Comparison of temporal changes in urban settlements and land surface temperature in Rangpur and Gazipur Sadar, Bangladesh after the establishment of city corporation

Roy, Bishal; Bari, Ehsanul; Nipa, Nusrat Jahan; Ani, Sadia Afrin

doi:10.1016/j.rsase.2021.100587

Cited by 13 publications

(8 citation statements)

References 43 publications

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“…Increased NDBI signifies increased build-ups of impervious surfaces or urbanization. As impervious surfaces show the highest temperatures in built-up areas [ 26 ], LST should be positively correlated with NDBI. Figure 4 (b) shows a substantial positive association between NDBI and LST in 2018, suggesting built-up areas increased in 2018 compared to 2000–2016, altering the thermal characteristics.…”

Section: Discussionmentioning

confidence: 99%

“…Due to increasing urbanization, land surface types have been changing in recent years [ 25 ]. Using remotely sensed satellite imagery, a change in surface temperature may be observed, which is an indicator of impervious surface build-up [ 26 ]. The distribution of LST is greatly influenced by the presence of natural vegetation [ 15 , 27 , 28 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

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Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine

Roy

Bari²

2022

Heliyon

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine

Roy

Bari²

2022

Heliyon

Self Cite

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“…To achieve this global goal and frame policies for mitigating Urban climate (UC) and Urban microclimate (UMC) change it is crucial to understand the Multi-Temporal LULC change and its impact on LST. Several studies have used Remote Sensing and GIS to study LST its impact on UC [15][16][17][18][19]. To carry out Multi Spatio-Temporal study of UMC using Remote Sensing is challenging with the constraints of proprietary software, big data, computer space, and tedious hour of processing data.…”

Section: Introductionmentioning

confidence: 99%

Integration of Remote Sensing and Big Data to Study Spatial Distribution of Urban Heat Island for Cities with Different Terrain

Shah

Patel

2023

IJE

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Urban microclimate has posed a detrimental effect on the life of the urban population. This research drives with an aim of identifying environmentally conscious factor vis-a-vis urban planning which leads to the vicious cycle of urban climate change. The vicious cycle is inclusive of many urban dynamics' parameters, which are complicated to understand. This research emphasizes on using Remote Sensing Big Data on Google Earth Engine as an advancement to study Climate Vulnerability leading to Urban Climate Gentrification. Temporal data of Landsat for the past 30 years has been taken into consideration for the study. Three cities with diverse geographical and terrain characteristics have been selected for the study, to understand the modern decisive planning is in coherence with the Sustainable Development Goals. Understanding spatial and temporal information of Urban hotspots using High-Resolution Satellite data is just not enough to suffice the need to decrease the temperature by 2-3°C. The present study is a toll on how the reasons for microclimate change vary along with the terrain, spatial location, and urban growth pattern of the city.

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“…The urban growth impacts the carbon cycle through land cover change, modification of surface energy balance especially albedo, and the loss of carbon stocks. Increasing trends in urban impervious surface have negative environmental impacts to the city climate as, less precipitation, more dryness and urban higher temperatures and associated natural hazards related to heat waves and urban heat islands 6,7 . However, the response of urban vegetation land cover to multiple climatic stressors varies interannually and in different seasons of the years, related to different vegetation type's characteristics and climatic conditions.…”

Section: Introductionmentioning

confidence: 99%

Exploring with time-series satellite data of multiple stressors effects on urban/periurban vegetation

Zoran,

Savastru,

Savastru

et al. 2023

Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023)

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Urban vegetation and its carbon storage capacity are critical factors for terrestrial carbon cycling and global sustainable development goals (SDGs). Scientific research for a better managing of urban green land cover is an essential issue of the sustainable urban development initiative promoted by the EU governments. Owing to a crucial role that urban vegetation perform in an urban ecosystem, being effective in mitigating the air pollution and urban heat island effect by canopy shade and evapotranspiration, studying the vegetation dynamics in terms of its derived satellite biogeophysical variables becomes inevitable in the context of climate-smart city planning and design. However, in order to explain the urban-rural gradient in vegetation greenness trends and its responses to climate and antropogenic drivers of land-cover changes this study used time-series of derived satellite data (normalized difference vegetation index-NDVI, enhanced vegetation index-EVI, land surface temperature-LST, leaf area index LAI, and fraction of photosynthetically active radiation absorbed by vegetation-FPAR). Satellite datasets of MODIS Terra, and Landsat TM/ETM + have been used for urban vegetation analysis over 2002-2022 period of Bucharest metropolitan area in Romania. Was found that the average decrease in vegetation land cover was 0.1 to 0.3. The correlation analyses revealed that, at the pixel-scale, LST possessed a strong positive correlation with NDVI, EVI, FPAR and LAI during the entire investigated period. Only during summer period NDNI/EVI are inversely correlated with LST (r= -0.67; p<0.01) The spatio-temporal pattern of urban/periurban vegetation dynamics trends and their association with other atmospheric, biological, and soil indicators need to be studied with different satellite sensors and resolutions over the long-term periods of time.

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Comparison of temporal changes in urban settlements and land surface temperature in Rangpur and Gazipur Sadar, Bangladesh after the establishment of city corporation

Cited by 13 publications

References 43 publications

Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine

Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine

Integration of Remote Sensing and Big Data to Study Spatial Distribution of Urban Heat Island for Cities with Different Terrain

Exploring with time-series satellite data of multiple stressors effects on urban/periurban vegetation

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