A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy

Abstract

Abstract:The Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the anthropic causes of UHI. The UHI phenomenon has a negative impact on the life quality of the local population (thermal discomfort, summer thermal shock, etc.), thus investigations and analyses on this topic are really useful and important for correct and sustainable urban planning; this study is included in this context. A multi-temporal analysis was performed in the municipality of Modena (Italy) to identify and estimate the Surface Urban Heat Island (SUHI, strictly correlated to the UHI phenomenon) from 2014 to 2017. For this purpose, Landsat-8 satellite images were processed with Quantum Geographic Information System (QGIS) to obtain the Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). For every pixel, LST and NDVI values of three regions of interest (ROI, i.e., Countryside, Suburbs, and City Center) were extracted and their correlations were investigated. A maximum variation of 6.4 • C in the LST values between City Center and Countryside was highlighted, confirming the presence of the SUHI phenomenon even in a medium-sized municipality like Modena. The implemented procedure demonstrates that satellite data are suitable for SUHI identification and estimation, therefore it could be a useful tool for public administration for urban planning policies.Keywords: urban heat island; land surface temperature; remote sensing; Landsat-8; semi-automatic classification plugin; QGIS; global warming; urbanization BackgroundAbout half of the world population lives in urban areas [1]. The global urbanization rate is expected to increase by 70% compared to the current world population [2], both because of the continued emergence of new urban areas [3] and because of the constant population migration from rural to urban and suburban areas [4,5]. It is not therefore surprising that the negative impacts of urbanization are an ever-growing global concern [6-10]. Urbanization has a negative impact on the environment, mainly due to pollution, changes in the physical and chemical properties of the atmosphere, and in the type of cover of the soil surface [11]. These phenomena lead to so-called Urban Heat Islands (UHI), namely urban areas where the atmospheric temperature is significantly higher than that in the surrounding rural areas [12]. The presence of UHIs is an increasing phenomenon studied by the international scientific community because of its dangerous and significant effects. In fact, the temperature increase has effects on the environment (higher temperatures cause higher energy consumption, photochemical smog, and worsening of the air quality), on the climate and on human health [13][14][15][16].

Impact of Urban Surface Characteristics and Socio-Economic Variables on the Spatial Variation of Land Surface Temperature in Lagos City, Nigeria

“…The value of the NDVI is ranging between −1 to 1. Its higher positive value denotes dense vegetation, and its low positive value represents bare soil or built-up areas, while its minors or its value closer to zero are linked to water [37][38][39]. The NDVI is calculated with Equation 9as follows,…”

“…Moreover, the green surface is gradually increased from the city midpoint to the country side expecting the small fluctuation along the gradient zones. The scientific literature [37] reveals that lower LSTs can be frequently found in the area where NDVI is high, and upper LSTs customarily represent the opposite of this scenario; this could be clearly examined in Lagos City through the urban-rural gradient analysis. Fast expansion of Lagos City has led to significant and irreversible deviations in the land use pattern and its characteristics with the increase of SUHI [5].…”

The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model

“…derived from thermal infrared remote sensing imagery [11,12] becomes effective in interpreting UHI effect because it provides a relatively rapid and low-cost data information on landscape scale. Currently, numerous studies have been conducted to deal with the spatial characteristics, changing trends and impact factors of UHI effect based on remote sensing data and geographic information systems (GIS) technology [13][14][15][16][17]. Among the above, the relationships between LST and related indicators become a hot topic that attracts wide-ranging research because these related findings have great significance to formulate urban planning policies to relieve UHI effect.…”

Prediction of Land Cover and Land Surface Temperature in Kuta Selatan Sub-district, Bali Province

“…Some focus on distribution patterns and their relationship to land cover using Landsat image data [4]- [6]. Several studies have examined Urban Heat Island (UHI) in urban and rural areas from LST analysis [7]- [9]. LST and land cover predicted for the future have also been carried out by several researchers involving the CA-Markov model, Multi-Layer Perception Markov, and Stochastic Markov [10]- [16].…”