第36卷，第8期 2016年8月
光谱学与光谱分析 Spectroscopy and Spectral Analysis
Vol. 36,No.8+pp2712-2720
August，2016
ANovelMethodtoMonitorCoalFiresBasedon
Multi-SpectralLandsatImages
XIAQing,HUZhen-qi*
China University of Mining and Technology (Beijing), Beijing 100083, China
Abstract Coal fires pose a serious threat to the environment worldwide, and they are responsible for atmos pheric pollution, water contamination, land subsidence and the safety of miners. The multi-spectral Landsat images offer the possibility of detecting and monitoring coal fires at large scales. In this study, the thermal in frared spectral is extracted, and a mono-window algorithm is used for retrieving coal fire temperature. Howev er, the surface emissivity and atmospheric water vapor content play important roles in determining the temper ature for this algorithm. The surface emissivity is particularly difficult to obtain with satellite overpasses be cause it is affected by a variety of factors. In general, an average emissivity value is assigned to represent all land cover categories, which leads to a big error for retrieving coal fire temperature. Meanwhile, atmospheric water vapor content is calculated by simulating atmospheric profile through standard atmosphere models. However, it is difficult to obtain real water vapor content and atmospheric profile is affected by many factors with each satellite pass. The lack of knowledge of the real atmospheric profile is a large constraint, and inaccu-rate simulation can introduce big errors. Aiming at overcoming drawbacks mentioned above and increasing the accuracy for this algorithm+ the NDVI threshold method is applied to estimate surface emissivity. The NDVI threshold method separates different land cover categories, and different emissivity is assigned to different land cover classifications. Based on the ground meteorological parameters' relationship between atmospheric water vapor and atmospheric water vapor pressure, an empirical relationship is found to estimate atmospheric water vapor content. For this method, the ground meteorological parameters are easily obtained from meteorological observation stations and it is convenient to estimate water vapor content. The mono-window algorithm is im-proved and coal fire temperature is retrieved. This methodology was applied to the Wuda coalfield, in China+ and coal fire temperatures were retrieved and extracted from the background from 1988 to 2015 in the study ar ea. A thorough inventory of coal fire areas and locations is annually presented, and area changes are qualita-tively analyzed during the observation period. This method is considered as feasible and effective for retrieving and monitoring coal fires based on multi-spectral Landsat images in comparison to other techniques in the Wuda coalfield, China.
Keywords Multi-spectral, Thermal infrared spectral; a mono-window algorithm; NDVI threshold method
中图分类号：TP79
Introduction
文献标识码：A
DOI: 10. 3964/j. issn. 10000593(2016)08-2712-09
scale. China is the largest coal producer in the world. Coal fires are an environmental catastrophe characterized by an in-crease in ambient temperature, the emission of noxious gases,
Uncontrolled coal fires are a serious problem on a global Received: 2015-11-05; aceepted: 2016-04-12
Foundation item: National Natural Science Fund in China (41371502)
land subsidence and collapse of surface ground. Moreover,
Biography: XIA Qing, (1987—), PhD, China University of Mining and Technology (Beijing)
* Corresponding author
e-mail: huzq1963@163.com
e-mail: xiaqingfriendxia@126. com