Characterizing spatial and temporal deforestation and its effects on surface urban heat islands in a tropical city using Landsat time series

Carrillo-Niquete, Gerardo A.; Andrade, José Luís; Valdez-Lazalde, José René; Reyes‐García, Casandra; Hernández‐Stefanoni, José Luis

doi:10.1016/j.landurbplan.2021.104280

Cited by 30 publications

(18 citation statements)

References 60 publications

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“…For UFS, in 2022, Carrillo-Niquete et al used a Landsat image series to analyze annual deforestation (from 2000 to 2018) in Mérida (a tropical city in the Yucatan), comparing the land surface temperature before and after deforestation, which showed that the land surface temperature had increased significantly after deforestation, and urban heat islands mainly occurred in the deforested areas [42]. In 2021, Lin et al studied the relationship between the spatial structure and thermal comfort of a bamboo forest with four distinct seasons at the micro-scale level in Dujiangyan City, China, using Rayman software to calculate the physiological equivalent temperature, which showed that modifying the forest structure (cover plant ratio, canopy diameter width, degree of facing the sun's trajectory vertically, etc.)…”

Section: Gi Ups Ufs Uts Gr Gw Referencementioning

confidence: 99%

“…For UFS, in 2022, Carrillo-Niquete et al noted that after a deforested area of 5413 ha in Mérida, Mexico, the land surface temperature increased by 2.36-3.94 °C and was significantly (p < 0.05) higher (0.90 °C) than in non-deforested sites [42]. Richards et al (2020) showed that secondary forest was associated with the largest temperature reduction (−1.7 °C) [56], and in 2019, Joseph et al showed that the urban forests in inner London provide a cooling benefit of 7.0-10.6 GWh, for savings equal to £1.23 million per year [58].…”

Section: Benefits and Valuesmentioning

confidence: 99%

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A Comprehensive Review of Different Types of Green Infrastructure to Mitigate Urban Heat Islands: Progress, Functions, and Benefits

Shao

Kim

2022

Land

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Climate change and rapid urbanization increase/amplify urban heat islands (UHIs). Green infrastructure (GI) is an effective and popularly strategy used to moderate UHIs. This paper aims to better understand the progress of different GI types (urban parks, urban forests, street trees, green roofs, green walls) in mitigating UHIs, and what benefits they provide. Firstly, this paper used CiteSpace to analyze 1243 publications on the Web of Science from 1990 to 2021, then analyzed the function/regulation of ecosystem services/benefits and values of GI types in reducing UHIs. The historical review results show that research on all GI types showed rapid growth since 2013, and their GR increased rapidly. The highest-ranking keywords were urban heat island/heat island, climate/climate change/microclimate, and temperature/land surface temperature/air temperature. “Design,” “vegetation,” “quality,” and “reduction” are the top four strongest keyword bursts. The most published countries are the People’s Republic of China, USA, Australia, Germany, and Italy, and the top three institutions are the Chinese Academy of Sciences, Arizona State University, and the National University of Singapore. Landscape and Urban Planning, Building and Environment, Energy and Building, and Urban Forestry and Urban Greening are the most published journals. In urban areas, different GI types as a form of ecosystem hardware provide multiple functions (reduced land surface temperatures, lower building energy usage, improved thermal comfort and enhanced human health, reduced morbidity and mortality, etc.). GI thus provides a regulated ecosystem service to ameliorate UHIs primarily through temperature regulation and shade. At the same time, GI provides benefits and values (ecological, economic, social, and cultural) to humans and urban sustainable development. GI types determine the functions they provide, afford corresponding regulated ecosystem services, and provide benefits and values in a logical/recycle system. Overall, this review highlights the development and importance of GI, as well as the relationship of GI types and functions of regulating the ecosystem service benefits and values to mitigate UHI, and advances the study of climate change adaptation in cities.

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Section: Gi Ups Ufs Uts Gr Gw Referencementioning

confidence: 99%

Section: Benefits and Valuesmentioning

confidence: 99%

A Comprehensive Review of Different Types of Green Infrastructure to Mitigate Urban Heat Islands: Progress, Functions, and Benefits

Shao

Kim

2022

Land

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“…A key in SUHI research is the calculation of land surface temperature (LST). At present, the LST calculations are mainly obtained by inversion of the thermal infrared band of satellites; common data sources include Landsat (Yang et al, 2021c;Kamali Maskooni et al, 2021;Najafzadeh et al, 2021;Carrillo-Niquete et al, 2022) and moderate resolution imaging spectroradiometer (MODIS) (Li et al, 2020;Mohammad and Goswami, 2021a;Niu et al, 2021). The lower resolution of MODIS data is more suitable for mesoscale research, whereas the resolution of Landsat data is 30 m, more suitable for urban scale research.…”

Section: Introductionmentioning

confidence: 99%

Seasonal differences in the dominant factors of surface urban heat islands along the urban-rural gradient

Xin

Yang

Wang

et al. 2022

Front. Environ. Sci.

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Urbanization has been accelerating; hence the effect of urban heat island (UHI) has increased. There has been extensive research on spatiotemporal UHI changes and drivers, however, data on the dominant seasonal factors of UHIs and the differences along urban-rural gradients remain limited. Based on Luojia-1A, Landsat 8, and moderate resolution imaging spectroradiometer (MODIS) data, we assessed the seasonal differences in surface UHI (SUHI), normalized differences in vegetation index (NDVI), built-up index (NDBI), and water index (NDWI) and their relationships in the Dalian City, Northeast China. We found that in the urban built-up area, the mean SUHI intensity (SUHII) decreased from that in summer (2.74°C) > autumn (1.65°C) > winter (0.28°C) > spring (−0.79°C). SUHII was more strongly affected by NDWI and NDBI than NDVI, and NDBI and NDWI showed positive and negative correlations with SUHII in different seasons, while NDVI and SUHII were positively correlated in spring and negatively correlated in the other seasons. When analyzing the dominant factors of SUHII, the importance results showed that, in spring, NDBI > NDVI > NDWI, in autumn, NDVI > NDWI > NDBI, in summer and winter, NDWI > NDVI > NDBI. In addition, SUHII changed the most in summer along the urban-rural gradient, decreasing from 2.74°C to −2.74°C. Among these indicators, except for spring NDVI which increased from 0.09 to 0.59 with distance from built-up areas, there was minimal change in NDVI, NDBI, and NDWI along the urban-rural gradient in other seasons (i.e., all were within 0.2). In this study, the difference analysis of SUHI and remote sensing indices along the urban-rural gradient can help to facilitate the rational layout of cities.

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“…Diversos são os estudos que tem adotado as imagens de sensoriamento remoto para análise de temperaturas de superfícies em áreas urbanas (CARRILLO-NIQUETE, 2017;KAPLAN et al, 2018;CAMACHO e MOSCHINI, 2021). Segundo Kamran et al (2015) o sensoriamento remoto no infravermelho térmico (TIR) fornece um método único para a obtenção de informações da TST, uma vez que a maior parte da energia detectada pelo sensor nesta região espectral é emitida diretamente pela superfície terrestre.…”

Section: Introductionunclassified

Influência da Infraestrutura de Transportes sobre a Temperatura de Superfície em um corredor BRT, na cidade de Goiânia/GO

2022

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A artificialização em áreas urbanas contribuem para concentração de problemas ambientais diversos, dentre os quais, a alteração do microclima urbano, incluindo a temperatura da superfície terrestre. Assim, a presente pesquisa tem como objetivo analisar os impactos da construção de um Sistema Bus Rapid Transit (BRT), localizado na cidade de Goiânia, sobre a temperatura da superfície terrestre, antes e após a sua implantação. A metodologia contemplou a análise de imagens de sensoriamento remoto orbital do satélite Landsat 8, sensores OLI e TIRS, manipuladas em um Sistema de Informação Geográfica (SIG). Para tanto, foram necessários o cálculo da temperatura de brilho; correção da emissividade e; a temperatura da superfície terrestre. Os resultados revelam como a alteração da paisagem urbana, influenciada pelo corredor de transportes, é uma das principais causas das mudanças de temperatura da superfície terrestre (TST), mostrando a intensificação de altas temperaturas em áreas onde houve o aumento de superfícies pavimentadas e comerciais, e redução da temperatura onde empregou-se manejos de arborização. Palavras-chave: Uso da Terra. Impacto ambiental. Transportes. Microclima.

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Characterizing spatial and temporal deforestation and its effects on surface urban heat islands in a tropical city using Landsat time series

Cited by 30 publications

References 60 publications

A Comprehensive Review of Different Types of Green Infrastructure to Mitigate Urban Heat Islands: Progress, Functions, and Benefits

A Comprehensive Review of Different Types of Green Infrastructure to Mitigate Urban Heat Islands: Progress, Functions, and Benefits

Seasonal differences in the dominant factors of surface urban heat islands along the urban-rural gradient

Influência da Infraestrutura de Transportes sobre a Temperatura de Superfície em um corredor BRT, na cidade de Goiânia/GO

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