Retrieval of precise land surface temperature from ASTER night-time thermal infrared data by split window algorithm for improved coal fire detection in Jharia Coalfield, India

被引：12

作者：

Singh, Narendra ^{[1
,2
]}

Chatterjee, R. S. ^{[2
]}

Kumar, Dheeraj ^{[1
]}

Panigrahi, D. C. ^{[1
]}

Mujawdiya, Ritesh ^{[2
]}

机构：

[1] Indian Sch Mines, Dept Min Engn, Indian Inst Technol, Dhanbad, Bihar, India

[2] Indian Inst Remote Sensing, Geosci Dept, Dehra Dun, Uttarakhand, India

来源：

GEOCARTO INTERNATIONAL | 2022年 / 37卷 / 03期

关键词：

Land surface temperature; land surface emissivity; split window algorithm; modified split-window covariance and variance ratio; ASTER TIR data; Jharia Coalfield; WATER; EMISSIVITY; SATELLITE; CALIBRATION; DERIVATION; INDEX;

D O I：

10.1080/10106049.2020.1753820

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The study proposed a methodology for the retrieval of precise Land Surface Temperature (LST) in Jharia Coalfield from night-time ASTER multispectral thermal infrared (TIR) data by split-window algorithm (SWA) using atmospheric transmittance and band-specific Land Surface Emissivity (LSE). For deriving night-time atmospheric transmittance, water vapor content was retrieved from night-time ASTER TIR data by modified split-window covariance and variance ratio approach. Improved LSE was retrieved by the proposed modified LSE model by integrating refined thermal emission-vegetation cover model, modified normalized difference water index and bandwidth-weighted red band reflectivity model. The retrieved SWA LST was compared with LST obtained by single-channel algorithm (SCA) across three coal fire test sites to demonstrate significant improvement in temperature contrast between coal fire and background pixels. Besides, SWA LST based coal fire thermal anomalies are significantly comparable (including substantially reduced false alarms) with in-situ observations than that of SCA LST.

引用

页码：926 / 943

页数：18