Environmental Challenges 4 (2021) 100167 Contents lists available at ScienceDirect Environmental Challenges journal homepage: www.elsevier.com/locate/envc Assessment of land surface temperature and land cover variability during winter: A spatio-temporal analysis of Pabna municipality in Bangladesh Farhan Asaf Abir ∗ , Ritu Saha Department of Urban and Regional Planning, Pabna University of Science and Technology (PUST), Rajapur, Pabna, 6600, Bangladesh a r t i c l e i n f o Keywords: Land use/land cover Land surface temperature Land surface indicators Maximum Likelihood Classification Simple Regression Model a b s t r a c t Monitoring the change of land use and land cover (LULC) and land surface temperature (LST) at different spatio- temporal scales is vital for evaluating landscape dynamics and thermal environment. This study investigates the decadal change of LULC and winter LST on Pabna municipality over the period between 1990 and 2020 using Landsat images (TM, ETM+ and OLI). The study further explores LST distribution for different LULC classes and the explanatory power of various land surface indicators for change in LST. A supervised maximum likelihood classification (MLC) technique was used for LULC mapping of the study area. The results showed that built- up areas were increasing rapidly while water bodies, bare lands and vegetation decreased. The built-up area expanded by 358% between 1990 and 2020, with the occupied area rising from 1.44 km 2 to 6.60 km 2 . To obtain reliable LST results, average values of LST obtained from multiple Landsat images for each year were used. The mean LST in the winter season has risen by 0.63 °C over the last 30 years. The variation in LST between separate days of the same year increased significantly, although the change in mean LST was small. Statistical analysis of land surface indicators revealed that NDVI, NDBI and NDBaI have significant explanatory power to describe LST scenarios. The explanatory power of NDBI and NDBaI to explain the rise of LST is increasing over time while the cooling capacity of NDVI is declining. LST had a moderate positive correlation with NDBI and NDBI and a weak negative correlation with NDVI. 1. Introduction Monitoring land use and land cover (LULC) change at different spatio-temporal scales is essential for assessing landscape dynamics and environmental health (Chamling and Bera, 2020). Spatio-temporal data records the dynamic change of objects or continuous events occur- ring in a specific location over time (Ansari et al., 2020). Through the construction of different types of infrastructure, urbanization is caus- ing large-scale LULC changes all across the world. (Kafy et al., 2021a; Tang et al., 2019). Population and economic growth lead to rapid urban- ization that responsible for unplanned and uncontrolled urban growth (Hua and Ping, 2018). Uncontrolled urbanization has several negative consequences, including the gradual decline of agricultural land, wa- ter bodies and vegetation around the cities which are prominent in de- veloping countries like Bangladesh (Gazi et al., 2020; Liu et al., 2015; Tang et al., 2019; Yao et al., 2017). From an urban perspective, change of land cover patterns affects the environment by influencing the transfer and flow of energy and ma- terials (Adulkongkaew et al., 2020; Arnfield, 2003; Gustafson, 1998; Turner, 2005; Zhou et al., 2011). The LULC pattern affects the ur- ban thermal environment in various ways (Fu and Weng, 2016; ∗ Corresponding author. E-mail address: farhan.urp21@gmail.com (F.A. Abir). Rinner and Hussain, 2011) and the change of land surface temperature (LST) is one of the consequences of changing LULC patterns in urban areas (Gohain et al., 2021; Mohammad et al., 2019). LST is an indica- tor of the energy balance at the land surface (Khandelwal et al., 2018) and has high spatial variability (Adams and Smith, 2014; Chaudhuri and Mishra, 2016). The LST pattern largely depends on the thermal proper- ties of different ground covers, such as thermal capacity and thermal conductivity (Walawender et al., 2014). LST often contributes to the formation of urban heat island (Kafy et al., 2020), which is responsible for deteriorating air and water quality, deteriorating human health and the spread of viral/bacterial diseases (Ahmed et al., 2013; Huang et al., 2019; Phelan et al., 2015). Nowadays, LST is extensively studied by many researchers for its great significance on urban health and sustain- able development (Wang and Murayama, 2020). Changes in LULC and LST are also examined for their effect on agricultural land and crop yield (Abd El-Hamid et al., 2020; Majumder et al., 2020; Zhang et al., 2020). Many researchers have studied the relationship between LULC and LST dynamics in different urban contexts (Aik et al., 2020; Chaudhuri and Mishra, 2016; Fu and Weng, 2016; Hua and Ping, 2018; Mohammad et al., 2019; Wang et al., 2015; Wang and Murayama, 2020; Zhou et al., 2011). Remote sensing (RS) and geographic information https://doi.org/10.1016/j.envc.2021.100167 Received 6 April 2021; Received in revised form 28 May 2021; Accepted 30 May 2021 2667-0100/© 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)