Urban Heat Island Assessment Using the Landsat 8 Data: A Case Study in Shenzhen and Hong Kong

Tsou, Jin Yeu; Zhuang, Jian; Yu, Li; Zhang, Yuanzhi

doi:10.3390/urbansci1010010

Cited by 51 publications

(24 citation statements)

References 33 publications

(53 reference statements)

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“…The best validation for LST in remote sensing it is the same time with image take a picture in location because the surface temperature in the field has boundary time to know how LST in that location [44]. The value surface temperature in the field is higher than the result of LST in an image because processing in an image has a reduce distraction such as atmospheric or sensor [45]. Figure.…”

Section: Land Surface Temperature Validationmentioning

confidence: 99%

Downscaling land surface temperature on multi-scale image for drought monitoring

Nugraha

Gunawan

Kamal

2019

Sixth Geoinformation Science Symposium

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Land Surface Temperature (LST) is an important indicator of environmental changes, especially related drought monitoring. It is necessary to accurately detect drought events using advanced technology proved information regarding the drought areas. Remote sensing images have proven to be efficient in detecting drought events. MODIS Terra and Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat 8 OLI/TIRS (The Operational Land Imager and the Thermal Infrared Scanner) represent remote imaging images with different spatial resolutions that enable us to provide drought information. However, proper methods are needed to optimize these images for monitoring drought events. The purpose of this study is to find out the ability of multi-scale images provide information about drought monitoring using LST methods. The method used in LST is a Temperature Condition Index (TCI), the Crop Water Stress Index (CWSI), and Principal Component Analysis (PCA). All three equations are selected because they represent a modification of the method for LST input. The results suggest that the three equations used in multi-level imagery have a critical alignment of information regarding the drought. The results show that the drought pattern identified by MODIS Terra image was similar to the one detected by Landsat ETM+ and OLI/TIRS images. However, we found a temperature difference in the dry season (especially in October) between Landsat ETM+ and OLI/TIRS. The degree of LST estimation accuracy between MODIS Terra and Landsat (ETM+ and OLI/TIRS) is indicated by the average difference between the results of those images, which was 1 degree Celsius (1°C). The use of these three equations for drought monitoring with multi-level imagery suggests that there is a positive relationship. This relationship manifests the same pattern, shape, and association that are produced, thus using a common equation for drought monitoring is more focused.

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Section: Land Surface Temperature Validationmentioning

confidence: 99%

Downscaling land surface temperature on multi-scale image for drought monitoring

Nugraha

Gunawan

Kamal

2019

Sixth Geoinformation Science Symposium

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“…Jika koreksi dilakukan secara benar dan atau dengan menggunakan persamaan meminimalkan efek gangguan atmosfer maupun sensor, akurasi yang dihasilkan akan semakin tinggi (mendekati nilai suhu yang sebenarnya) (Tsou et al, 2017). Terkait hal ini, Fawzi dan Jatmiko (2015) menemukan tren yang menunjukkan perbedaan yang relatif besar pada nilai suhu kisaran dan nilai yang sebenarnya pada objek-objek yang terbangun (memiliki suhu sebenarnya yang lebih tinggi), dibanding dengan objek-objek alami yang nilai suhu kisaran mendekati nilai suhu yang sebenarnya (perbedaan relatif lebih kecil).…”

Section: Hal Yang Berpengaruh Mengenai Uhi Dalam Penginderaan Jauhunclassified

Mengukur Urban Heat Island Menggunakan Penginderaan Jauh, Kasus Di Kota Yogyakarta

Fawzi¹

2017

MIG

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Peningkatan suhu di kawasan perkotaan adalah salah satu dampak dari urbanisasi. Fenomena Urban Heat Island (UHI) merupakan salah satu akibat yang dihasilkan akibat peningkatan suhu tersebut. Diperlukan upaya untuk menilai perubahan suhu apakah dapat berbahaya bagi manusia atau tidak. Melalui pengukuran UHI, pengaruh pembangunan kota terhadap peningkatan suhu dapat diukur. Tujuan penelitian ini adalah untuk memberikan panduan ilmiah tentang perolehan intensitas dan distribusi UHI menggunakan teknik penginderaan jauh. Studi kasus yang dilakukan berada di Kota Yogyakarta, Daerah Istimewa Yogyakarta. Citra penginderaan jauh yang digunakan adalah citra Landsat 8 perekaman tanggal 24 Juni 2013, path/row 120/65. Metode ekstraksi suhu permukaan menggunakan inversi persamaan Planck dengan koreksi emisivitas dan atmosfer menggunakan radiative transfer equation. Hasil pengolahan didapatkan intensitas UHI sebesar ±2,5oC pada Kota Yogyakarta dan intensitas UHI sebesar ±3,23oC pada area yang diperluas dengan buffer 1 km dari batas Kota Yogyakarta. Hal ini menunjukkan bahwa pemilihan area penelitian untuk analisis UHI menjadi penting karena mempengaruhi nilai intensitas UHI dan distribusi UHI. Ditemukan kawasan Malioboro dan sekitarnya berpotensi kuat terjadi UHI, sehingga perlu upaya mitigasi UHI pada kawasan tersebut. Pengukuran UHI menggunakan penginderaan jauh dipengaruhi oleh hal-hal yang berkaitan dengan sistem penginderaan jauh, seperti validasi dan akurasi hasil estimasi, pengaruh atmosfer, dan perbedaan waktu intensitas puncak UHI. Metode perolehan UHI dalam penelitian ini dapat menjadi panduan ilmiah yang digunakan untuk dasar evaluasi pembangunan perkotaan untuk lebih baik.

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“…Satellite image data have become a strong means for UHI research because they provide a convenient and consistent mechanism for detecting the thermal features of urban surfaces [20][21][22]. e satellite remote-sensing images with a thermal infrared band can be transformed into land surface temperature (LST) to characterize an UHI [23,24]. For example, Landsat TM/ETM+/OLI data have been widely applied to calculate the LST values for UHI effect studies [25,26].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region

et al. 2020

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Under the trend of rapid urbanization, the urban heat island (UHI) effect has become a hot issue for scholars to study. In order to better alleviate UHI effect, it is important to understand the effect of landuse/landcover (LULC) and landscape patterns on the urban thermal environment from perspective of landscape ecology. This research aims to quantitatively investigate the effect of LULC landscape patterns on UHI effects more accurately based on a landscape metrics analysis. In addition, we also explore the complex relationship between land surface temperature (LST) and vegetation cover. Taking Zhengzhou City of China as a case study, an integrated method which includes the geographic information system (GIS), remote-sensing (RS) technology, and landscape metrics was employed to facilitate the analysis. Landsat data (2000–2014) were applied to investigate the spatiotemporal evolution patterns of LST and LULC. The results indicated that the mean LST value increased by 2.32°C between 2000 and 2014. The rise of LST was consistent with the trend of rapid urbanization in Zhengzhou City, which resulted in sharp increases in impervious surfaces (IS) and substantial losses of vegetation cover. Furthermore, the investigation of LST and vegetation cover demonstrated that fractional vegetation cover (FVC) had a stronger negative effect on LST than normalized differential vegetation index (NDVI). In addition, LST was obviously correlated with LULC landscape patterns, and both landscape composition and spatial configuration affected UHI effects to varying degrees. This study not only illustrates a feasible way to investigate the relationship between LULC and urban thermal environment but also suggests some important measures to improve urban planning to reduce UHI effects for sustainable development.

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Urban Heat Island Assessment Using the Landsat 8 Data: A Case Study in Shenzhen and Hong Kong

Cited by 51 publications

References 33 publications

Downscaling land surface temperature on multi-scale image for drought monitoring

Downscaling land surface temperature on multi-scale image for drought monitoring

Mengukur Urban Heat Island Menggunakan Penginderaan Jauh, Kasus Di Kota Yogyakarta

Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region

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