Exploring temperature indices by deriving relationship between land surface temperature and urban landscape

Nimish, G.; Hariharan, Bharath; Allaka, Lalitha

doi:10.1016/j.rsase.2020.100299

Cited by 38 publications

(19 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This correlation was weak positive (0.06) in Harare Metropolitan City, Zimbabwe (Mushore et al, 2017). This relationship was also positive (0.458) in Kolkata Metropolitan Area, India (Nimish et al, 2020). The present study shows that the average correlation coefficient between LST and NDBaI for all the months from 1988 to 2020 is moderate positive (0.32).…”

Section: Monthly Analysis On Lst-spectral Indices Relationshipmentioning

confidence: 40%

A long-term monthly analytical study on the relationship of LST with normalized difference spectral indices

Guha

Govil

2021

European Journal of Remote Sensing

View full text Add to dashboard Cite

This study analyzes the long-term monthly variation of land surface temperature (LST) and its relationship with normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), and normalized difference bareness index (NDBaI) in the Raipur City of India using one hundred and twenty-three Landsat images from 1988-2020. In terms of LST, the warmest month is April (38.49 o C) and the coldest month is January (23.04 o C). The standard deviation in LST is noticed as 1.1022 o C throughout the period. The growth pattern of LST is increasing in the earlier stage while it is steady and decreasing in the later stage. The mean linear regression coefficients for LST-NDVI is -0.42, LST-NDBI are 0.68, LST-NDWI is 0.27, and LST-NDBaI is 0.32. It indicates that the high ratio of green vegetation and water bodies resist the raise of LST, whereas the bare rock surface and built-up land accelerate the LST. The value of the spectral indices and LST varies with the change of month due to the physical change of the land surface materials. Hence, the study will be an effective one for the town and country planners for their future estimation of land conversion.

show abstract

Section: Monthly Analysis On Lst-spectral Indices Relationshipmentioning

confidence: 40%

A long-term monthly analytical study on the relationship of LST with normalized difference spectral indices

Guha

Govil

2021

European Journal of Remote Sensing

View full text Add to dashboard Cite

show abstract

“…(Cui and Shi 2012). The positive association between LST and NDBI was shown by Tan et al (2020) and Nimish et al (2020), demonstrating the high impact of impermeable surfaces on urban temperatures (Nimish et al 2020, Tan et al 2020. In relation to LULC, Liu et al (2020) evaluated the LST variation and concluded that the LST variation was associated positively with impermeable surfaces and negatively with vegetation (Liu et al 2020).…”

Section: Discussionmentioning

confidence: 97%

Spatiotemporal shifts in thermal climate in responses to urban cover changes: a-case analysis of major cities in Punjab, Pakistan

Dilawar

Chen

Trisurat

et al. 2021

Geomatics, Natural Hazards and Risk

View full text Add to dashboard Cite

This study investigates the relationship of urban thermal environment (UTE) with various influential factors as well as ecological conditions. The relation between LST and land use and land cover (LULC) changes was explored in terms of remote-sensing (RS) based indices; heat effect contribution index (HECI), Urban thermal field variance index (UTFVI), Surface urban heat island intensity (SUHII), Normal Difference Built-up Index (NDBI), and Normal Difference Vegetation Index (NDVI). LULC maps were classified using the unsupervised classification technique and made error matrix to determine the accuracy. Results revealed that the vegetated area in Faisalabad decreased by 230 km 2 due to an expansion in the urban area of 124-320 km 2 during the period 1992-2014. An average LST in the rural buffers is increasing rapidly as compare to urban buffer and varied over the eight years with a range of 0.68-2.57 (C). After 2007, SUHII's linear trend was negative because rural temperatures were still rising. Based on HECI, we found that urban expansion mainly led to increase in LST. UTFVI has shown poor ecological conditions in all urban buffers. In addition, there is a positive correlation between LST and NDBI, while NDVI indicates a negative correlation with LST.

show abstract

“…LST can change significantly in a vast homogeneous land surface or even inside a relatively small heterogeneous urban area [14,24,25]. Different types of LULC response differently in TIR band and consequently LST largely varies in an urban environment [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44]. The LULC types are mainly changed by land conversion process [10].…”

Section: Introductionmentioning

confidence: 99%

Land surface temperature and normalized difference vegetation index relationship: a seasonal study on a tropical city

Guha

Govil

2020

SN Appl. Sci.

View full text Add to dashboard Cite

Land surface temperature (LST) and its relationship with normalized difference vegetation index (NDVI) are significantly considered in environmental study. The aim of this study was to retrieve the LST of Raipur City of tropical India and to explore its seasonal relationships with NDVI. Landsat images of four specific seasons for three particular years with fourteen years time interval were analyzed. The result showed a gradual rising (3.63 °C during 1991-2004 and 1.54 °C during 2004-2018) of LST during the whole period of study. The mean LST value of three particular years was the lowest (27.21 °C) on green vegetation and the highest (29.81 °C) on bare land and built-up areas. The spatial distribution of NDVI and LST reflects an inverse relationship. The best (− 0.63) and the least (− 0.17) correlation were noticed in the postmonsoon and winter seasons, respectively, whereas a moderate (− 0.45) correlation were found both in the monsoon and pre-monsoon seasons. This LST-NDVI correlation was strong negative (− 0.51) on vegetation surface, moderate positive on water bodies (0.45), and weak positive on the built-up area and bare land (0.14). In summary, the LST is greatly controlled by surface characteristics. This study can be used as a reference for land use and environmental planning in a tropical city.

show abstract

Exploring temperature indices by deriving relationship between land surface temperature and urban landscape

Cited by 38 publications

References 29 publications

A long-term monthly analytical study on the relationship of LST with normalized difference spectral indices

A long-term monthly analytical study on the relationship of LST with normalized difference spectral indices

Spatiotemporal shifts in thermal climate in responses to urban cover changes: a-case analysis of major cities in Punjab, Pakistan

Land surface temperature and normalized difference vegetation index relationship: a seasonal study on a tropical city

Contact Info

Product

Resources

About