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

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).

DOI

10.1007/978-3-030-51328-3_17

URI

http://hdl.handle.net/20.500.11861/6520

Type

Conference Paper

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.

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

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