Using Google Earth Engine open-source code for land surface temperature estimation from Landsat data in Chuong My district, Hanoi city, Vietnam
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DOI: https://doi.org/10.55250/Jo.vnuf.9.2.2024.097-106Keywords:
Emissivity, Land surface temperature, Landsat, NDVIReferences
. Quattrochi D.A. & Luvall J.C. (1999). Thermal infrared remote sensing for analysis of landscape ecological processes: Methods and applications. Landsc. Ecol. 14: 577-598.
. Chrysoulakis N., Lopes M., San José R., Grimmond C.S.B., Jones M.B., Magliulo V., Klostermann, J.E.M., Synnefa, A., Mitraka, Z., Castro E.A., Gonzales A., Vogt R., Vesala T., Spano D., Pigeon G., Freer-Smith P., Staszewski T., Hodges N., Mills G. & Cartalis C. (2013). Sustainable urban metabolism as a link between bio-physical sciences and urban planning: The BRIDGE project. Landsc. Urban Plan. 112: 100-117.
. Anderson M.C., Norman J.M., Kustas W.P., Houborg R., Starks P.J. & Agam N. (2008). A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales. Remote Sens. Environ. 112: 4227-4241.
. Parastatidis D., Mitraka Z., Chrysoulakis N. & Abrams M. (2027). online global Landsat surface temperature estimation from Lansat. Remote Sensing. 9: 1208. https://doi.org/10.3390/rs9121208
. Benas N., Chrysoulakis N. & Cartalis C. (2016). Trends of urban surface temperature and heat island characteristics in the Mediterranean. Theor. Appl. Climatol. 1–10.
. Weng Q., Lu D. & Schubring J. (2004). Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sens. Environ. 89: 467-483.
. Tomlinson C.J., Chapman L., Thornes J.& Baker C. (2011). Remote sensing land surface temperature for meteorology and climatology: A review. Meteorol. Appl. 18: 296-306.
. Jimenez-Munoz J.C., Cristobal J., Sobrino J.A., Sòria G., Ninyerola M. & Pons X. (2009). Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data. IEEE Trans. Geosci. Remote Sens. 47: 339–349.
. Jimenez-Munoz J.C., Sobrino J.A., Skokovic D., Mattar C. & Cristobal J. (2014). Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geosci. Remote Sens. Lett. 11: 1840-1843.
. Quantum Geographic Information System (QGIS). Available online: http://www.qgis.org/en/site/index. html (accessed on 23 May 2024)
. Avdan U. & Jovanovska G. (2016). Algorithm for automated mapping of land surface temperature using Landsat 8 satellite data. J. Sens. 1–8.
. Vo Dai Nguyen, Nguyen Hai Hoa, Nguyen Quyet & Pham Duy Quang. (2021). Land surface temperature responses to vegetation and soil moisture index using Landsat-8 data in Luong Son district, Hoa Binh province. Journal of Forestry Science & Technology. 11: 82-94.
. Nguyen Hai Hoa (2015). Using Landsat data to estimate the changes in land surface temperature and solutions on minimising its impacts in Chuong My ditstrict, Hai Noi during 2000-2015. Journal of Forestry Science & Technology (Translated from Nguyen Hai Hoa).
. Nguyen Khac Manh, Nguyen Hai Hoa, Le Thao Van, Pham Duy Quang & Vo Dai Nguyen (2020). Determing threshold of water indices to detect small surface water areas in wetlands of Chuong My district, Hanoi city. Journal of Forest Science & Technology. 10: 77-87.
. Gislason P.O., Benediktsson J.A. & Sveinsson J.R. (2006). Random Forest for land cover classification. Patter Recognition Letters. 27:294-300. https://doi.org/10.1016/j.patrec.2005.08.011
. Nong Thi Oanh, Tran Xuan Truong, Ta Hoang Trung & Trinh Viet Nga (2023). Automatic model for classification of land cover data for greenhouse gas Inventory using remote sensing imageries. Journal of Geodesy & Cartography. 57(9): 55-64
. Praticò S., Solano F., Di Fazio S. & Modica G. (2021). Machine learning classification of mediterranean forest habitats in Google Earth Engine based on seasonal Sentinel-2 time-series and input image composition optimisation. Remote Sens. 13:586. https://doi.org/10.3390/rs13040586
. Abdel-Rahman E.M., Mutanga O.; Adam E., & Ismail R. (2014). Detecting Sirex octillion grey-attacked and lightning-struck pine trees using airborne hyperspectral data, random forest and support vector machines classifiers. ISPRS J. Photogram. Remote Sens. 88: 48–59. https://doi.org/10.1016/j.isprsjprs.2013.11.013
. Breiman L. (2001). Random Forests. Mach. Learn. 45: 5–32.
https://doi.org/10.1023/A:1010933404324
. Sandoval S., Escobar-Flores J.G. & Munir M.B. (2023). Urbanization and its impacts on land surface temperature and sea surface temperature in a tourist region in Mexico from 1990 to 2020. Remote Sensing Applications: Society and Environment. 101046. https://doi.org/10.1016/j.rsase.2023.101046
. Portela C.I., Massi K.G., Rodrigues T. & Alcantara, E. (2020). Impact of urban and industrial features on land surface temperature: Evidence from satellite thermal indices. Sustainable Cities and Society. 102100. https://doi.org/10.1016/j.scs.2020.102100
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