scholarly journals Fungsi Taman Kota Untuk Mitigasi Dampak Urban Heat Island di Kota Bandung

2020 ◽  
Vol 6 (1) ◽  
pp. 1-7
Author(s):  
Dian Rosleine ◽  
Arka Irfani
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Negative Impact ◽  
Mobile Station ◽  
Landsat 8 ◽  
Heat Island ◽  
Land Classification ◽  
Forest Park ◽  
Urban Heat ◽  
Forest Parks

Forest parks can take a role in mitigating negative impact of Urban Heat Island. Therefore, this study was conducted to clarify ecological function of three forest parks i.e Ganesha, Maluku, and Tegalega forest park in mitigating Urban Heat Island. Land classification and surface temperature were determined by analyzing Landsat 8 image with QGIS. Air temperature was measured by mobile station through north-south and east-west of Bandung City area. There are four types of land classification in Bandung as follows: settlements, water body, bare soil, and vegetation. In Bandung City, vegetation cover is around 20.72%; surface temperatures in the afternoon varies from 23 to 39.6°C, while during the night air temperatures varies from 20.5 to 24.9°C. Northern part of Bandung tends to have cooler air temperature due to high coverage of vegetation. Tegalega forest park can reduce temperature up to 2.6°C, while in Maluku forest park is 1.98°C and Ganesha forest park is 0.75°C. Therefore, the existence of forest parks is important in urban area because they can take a part to reduce negative impact of Urban Heat Island.  

Analisis Pengaruh Kerapatan Vegetasi Terhadap Suhu Permukaan dan Keterkaitannya Dengan Fenomena UHI

2020 ◽  
Vol 21 (1) ◽  
pp. 99
Author(s):  
Dewi Miska Indrawati ◽  
Suharyadi Suharyadi ◽  
Prima Widayani
Keyword(s):  
Urban Heat Island ◽  
Landsat 8 ◽  
Heat Island ◽  
Landsat 8 Oli ◽  
Urban Heat ◽  
Split Window Algorithm

Kota Mataram adalahpusat dan ibukota dari provinsi Nusa Tenggara Barat yang tentunya menjadi pusat semua aktivitas masyarakat disekitar daerah tersebut sehingga menyebabkan peningkatan urbanisasi. Semakin meningkatnya peningkatan urbanisasi yan terjadi di perkotaan akan menyebabkan perubahan penutup lahan, dari awalnya daerah bervegetasi berubah menjadi lahan terbangun. Oleh karena itu, akan memicu peningkatan suhu dan menyebabkan adanya fenomena UHI dikota Mataram.Tujuan dari penelitian ini untuk mengetahui hubungan kerapatan vegetasi dengan kondisi suhu permukaan yang ada diwilayah penelitian dan memetakan fenomena UHI di Kota Mataram. Citra Landsat 8 OLI tahun 2018 yang digunakan terlebih dahulu dikoreksi radiometrik dan geometrik. Metode untuk memperoleh data kerapatan vegetasi menggunakan transformasi NDVI, LST menggunakan metode Split Window Algorithm (SWA) dan identifikasi fenomena urban heat island. Hasil penelitian yang diperoleh menunjukkan kerapatan vegetasi mempunyai korelasi dengan nilai LST. Hasil korelasi dari analisis pearson yang didapatkan antara kerapatan vegetasi terhadap suhu permukaan menghasilkan nilai -0,744. Fenomena UHIterjadi di pusat Kota Mataram dapat dilihat dengan adanya nilai UHI yaitu 0-100C. Semakin besar nilai UHI, semakin tinggi perbedaan LSTnya.

scholarly journals A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform Observations

2021 ◽  
Author(s):  
Shihan Chen ◽  
Yuanjian Yang ◽  
Fei Deng ◽  
Yanhao Zhang ◽  
Duanyang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Model Framework ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
The City

Abstract. Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high spatial resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a Random Forest (RF) model. Firstly, the observed environmental parameters [e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF)] around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 °C. Then, the spatial distribution of CUHII was evaluated at 30-m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the de-creasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.

A comparative study of urban heat island effects in two Belarusian cities from satellite and ground-based observations

2021 ◽  
Author(s):  
Heorhi Burchanka ◽  
Yahor Prakopchyk ◽  
Tsimafei Schlender ◽  
Aleh Baravik ◽  
Siarhei Barodka
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
City Planning ◽  
Thermal Characteristics ◽  
Data Availability ◽  
Eastern Bloc ◽  
Temperature Fields ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat

<p>This study is devoted to analysis of urban development effects on surface thermal characteristics for the case of Belarusian cities of Minsk and Mahiloŭ. Both cities being situated on the same latitude (53.90 N) and not far from each other (~180 km distance), while also sharing a number of similar features typical for cities in Belarus (and in some other former Eastern Bloc countries as well), Minsk and Mahiloŭ nevertheless differ significantly in terms of their population, size and structure. It is therefore of interest to perform urban climate studies for these two cities in parallel.</p><p>First, we use geoinformation systems (QGIS), centralized city planning databases and Open Street Maps (OSM) vector data to implement description of Minsk and Mahiloŭ urban territories in terms of functional zones, taking into account such features as buildings density and urban area category (industrial, residential, business, recreational and other types).</p><p>Furthermore, we perform analysis of surface temperature fields for both cities from satellite data (Landsat-8) and ground-based observations, the latter including both regular meteorological stations (in urban as well as surrounding rural areas) and a volunteer network of weather and air quality sensors distributed in both cities as part of the AirMQ project [1]. We analyze observations for several months in the 2019-2021 period (depending on data availability), paying special attention to days with specific weather conditions (e.g. blocking anticyclones).</p><p>Analysis demonstrates clear evidence of significant urban heat island effects in thermal regimes of both cities, with specific areas of increased temperature related to urban zoning, industrial and green areas, buildings heights and density. However, the selected method of surface urban heat island (SUHI) detection turns out to be somewhat limited for the purposes of studying the effects of blocking anticyclones on urban heat island phenomena development, thereby calling for application of atmospheric numerical modelling techniques.</p><p>[1] AirMQ project, URL: https://airmq.by/</p>

scholarly journals Spatiotemporal Changes in the Built Environment Characteristics and Urban Heat Island Effect in a Medium-Sized City, Chiayi City, Taiwan

2020 ◽  
Vol 12 (1) ◽  
pp. 365 ◽  
Author(s):  
Jou-Man Huang ◽  
Heui-Yung Chang ◽  
Yu-Su Wang
Keyword(s):  
Population Density ◽  
Built Environment ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Area Ratio ◽  
Heat Island ◽  
Downtown Area ◽  
Green Area ◽  
Spatiotemporal Changes ◽  
Urban Heat

This study took Chiayi City—a tropical, medium-sized city—as an example to investigate the urban heat island (UHI) effect using mobile transects and built environment characteristics in 2018. The findings were compared to those from a study in 1999 to explore the spatiotemporal changes in the built environment characteristics and UHI phenomenon. The result for the UHI intensity (UHII) during the day was approximately 4.1 °C and at midnight was approximately 2.5 °C. Compared with the survey in 1999, the UHII during the day increased by approximately 1.3 °C, and the UHII at midnight decreased by approximately 1.2 °C. The trend of the spatial distribution of the increasing artificial area ratio (AAR) proved the importance of urban land use expansion on UHI. The results of the air temperature survey were incorporated with the nesting space in GIS to explore the role of built environment characteristics in UHI effects. The higher the population density (PD) and artificial area ratio (AAR) were, the closer the proximity was to the downtown area. The green area ratio (GAR) was less than 0.2 in the downtown area and increased closer to the rural areas. The built environment factors were analyzed in detail and correlated with the UHI effect. The air temperature in the daytime increased with the population density (PD) and artificial area ratio (AAR), but decreased with the green area ratio (GAR) (r = ±0.3–0.4). The result showed good agreement with previous studies.

Reflective Parking Lots for Microscale Urban Heat Island Mitigation

2020 ◽  
Vol 2674 (8) ◽  
pp. 663-671
Author(s):  
Sushobhan Sen ◽  
Juan Pablo Ricardo Mendèz-Ruiz Fernandèz ◽  
Jeffery Roesler
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Significant Proportion ◽  
Climate Index ◽  
Heat Island ◽  
Universal Thermal Climate Index ◽  
Parking Lots ◽  
Parking Lot ◽  
Thermal Climate ◽  
Urban Heat

Paved surfaces, especially parking lots, occupy a significant proportion of the horizontal surface area in cities. The low albedo of many of these parking lots contribute to the urban heat island (UHI) and affect the local microclimate around them. The albedo of six parking lots in Champaign-Urbana, U.S., was measured using a ground-based albedometer and was found to vary between 0.18 and 0.28, with a statistically significant variation in albedo at different points within each parking lot. The numerical model ENVI-met was then employed to model the microclimate around one of these lots to examine the potential of increasing its albedo to mitigate UHI. The higher albedo decreased the air temperature over the parking lot by about 1°C. Furthermore, the Universal Thermal Climate Index (UTCI), which combines the effects of air temperature, reflected radiation, wind speed, clothing, metabolism, and humidity, demonstrated that increasing the albedo of the parking lot could improve overall pedestrian thermal comfort and even eliminate it during several hours of the day, and thus mitigate the UHI effect.

scholarly journals Comparasion of NDBI and NDVI as Indicators of Surface Urban Heat Island Effect in Landsat 8 Imagery: A Case Study of Iasi

2017 ◽  
Vol 11 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Paul Macarof ◽  
Florian Statescu
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Sensing Technology ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This study compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island effects in Landsat-8 OLI imagery by investigating the relationships between the land surface temperature (LST), NDBI and NDVI. The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural areas due to urbanization. With the development of remote sensing technology, it has become an important approach to urban heat island research. Landsat data were used to estimate the LST, NDBI and NDVI from four seasons for Iasi municipality area. This paper indicates than there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI varies by season. This paper suggests, NDBI is an accurate indicator of surface UHI effects and can be used as a complementary metric to the traditionally applied NDVI.

scholarly journals Changes in the Water Temperature of Rivers Impacted by the Urban Heat Island: Case Study of Suceava City

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1343 ◽  
Author(s):  
Andrei-Emil Briciu ◽  
Dumitru Mihăilă ◽  
Adrian Graur ◽  
Dinu Iulian Oprea ◽  
Alin Prisăcariu ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Water Temperature ◽  
Urban Heat Island ◽  
River Water ◽  
Air Temperature ◽  
Stream Water ◽  
Heat Island ◽  
Urban Heat ◽  
The City ◽  
River Water Temperature

Cities alter the thermal regime of urban rivers in very variable ways which are not yet deciphered for the territory of Romania. The urban heat island of Suceava city was measured in 2019 and its impact on Suceava River was assessed using hourly and daily values from a network of 12 water and air monitoring stations. In 2019, Suceava River water temperature was 11.54 °C upstream of Suceava city (Mihoveni) and 11.97 °C downstream (Tişăuţi)—a 3.7% increase in the water temperature downstream. After the stream water passes through the city, the diurnal thermal profile of Suceava River water temperature shows steeper slopes and earlier moments of the maximum and minimum temperatures than upstream because of the urban heat island. In an average day, an increase of water temperature with a maximum of 0.99 °C occurred downstream, partly explained by the 2.46 °C corresponding difference between the urban floodplain and the surrounding area. The stream water diurnal cycle has been shifted towards a variation specific to that of the local air temperature. The heat exchange between Suceava River and Suceava city is bidirectional. The stream water diurnal thermal cycle is statistically more significant downstream due to the heat transfer from the city into the river. This transfer occurs partly through urban tributaries which are 1.94 °C warmer than Suceava River upstream of Suceava city. The wavelet coherence analyses and ANCOVA (analysis of covariance) prove that there are significant (0.95 confidence level) causal relationships between the changes in Suceava River water temperature downstream and the fluctuations of the urban air temperature. The complex bidirectional heat transfer and the changes in the diurnal thermal profiles are important to be analysed in other urban systems in order to decipher in more detail the observed causal relationships.

scholarly journals Integration of a Building Energy Model in an Urban Climate Model and its Application

2020 ◽  
Author(s):  
Luxi Jin ◽  
Sebastian Schubert ◽  
Daniel Fenner ◽  
Fred Meier ◽  
Christoph Schneider
Keyword(s):  
Temporal Variation ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Indoor Air ◽  
Climate Model ◽  
Building Energy ◽  
Energy Model ◽  
Heat Island ◽  
Energy Fluxes ◽  
Urban Heat

Abstract We report the ability of an urban canopy model, coupled with a regional climate model, to simulate energy fluxes, the intra-urban variability of air temperature, urban-heat-island characteristics, indoor temperature variation, as well as anthropogenic heat emissions, in Berlin, Germany. A building energy model is implemented into the Double Canyon Effect Parametrization, which is coupled with the mesoscale climate model COSMO-CLM (COnsortium for Small-scale MOdelling in CLimate Mode) and takes into account heat generation within buildings and calculates the heat transfer between buildings and the urban atmosphere. The enhanced coupled urban model is applied in two simulations of 24-day duration for a winter and a summer period in 2018 in Berlin, using downscaled reanalysis data to a final grid spacing of 1 km. Model results are evaluated with observations of radiative and turbulent energy fluxes, 2-m air temperature, and indoor air temperature. The evaluation indicates that the improved model reproduces the diurnal characteristics of the observed turbulent heat fluxes, and considerably improves the simulated 2-m air temperature and urban heat island in winter, compared with the simulation without the building energy model. Our set-up also estimates the spatio–temporal variation of wintertime energy consumption due to heating with canyon geometry. The potential to save energy due to the urban heat island only becomes evident when comparing a suburban site with an urban site after applying the same grid-cell values for building and street widths. In summer, the model realistically reproduces the indoor air temperature and its temporal variation.

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