scholarly journals Monitoring the Impact of Land Cover Change on Surface Urban Heat Island through Google Earth Engine: Proposal of a Global Methodology, First Applications and Problems

2018 ◽  
Vol 10 (9) ◽  
pp. 1488 ◽  
Author(s):  
Roberta Ravanelli ◽  
Andrea Nascetti ◽  
Raffaella Cirigliano ◽  
Clarissa Di Rico ◽  
Giovanni Leuzzi ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Urban Heat Island ◽  
Landsat Imagery ◽  
Google Earth ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Google Earth Engine ◽  
Spatio Temporal

All over the world, the rapid urbanization process is challenging the sustainable development of our cities. In 2015, the United Nation highlighted in Goal 11 of the SDGs (Sustainable Development Goals) the importance to “Make cities inclusive, safe, resilient and sustainable”. In order to monitor progress regarding SDG 11, there is a need for proper indicators, representing different aspects of city conditions, obviously including the Land Cover (LC) changes and the urban climate with its most distinct feature, the Urban Heat Island (UHI). One of the aspects of UHI is the Surface Urban Heat Island (SUHI), which has been investigated through airborne and satellite remote sensing over many years. The purpose of this work is to show the present potential of Google Earth Engine (GEE) to process the huge and continuously increasing free satellite Earth Observation (EO) Big Data for long-term and wide spatio-temporal monitoring of SUHI and its connection with LC changes. A large-scale spatio-temporal procedure was implemented under GEE, also benefiting from the already established Climate Engine (CE) tool to extract the Land Surface Temperature (LST) from Landsat imagery and the simple indicator Detrended Rate Matrix was introduced to globally represent the net effect of LC changes on SUHI. The implemented procedure was successfully applied to six metropolitan areas in the U.S., and a general increasing of SUHI due to urban growth was clearly highlighted. As a matter of fact, GEE indeed allowed us to process more than 6000 Landsat images acquired over the period 1992–2011, performing a long-term and wide spatio-temporal study on SUHI vs. LC change monitoring. The present feasibility of the proposed procedure and the encouraging obtained results, although preliminary and requiring further investigations (calibration problems related to LST determination from Landsat imagery were evidenced), pave the way for a possible global service on SUHI monitoring, able to supply valuable indications to address an increasingly sustainable urban planning of our cities.

ANALISIS SURFACE URBAN HEAT ISLAND MENGGUNAKAN TEKNIK PENGINDERAAN JAUH BERBASIS CLOUD COMPUTING PADA GOOGLE EARTH ENGINE DI KOTA SAMARINDA

2021 ◽  
pp. 75
Author(s):  
Bayu Elwantyo Bagus Dewantoro ◽  
Pavita Almira Natani ◽  
Zumrotul Islamiah
Keyword(s):  
Cloud Computing ◽  
Urban Heat Island ◽  
Google Earth ◽  
Landsat 8 ◽  
Heat Island ◽  
Landsat 8 Oli ◽  
Boundary Analysis ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Google Earth Engine

Peningkatan intensitas pembangunan fisik dan sosial di kawasan perkotaan Samarinda sebagai indikator kemajuan suatu kawasan perkotaan secara tidak langsung berdampak terhadap stabilitas kondisi atmosfer. Fenomena urban heat island sebagai turunan dari dinamika iklim mikro perkotaan sebagai dampak dari pembangunan fisik dan sosial tersebut semakin meluas, sehingga kebutuhan akan teknik monitoring yang efektif dan efisien menjadi sangat penting. Penginderaan jauh mampu melakukan pemantauan dan deteksi titik panas dalam rangka mitigasi dan pengendalian efek urban heat island dalam cakupan wilayah yang luas dengan waktu singkat. Penelitian ini berfokus pada kajian surface urban heat island (SUHI) yang bertujuan untuk mengetahui distribusi spasial intensitas SUHI di Kota Samarinda. Metode yang digunakan pada penelitian ini berupa integrasi teknik penginderaan jauh dan cloud computing pada Google Earth Engine menggunakan band termal citra Landsat 8 OLI/TIRS serta analisis statistik citra menggunakan Buffer Boundary Analysis untuk identifikasi potensi terjadinya SUHI di Kota Samarinda. Ekstraksi suhu permukaan diperoleh dari persamaan Planck yang diintegrasikan dengan koreksi atmosfer untuk koreksi emisivitas permukaan menggunakan syntax dengan bahasa Javacript pada Google Earth Engine. Hasil pengolahan menunjukkan adanya potensi SUHI dengan intensitas tinggi dengan nilai 3,001-6,000°C pada radius 5 km dari pusat kota dan intensitas semakin turun seiring radius yang semakin jauh dari pusat kota. Secara administratif, intensitas SUHI tertinggi relatif berada pada kecamatan Samarinda Kota, Samarinda Ilir, dan Samarinda Seberang dengan rentang intensitas SUHI sebesar 1,5001-6,000°C, sementara intensitas SUHI terendah relatif berada pada kecamatan Sungai Kunjang dan Palaran dengan rentang intensitas SUHI sebesar -10,000-1,500°C.

scholarly journals Spatial and Temporal Analysis of Surface Urban Heat Island and Thermal Comfort Using Landsat Satellite Images between 1989 and 2019: A Case Study in Tehran

2021 ◽  
Vol 13 (21) ◽  
pp. 4469
Author(s):  
Faezeh Najafzadeh ◽  
Ali Mohammadzadeh ◽  
Arsalan Ghorbanian ◽  
Sadegh Jamali
Keyword(s):  
Thermal Comfort ◽  
Urban Heat Island ◽  
Temporal Variations ◽  
Google Earth ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
Spatio Temporal ◽  
The City

Mapping and monitoring the spatio-temporal variations of the Surface Urban Heat Island (SUHI) and thermal comfort of metropolitan areas are vital to obtaining the necessary information about the environmental conditions and promoting sustainable cities. As the most populated city of Iran, Tehran has experienced considerable population growth and Land Cover/Land Use (LULC) changes in the last decades, which resulted in several adverse environmental issues. In this study, 68 Landsat-5 and Landsat-8 images, collected from the Google Earth Engine (GEE), were employed to map and monitor the spatio-temporal variations of LULC, SUHI, and thermal comfort of Tehran between 1989 and 2019. In this regard, planar fitting and Gaussian Surface Model (GSM) approaches were employed to map SUHIs and derive the relevant statistical values. Likewise, the thermal comfort of the city was investigated by the Urban Thermal Field Variance Index (UTFVI). The results indicated that the SUHI intensities have generally increased throughout the city by an average value of about 2.02 °C in the past three decades. The most common reasons for this unfavorable increase were the loss of vegetation cover (i.e., 34.72%) and massive urban expansions (i.e., 53.33%). Additionally, the intra-annual investigations in 2019 revealed that summer and winter, with respectively 8.28 °C and 4.37 °C, had the highest and lowest SUHI magnitudes. Furthermore, the decadal UTFVI maps revealed notable thermal comfort degradation of Tehran, by which in 2019, approximately 52.35% of the city was identified as the region with the worst environmental condition, of which 59.94% was related to human residents. Additionally, the relationships between various air pollutants and SUHI intensities were appraised, suggesting positive relationships (i.e., ranging between 0.23 and 0.43) that can be used for establishing possible two-way mitigations strategies. This study provided analyses of spatio-temporal monitoring of SUHI and UTFVI throughout Tehran that urban managers and policymakers can consider for adaption and sustainable development.

scholarly journals Satellite Based Analysis of Surface Urban Heat Island Intensity

2016 ◽  
Vol 9 (1-2) ◽  
pp. 23-30 ◽  
Author(s):  
Orsolya Gémes ◽  
Zalán Tobak ◽  
Boudewijn van Leeuwen
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Urban Climate ◽  
Seasonal Development ◽  
Heat Island ◽  
Early Afternoon ◽  
Local Climate Zones ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract The most obvious characteristics of urban climate are higher air and surface temperatures compared to rural areas and large spatial variation of meteorological parameters within the city. This research examines the long term and seasonal development of urban surface temperature using satellite data during a period of 30 years and within a year. The medium resolution Landsat data were (pre)processed using open source tools. Besides the analysis of the long term and seasonal changes in land surface temperature within a city, also its relationship with changes in the vegetation cover was investigated. Different urban districts and local climate zones showed varying strength of correlation. The temperature difference between urban surfaces and surroundings is defined as surface urban heat island (SUHI). Its development shows remarkable seasonal and spatial anomalies. The satellite images can be applied to visualize and analyze the SUHI, although they were not collected at midday and early afternoon, when the phenomenon is normally at its maximum. The applied methodology is based on free data and software and requires minimal user interaction. Using the results new urban developments (new built up and green areas) can be planned, that help mitigate the negative effects of urban climate.

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