Study of the urban heat island intensity using Landsat 8 in Da Nang in 2020
Hanoi University of Natural Resources and Environment, Hanoi, Vietnam
- Received: 19th-July-2022
- Revised: 27th-Dec-2022
- Accepted: 31st-Mar-2023
- Online: 30th-June-2023
- Section: Geomatics and Land Administration
Monitoring spatiotemporal changes in land surface temperature in metropolitan areas is important to obtain the necessary information about environmental conditions and promote sustainable cities. Da Nang is a big city and is considered one of the tourist centers of Vietnam. Economic development and population growth lead to the expansion of urban land there. That affects the environment, especially resulting in the increase in surface temperature of the core city compared to the surrounding areas. The application of remote sensing data and techniques using thermal sensors for the estimation of land surface temperature and the formation of urban heat islands. This research aims to determine land surface temperature (LST) values and urban heat island (UHI) intensity distribution using Landsat 8 images. UHI is calculated in two steps: first, LST is calculated, and then the temperature threshold for UHI and none UHI is determined by the mean and standard deviation statistics of LST in the study area. To compute the LST, two levels of data must be processed: the NIR and RED bands from level 1 and the thermal band from level 2. The results showed the temperature in Da Nang varies from 15.7÷46.8 0C, with a significant regional temperature variance. The areas with high vegetation index had low temperatures while areas with low vegetation index had high temperatures. Non-UHI areas are present in areas with dense vegetation, dominated by Hoa Vang district and Son Tra peninsula. UHI is found in areas with temperatures more than or equal to 34.2 0C. The urban heat island has been taken play in the core of Da Nang, where the densely populated areas, industrial zones, airports, and landfill are located.
Chen, X. L., Zhao, H. M., Li, P. X., and Yin, Z. Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote sensing of environment, 104(2), 133-146.
de Faria Peres, L., de Lucena, A. J., Rotunno Filho, O. C., and de Almeida França, J. R. (2018). The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data. International journal of applied earth observation and geoinformation, 64, 104-116.
Falahatkar, S., Hosseini, S. M., and Soffianian, A. R. (2011). The relationship between land cover changes and spatial-temporal dynamics of land surface temperature. Indian Journal of Science and Technology, 4(2), 76-81.
Kikegawa, Y., Genchi, Y., Kondo, H., and Hanaki, K. (2006). Impacts of city-block-scale countermeasures against urban heat-island phenomena upon a building’s energy-consumption for air-conditioning. Applied Energy, 83(6), 649-668.
Lai, J., Zhan, W., Huang, F., Voogt, J., Bechtel, B., Allen, M., ... and Du, P. (2018). Identification of typical diurnal patterns for clear-sky climatology of surface urban heat islands. Remote sensing of environment, 217, 203-220.
Le, H. T. T., Doan, N. D., Huynh, L. T., Nguyen, T. T. T., Nguyen, H. N. T., Luu, T. T. T., ... and Le, N. T. (2020). The Influences of Landcover structure on surface urban heat islands: A case study of Ho Chi Minh, Vietnam. Journal of Mining and Earth Sciences Vol, 61(2), 76-85.
Mildrexler, D. J., Zhao, M., and Running, S. W. (2011). A global comparison between station air temperatures and MODIS land surface temperatures reveals the cooling role of forests. Journal of Geophysical Research: Biogeosciences, 116(G3).
Nascimento, A. C. L., Galvani, E., Gobo, J. P. A., and Wollmann, C. A. (2022). Comparison between Air Temperature and Land Surface Temperature for the City of São Paulo, Brazil. Atmosphere, 13(3), 491.
Niu, L., Zhang, Z., Peng, Z., Liang, Y., Liu, M., Jiang, Y. and Tang, R. (2021). Identifying surface urban heat island drivers and their spatial heterogeneity in China’s 281 cities: An empirical study based on multiscale geographically weighted regression. Remote Sensing, 13(21), 4428.
Pham, V. C., Watanabe, H. (2004). Use of Thermal Infrared Channels of ASTER to evaluate the Land Surface Temperature Changes of an Urban Area in Hanoi, Vietnam. Japan-Vietnam Geoinformatics Consortium, 19 Le Thanh Tong Campus, Hanoi University of Science, Conference Hall, Hanoi, Vietnam http://gisws. media. osaka-cu. ac. jp/gisideas04/.
Puspita, B. D., and Hadiyanti, A. (2022). Measuring Urban Heat Islands Using Landsat 8 TIRS and Investigating the Variety of Landuse Proportion in Yogyakarta City. In Proceeding International Conference on Religion, Science and Education (Vol. 1, pp. 595-603).
Schwarz, N., Lautenbach, S., and Seppelt, R. (2011). Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures. Remote Sensing of Environment, 115(12), 3175-3186.
Sobrino, J. A., Jiménez-Muñoz, J. C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J., ... and Martínez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE transactions on geoscience and remote sensing, 46(2), 316-327.
Thanh Hoan, N., Liou, Y. A., Nguyen, K. A., Sharma, R. C., Tran, D. P., Liou, C. L., and Cham, D. D. (2018). Assessing the effects of land-use types in surface urban heat islands for developing comfortable living in Hanoi City. Remote Sensing, 10(12), 1965.
Yan, W. Y., Mahendrarajah, P., Shaker, A., Faisal, K., Luong, R., and Al-Ahmad, M. (2014). Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites. Environmental monitoring and assessment, 186, 8161-8173.