Relationship between land use/cover and surface temperatures in the urban agglomeration of Cuiabá-Várzea Grande, Central Brazil

Callejas, Ivan Júlio Apolônio

doi:10.1117/1.3666044

Cited by 25 publications

(19 citation statements)

References 24 publications

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“…For UHI studies, the LST and vegetation index relationship has been utilized by several authors [19,53] to understand the role of LST in urban development and vegetation coverage dynamic assessment. The LST obtained from satellite imagery is, strictly speaking, a measure of the "skin temperature" or surface radiometric energy (kinetic) emitted from the land surface and is related to the thermal infrared (TIR) radiation rather than air temperature [36,41], which is more commonly used in physiological studies [50].…”

Section: Lst and Biophysical Descriptorsmentioning

confidence: 99%

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Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management

Gusso

Cafruni

Bordin³

et al. 2015

Sustainability

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For a reliable assessment of sustainability in big cities, it is imperative to evaluate urban ecosystem conditions and the environment of the cities undergoing economic growth. Urban green spaces are valuable sources of evapotranspiration, which is generated by trees and vegetation; these spaces mitigate urban heat islands in cities. Land surface temperature (LST) is closely related to the distribution of land-use and land-cover characteristics and can be used as an indicator of urban environment conditions and development. This study evaluates the patterns of LST distribution through time by employing the thermal spatial distribution signature procedure using thermal infrared data obtained from Landsat-5 Thematic Mapper. A set of 18 images, between 1985 and 2010, OPEN ACCESSSustainability 2015, 7 3130 was used to study the urban environment during summer in 47 neighborhoods of Porto Alegre, Brazil. On a neighborhood scale, results show a non-linear inverse correlation (R² = 0.55) between vegetation index and LST. The overall average of the LST is 300.23 K (27.8 C) with a standard deviation of 1.25 K and the maximum average difference of 2.83 K between neighborhoods. Results show that the Thermal Spatial Distribution Signature (TSDS) analysis can help multi-temporal studies for the evaluation of UHI through time.

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Section: Lst and Biophysical Descriptorsmentioning

confidence: 99%

“…The Landsat data series satellites have collected several years of data in the thermal spectral band and have been used in several studies on UHI [19]. For the reliable assessment of sustainability in big cities, it is imperative to evaluate urban ecosystem conditions and the environment for cities undergoing economic growth.…”

Section: Introductionmentioning

confidence: 99%

Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management

Gusso

Cafruni

Bordin³

et al. 2015

Sustainability

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“…[6][7][8][9] In particular, special attention has been given to large cities and urban agglomerations at the global level. [10][11][12][13][14] For example, Weng produced land use and land cover maps for 1989, 1994, and 1997 from Landsat TM images and analyzed the process of urban agglomerations of the Zhujiang Delta, China. 10 Griffiths et al developed an approach to mapping urban growth from multisensor data and applied it to the Dhaka megacity region in Bangladesh between 1990 and 2006.…”

Section: Introductionmentioning

confidence: 99%

Monitoring bidecadal development of urban agglomeration with remote sensing images in the Jing-Jin-Tang area, China

Guo

Wang

et al. 2014

J. Appl. Remote Sens

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Abstract. As an important urban agglomeration of China, the Jing-Jin-Tang area has experienced intense urbanization since the 1980s. This study explores the spatiotemporal dynamics of urban areas in this region using multitemporal Landsat images. An enhanced built-up (BU) index method was applied to extract BU areas with an overall accuracy ranging from 75% to 91.35%. Seven spatial metrics were used to discern urban growth patterns at city and county levels. The results indicate that all cities witnessed a rapid growth of BU areas with different spatial patterns. Beijing has been aggregating since the 1990s and a large homogeneous urban patch has formed. The construction and development of metropolitan Beijing and Tianjin started in the early 1980s and became almost fully developed by the end of 1990. Tangshan, like many medium-sized cities in China, is still enduring a development process with an accelerating pace. The metropolitan areas of Beijing and Tianjin have been greatly developed with BU densities exceeding 90% since 2000, compared with Tangshan's 55% in 2010. These results provide spatial information on the evolution of urban extent in the period of 1990s to 2010s in this region.

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“…The Landsat data series satellites have collected several years of data in the thermal spectral band and have been used in several studies for UHI [41]. However, the challenge in urban environmental LST estimation is the numerous factors that need to be quantified in order to assess accurate LST retrieval from thermal satellite data.…”

Section: Satellite Imagery and Data Setmentioning

confidence: 99%

Income Driven Patterns of the Urban Environment

et al. 2017

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This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation-Impervious-Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1.263 million in 1991 to 1.409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R 2 between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics.

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Relationship between land use/cover and surface temperatures in the urban agglomeration of Cuiabá-Várzea Grande, Central Brazil

Cited by 25 publications

References 24 publications

Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management

Multi-Temporal Patterns of Urban Heat Island as Response to Economic Growth Management

Monitoring bidecadal development of urban agglomeration with remote sensing images in the Jing-Jin-Tang area, China

Income Driven Patterns of the Urban Environment

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