The Mining Area Land Surface Temperature Retrieval from Landsat-8 Data

Chunsen Zhang, Rongrong Wu

Abstract

Taking the Shendong mining area as a research area, Landsat-8 data were used to retrieve the surface temperature of the study area using the radiation conduction equation method, the image-based retrieval algorithm(IB algorithm), the Mono-window algorithm(MW algorithm) and the single-channel algorithm(SC algorithm) respectively. The data were validated by MODIS land surface temperature (LST) data, comparing the similarities and differences between different algorithms. The results show that: (1) The Mono-window algorithm inversion accuracy is the highest among the four surface temperature inversion algorithms, which is the closest to MODIS LST data, followed by the radiation conduction equation, SC algorithm and IB algorithm. (2) The retrieval results of bare soil and buildings are the best for the four kinds of landform types, of which MW algorithm has the highest retrieval accuracy. (3) The MW algorithm should be adopted for the retrieval of surface temperature based on Landsat-8 data in the mining area.

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Paper Citation


in Harvard Style

Zhang C. and Wu R. (2018). The Mining Area Land Surface Temperature Retrieval from Landsat-8 Data.In Proceedings of the International Workshop on Environment and Geoscience - Volume 1: IWEG, ISBN 978-989-758-342-1, pages 489-495. DOI: 10.5220/0007432304890495


in Bibtex Style

@conference{iweg18,
author={Chunsen Zhang and Rongrong Wu},
title={The Mining Area Land Surface Temperature Retrieval from Landsat-8 Data},
booktitle={Proceedings of the International Workshop on Environment and Geoscience - Volume 1: IWEG,},
year={2018},
pages={489-495},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007432304890495},
isbn={978-989-758-342-1},
}


in EndNote Style

TY - CONF

JO - Proceedings of the International Workshop on Environment and Geoscience - Volume 1: IWEG,
TI - The Mining Area Land Surface Temperature Retrieval from Landsat-8 Data
SN - 978-989-758-342-1
AU - Zhang C.
AU - Wu R.
PY - 2018
SP - 489
EP - 495
DO - 10.5220/0007432304890495