Remote sensing, heat island effect and housing price prediction via autoML

Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/6520

Title:	Remote sensing, heat island effect and housing price prediction via autoML
Authors:	Prof. LI Yi Man, Rita Chau, Kwong Wing Li, Ching Yu, Herru Zeng, Fanjie Tang, Beiqi Ding, Meilin
Issue Date:	2020
Source:	In Tareq, Ahram (ed.) (2020). Advances in artificial intelligence, software and systems engineering, proceedings of the AHFE 2020 virtual conferences on software and systems engineering, and artificial intelligence and social computing (pp. 113-118).
Conference:	AHFE 2020: Advances in Artificial Intelligence, Software and Systems Engineering
Abstract:	Global warming has become a major environmental concern in recent years. It is believed that urban heat island issues have caused health problems and thus we aim to investigate the impact of the heat island effect on housing prices by studying Whampoa Garden – one of the largest trading volume housing estates in Hong Kong. Landsat 8, an advance satellite that comprises the camera of the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) were used to collect satellite images from 2014 to 2018 from the United States Geological Survey (USGS). All the satellite images of the study points are equipped with the least cloud. We then used that information to conduct housing price prediction via AutoML.
Type:	Conference Paper
URI:	http://hdl.handle.net/20.500.11861/6520
ISBN:	9783030513276 9783030513283
DOI:	10.1007/978-3-030-51328-3_17
Appears in Collections:	Economics and Finance - Publication

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