On the other hand, the distribution of change in average LST shows that water, vacant land, and buildup area recorded the highest increase in temperature by 2.720C, 4.150C, 4.590C, respectively. The result shows the average LST increased from 25.800C to 27.150C in Ward No 9, 26.840C to 27.230C in Ward No 14 and 26.870C to 27.120C in Ward No 16. Here, the most responsible factor is the transformation of land cover in buildup areas.

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Section: Introductionmentioning

confidence: 53%

Section: Relationship Between Lst and Land Cover Changementioning

confidence: 99%

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Surface Temperature Dynamics in Response to Land Cover Transformation

Morshed

Fattah

Rimi

et al. 2020

JCEST

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“…These results conclude that Dhaka and Chattogram are highly concentrated urban areas with intense land surface temperature; hence, they retain greater hotspot zones. Similarly, diversified surface temperatures are acknowledged for different cities in Bangladesh including Chattogram [62,63], Dhaka [58], Rajshahi [45,64,65], Barisal [66], and Mymensingh [67]. The obtained identification determines that dry land considers high LST values as well as urbanized areas, which is shown in the exploration of several studies [45,63].…”

Section: Assessment Of Lstmentioning

confidence: 96%

Impact of Urbanization on Urban Heat Island Intensity in Major Districts of Bangladesh Using Remote Sensing and Geo-Spatial Tools

Rahman

Rony

Jannat

et al. 2022

Climate

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Urbanization is closely associated with land use land cover (LULC) changes that correspond to land surface temperature (LST) variation and urban heat island (UHI) intensity. Major districts of Bangladesh have a large population base and commonly lack the resources to manage fast urbanization effects, so any rise in urban temperature influences the population both directly and indirectly. However, little is known about the impact of rapid urbanization on UHI intensity variations during the winter dry period in the major districts of Bangladesh. To this end, we aim to quantify spatiotemporal associations of UHI intensity during the winter period between 2000 and 2019 using remote-sensing and geo-spatial tools. Landsat-8 and Landsat-5 imageries of these major districts during the dry winter period from 2000 to 2020 were used for this purpose, with overall precision varying from 81% to 93%. The results of LULC classification and LST estimation showed the existence of multiple UHIs in all major districts, which showed upward trends, except for the Rajshahi and Rangpur districts. A substantial increase in urban expansion was observed in Barisal > 32%, Mymensingh > 18%, Dhaka > 17%, Chattogram > 14%, and Rangpur > 13%, while a significant decrease in built-up areas was noticed in Sylhet < −1.45% and Rajshahi < −3.72%. We found that large districts have greater UHIs than small districts. High UHI intensities were observed in Mymensingh > 10 °C, Chattogram > 9 °C, and Barisal > 8 °C compared to other districts due to dense population and unplanned urbanization. We identified higher LST (hotspots) zones in all districts to be increased with the urban expansion and bare land. The suburbanized strategy should prioritize the restraint of the high intensity of UHIs. A heterogeneous increase in UHI intensity over all seven districts was found, which might have potential implications for regional climate change. Our study findings will enable policymakers to reduce UHI and the climate change effect in the concerned districts.

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“…They found that the UHI effect was significantly related to population change, urban expansion, and meteorological factors such as cloud cover. Parvin and Abudu (2017) used Landsat data to assess UHI in Dhaka from 2002 to 2014 and reported that the temperature of all types of land cover was rising. Das et al (2020) used MODIS data to study UHI seasonal changes in Kolkata and the relationship between UHI and vegetation.…”

Section: Introductionmentioning

confidence: 99%

Diverse cooling effects of green space on urban heat island in tropical megacities

Zong-tang

et al. 2022

Front. Environ. Sci.

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Cities in tropical regions are experiencing high heat risks by overlaying the urban heat island (UHI) effect. Urban green space (UGS) can provide local cooling effect and reduce UHI. However, there still lack a comprehensive exploration of the characteristics of UHI and cooling effect of UGS due to high cloud coverage and limited number of available remote sensing observations. In this study, the enhanced spatial and temporal adaptive reflectance data fusion method was employed to develop an enhanced land surface temperature data in winter seasons in three tropical megacities, Dhaka, Kolkata, and Bangkok. The spatiotemporal variations of surface urban heat island (SUHI) were explored from 2000 to 2020 with a 5-years interval. The optimal size of UGS associated with its cooling effects was assessed by using the threshold value of efficiency (TVoE). The relationship between the intensity and range of urban cooling island (UCI) and four landscape metrics of green space patches, total area (P_Area), shape index (P_SI), normalized difference vegetation index (P_NDVI), and land surface temperature (P_LST), were analyzed. The results show that the average SUHI intensity increased by 0.98°C, 1.42°C, and 0.73°C in Dhaka, Kolkata, and Bangkok, respectively, from 2000 to 2020. The maximum intensity of UCI ranges from 4.83°C in Bangkok to 8.07°C in Kolkata, and the maximum range of UCI varies from 300 m in Bangkok to 420 m in Kolkata. The optimal size of green space is 0.37 ha, 0.77 ha, and 0.42 ha in Dhaka, Kolkata, and Bangkok, respectively. The P_NDVI and P_Area had significant positive effects on UCI intensity and range, while the background temperature had significant negative effects. With higher background temperature, the optimal patch size of UGS is larger. This study provides useful information for developing effective heat mitigation and adaptation strategies to enhance climate resilience in tropical cities.

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Estimating Urban Heat Island Intensity using Remote Sensing Techniques in Dhaka City

Cited by 6 publications

References 17 publications

Surface Temperature Dynamics in Response to Land Cover Transformation

Surface Temperature Dynamics in Response to Land Cover Transformation

Impact of Urbanization on Urban Heat Island Intensity in Major Districts of Bangladesh Using Remote Sensing and Geo-Spatial Tools

Diverse cooling effects of green space on urban heat island in tropical megacities

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