scholarly journals THE RELATIONSHIP BETWEEN NORMALIZED DIFFERENCE VEGETATION INDEX AND CANOPY TEMPERATURE THAT AFFECTS THE URBAN HEAT ISLAND PHENOMENON

2020 ◽  
Vol 15 (2) ◽  
pp. 222-234
Author(s):  
Tissadee PROHMDIREK ◽  
Poramate CHUNPANG ◽  
Teerawong LAOSUWAN
Keyword(s):  
Urban Heat Island ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Temperature ◽  
Heat Island ◽  
Urban Heat ◽  
The Relationship

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 The localization of urban heat island in the Katowice conurbation (Poland) using the combination of land surface temperature, Normalized Difference Vegetation Index and Normalized Difference Built-up Index

2021 ◽  
Vol 94 (1) ◽  
pp. 111-129
Author(s):  
Ádám Nádudvari
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
High Surface ◽  
Temperature Measurements ◽  
Heat Island ◽  
Urban Heat

The localization of Surface Urban Heat Island (SUHI) as a potential heat risk for the urban population was evaluated. The paper aimed to propose an approach to quantify and localize (SUHI) based on Landsat series TM, ETM+, OLI satellite imageries from the period 1996-2018 and recognize the Atmospheric Urban Heat Island (AUHI) effects from long term temperature measurements. Using the theoretical relation between the Normalized Difference Built-up Index (NDBI), the Normalized Difference Vegetation Index (NDVI) and the LST (Land Surface Temperature), SUHIintensity and SUHIrisk maps were created from the combination of LST, NDVI, NDBI using threshold values to localize urban heat island in the Katowice conurbation. Negative values of SUHI intensity characterize areas where there is no vegetation, highly built-up areas, and areas with high surface temperatures. The urban grow – revealed from SUHI – and global climate change are acting together to strengthen the global AUHI effect in the region as the temperature measurements were indicated.

scholarly journals Hubungan Kerapatan Vegetasi dan Bangunan terhadap UHI (Urban Heat Island) di Kota Magelang

Ruang ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 83
Author(s):  
Febriyan Riyadi ◽  
Sri Rahayu
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Least Square ◽  
Heat Island ◽  
Ordinary Least Square ◽  
Urban Heat

Urban Heat Island (UHI) adalah fenomena dimana suatu wilayah perkotaan lebih panas daripada wilayah disekitarnya. Faktor utama yang mempengaruhi terjadinya UHI adalah terjadinya konversi tutupan lahan vegetasi menjadi daerah terbangun akibat perkembangan kota. Hal tersebut mengakibatkan peningkatan suhu permukaan, dikarenakan kerapatan vegetasi yang berkurang dan meningkatnya kerapatan bangunan. Analisis yang digunakan adalah klasifikasi tak terbimbing untuk melihat perubahan tutupan lahan, analisis NDVI (Normalized Difference Vegetation Index) untuk mengetahui perubahan vegetasi, analisis NDBI (Normalized Difference Vegetation Index) untuk mengetahui perubahan kerapatan bangunan, serta menggunakan LST (Land Surface Temperature) untuk mengetahui suhu permukaan suatu kota dan OLS (Ordinary Least Square) merupakan permodelan regresi berganda pada aplikasi ArcGis  digunakan untuk mengetahui hubungan antar variabel tersebut. Hasil dalam penelitian ini menunjukkan bahwa suhu rata-rata Kota Magelang pada tahun 2000 sebesar 22,58°C meningkat menjadi 27,11°C pada tahun 2016. Artinya suhu rata-rata Kota Magelang mengalami kenaikan sebesar 4,53°C. Hubungan antara kerapatan bangunan (x1) dan kerapatan vegetasi (x2) terhadap suhu permukaan (y) diketahui melalui formula OLS yang dihasilkan yaitu Y= 5,61 X1 – 1,34 X2 + 2,4.Hal ini berarti jika kerapatan bangunan meningkat dan kerapatan vegetasi berkurang, maka suhu permukaan meningkat.

scholarly journals Urban Heat Island in Kathmandu, Nepal: Evaluating Relationship between NDVI and LST from 2000 to 2018

2019 ◽  
Vol 8 (1) ◽  
pp. 17-29
Author(s):  
Bijesh Mishra ◽  
Jeremy Sandifer ◽  
Buddhi Raj Gyawali
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Surface Characteristics ◽  
Heat Island ◽  
Rate Of Increase ◽  
Urban Heat

The term “urban heat island” (UHI) describes increased surface and atmospheric temperatures in an urban core relative to surrounding non-urbanized areas. Although the phenomenon has been studied to a great extent throughout the world, it is less understood for Kathmandu, Nepal. This study used the Moderate Resolution Imaging Spectro-radiometer (MODIS) 8-day product (MOD11A2) to evaluate land surface temperatures (LSTs), the MODIS-derived Normalized Difference Vegetation Index (NDVI) 16-day product (MOD13Q1) to quantify land surface characteristics, and the MODIS annual land cover classification product (MCD12Q1) to identify major land cover classes. We evaluated the spatial correlation between significant changes in LSTs and NDVI between 2000–2018. Overall, urban (permanently developed areas) LSTs were consistently greater than non-urban (forests and dynamic agriculture lands) LSTs; however, the rate of increase in temperature was higher outside the central Kathmandu developed urban area. Furthermore, significant changes in NDVI values over time were more widespread and not always spatially coincident with significant changes in LST values, particularly for forested land areas. These results provide insight into systematic planning of open and green areas, construction of new infrastructure in peripheral areas, and highlight the challenges in applying traditional UHI conceptual models to rapidly developing urban areas such as Kathmandu, Nepal.

scholarly journals The Use of Land Cover Indices for Rapid Surface Urban Heat Island Detection from Multi-Temporal Landsat Imageries

2021 ◽  
Vol 10 (6) ◽  
pp. 416
Author(s):  
Nagihan Aslan ◽  
Dilek Koc-San
Keyword(s):  
Land Cover ◽  
Urban Heat Island ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Heat Island ◽  
Landsat Images ◽  
Multi Temporal ◽  
Urban Heat ◽  
Surface Urban Heat Island

The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period.

scholarly journals The Urban Heat Island in an Urban Context: A Case Study of Mashhad, Iran

2019 ◽  
Vol 16 (3) ◽  
pp. 313 ◽  
Author(s):  
Marzie Naserikia ◽  
Elyas Asadi Shamsabadi ◽  
Mojtaba Rafieian ◽  
Walter Leal Filho
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Weather Conditions ◽  
Heat Island ◽  
Urban Heat ◽  
Semi Arid

In this study, the spatio-temporal changes of urban heat island (UHI) in a mega city located in a semi-arid region and the relationships with normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) are appraised using Landsat TM/OLI images with the help of ENVI and ArcGIS software. The results reveal that the relationships between NDBI, NDVI and land surface temperature (LST) varied by year in the study area and they are not suitable indices to study the land surface temperature in arid and semi-arid regions. The study also highlights the importance of weather conditions when appraising the relationship of these indices with land surface temperature. Overall, it can be concluded that LST in arid and steppe regions is most influenced by barren soil. As a result, built-up areas surrounded by soil or bituminous asphalt experience higher land surface temperatures compared to densely built-up areas. Therefore, apart from setting-up more green areas, an effective way to reduce the intensity of UHI in these regions is to develop the use of cool and smart pavements. The experiences from this paper may be of use to cities, many of which are struggling to adapt to a changing climate.

scholarly journals MODEL KEKRITISAN INDEKS LINGKUNGAN DENGAN ALGORITMA URBAN HEAT ISLAND DI KOTA SEMARANG

2017 ◽  
Vol 19 (1) ◽  
pp. 45 ◽  
Author(s):  
Bandi Sasmito ◽  
Andri Suprayogi
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat ◽  
Criticality Index

<p align="center"> <strong>ABSTRAK</strong></p><p class="JudulABSInd"><span lang="IN"> </span></p><p class="abstrak"><span lang="IN">Pembangunan infrastruktur di Kota Semarang berkembang sangat pesat sebagai pusat bisnis, ekonomi, industri, hiburan, dan pendidikan. Pembangunan memberikan dampak positif bagi masyarakat kota, namun terdapat juga dampak negatif yang terjadi yaitu penurunan kualitas lingkungan. Meningkatnya suhu udara adalah salah satu dampak dari penurunan kualitas lingkungan. Puncak atap dan dinding dari gedung bertingkat, tempat parkir, jalan, dan trotoar cenderung memiliki albedo yang rendah. Permukaan rendah albedo menyerap energi panas radiasi matahari lebih tinggi dari objek sekitarnya. Akibatnya, jumlah kelebihan energi panas menumpuk di sekitarnya menjadi pulau-pulau panas atau <em>Urban Heat Island</em> (UHI). Penelitian ini bertujuan untuk mendeteksi terjadinya fenomena kekritisan lingkungan akibat UHI dengan menganalisis suhu permukaan dan sebaran vegetasi di wilayah studi. Ada dua langkah metode dalam penelitian ini, pertama adalah membuat peta sebaran suhu permukaan tanah dan peta sebaran kerapatan vegetasi di tahun 2013 sampai 2016. Peta suhu permukaan dibuat dengan model algoritma <em>Land Surface Temperature</em> (LST) dan sebaran vegetasi adalah dengan algoritma <em>Normalized Difference Vegetation Index</em> (NDVI). LST didapatkan dengan mengolah Citra Landsat-8 band TIRS (<em>Thermal Infrared Red Sensor</em>), sedangkan NDVI  didapatkan dengan mengolah Citra Landsat-8 band OLI (<em>Operation Land Imager</em>). Langkah kedua adalah membuat peta kekritisan lingkungan dengan algoritma ECI (<em>Environmental Criticality Index</em>). ECI didapatkan dari nilai LST dibagi NDVI yang direntangkan histogram spektralnya menjadi 8 bit. </span>Melalui<span lang="IN"> hasil penelitian ini dapat disimpulkan bahwa suhu permukaan di Kota Semarang meningkat dan sebaran kelas suhu tinggi meluas setiap tahun. Kekritisan lingkungan akibat UHI terdeteksi di pusat kota, yaitu wilayah Utara Kota Semarang.</span></p><p class="abstrak"><strong><span lang="IN">Kata kunci</span></strong><span lang="IN">: </span><em><span lang="IN">Urban Heat Island</span></em><span lang="IN"> (UHI), </span><em><span lang="IN">Land Surface Temperature</span></em><span lang="IN"> (LST), <em>Normalized Difference Vegetation Index</em> (NDVI)</span><span lang="IN">, </span><em><span lang="IN">Environmental Criticality Index</span></em><span lang="IN"> (ECI)</span></p><p align="center"><strong><br /></strong></p><p align="center"><strong><em>ABSTRACT</em></strong></p><p class="Abstrakeng">Infrastructure in Semarang City developes rapidly as a center of business, economics, industry, entertainment, and education. Development gives positive impact to citizen, however environmental degradation as the negative impact also occured. Temperatures rising is one of environmental degradation impact. Roof top and wall of a building, parking lot, road, and sidewalk tend to have a low albedo. The low surface albedo absorbs thermal energy from solar radiation higher than the surrounding objects. As a result, the amount of excess heat accumulate in the vicinity into heat islands or Urban Heat Island (UHI). This study aims to detect the occurrence of environmental criticality due to UHI phenomenon by analyzing the surface temperature and the distribution of vegetation in the study area. There are two steps in this research, first step is to create land surface temperature distribution map and vegetation density distribution map in the year of 2013 to 2016. The surface temperature map created by Land Surface Temperature (LST) algorithm model and vegetation distribution created by Normalized Difference Vegetation Index (NDVI) algorithm. LST is obtained by processing Landsat-8 band TIRS (Thermal Infrared Sensor Red), while the NDVI obtained by processing Landsat-8 band OLI (Operation Land Imager). The second step is to create environmental criticality map with  ECI (Environmental Criticality Index) algorithm. ECI is obtained from LST value divided by NDVI spectral histogram stretched to 8 bits. From this research, can be concluded that the heat coverage in Semarang City increase and distribution of vegetation density index spread every year. Environmental criticality due to UHI occurred in downtown area, specifically in the northern side of Semarang City.</p><p><strong><em>Keywords</em></strong><em>:</em><em>   </em><em>Urban Heat Island</em> (UHI), <em>Land Surface Temperature</em> (LST), <em>Normalized Difference Vegetation Index</em> (NDVI), <em>Environmental Criticality Index</em> (ECI)</p><p align="center"><strong><em><br /></em></strong></p><p> </p>

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