Research Article
Estimating Land Surface Temperature from Landsat-8 Images Based on a Cloud-Based Automated Processing Service
@INPROCEEDINGS{10.1007/978-3-030-67101-3_5, author={Phan Hien Vu and Tan-Long Le and Cuong Pham-Quoc}, title={Estimating Land Surface Temperature from Landsat-8 Images Based on a Cloud-Based Automated Processing Service}, proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26--27, 2020, Proceedings}, proceedings_a={ICCASA \& ICTCC}, year={2021}, month={1}, keywords={Lansat LST Cloud-based service HCMC}, doi={10.1007/978-3-030-67101-3_5} }- Phan Hien Vu
Tan-Long Le
Cuong Pham-Quoc
Year: 2021
Estimating Land Surface Temperature from Landsat-8 Images Based on a Cloud-Based Automated Processing Service
ICCASA & ICTCC
Springer
DOI: 10.1007/978-3-030-67101-3_5
Abstract
As the biggest city in Vietnam, Ho Chi Minh City (HCMC) usually suffers from a number of environmental issues such as traffic jam, subsidence and inundation, river and air pollution, high temperature, etc. Therefore, a hazard maps system helps the city government and population understand well environmental risks. The main data sources for such system is a combination of in-situ measurements in ground and remotely sensed images from space. Popular satellite data products available and free of charge are used to environmental monitoring, consisting of Sentinel, Landsat, and Terra/Aqua MODIS. In this paper, we focus on estimating land surface temperature (LST) from Landsat-8 images based on a cloud-based automated processing service. The LST image is computed from red, near-infrared and thermal infrared bands. The service can be integrated as a part of a hazard map system when its data are collected from different sources.
