高温目标遥感特征识别技术监测土法炼焦研究
|
摘要
无论在地球表面还是高空，高温现象都普遍存在，地表发生的一些高温现象如森林大火、草场火、火山活动、油井火、煤火等，在高空中如飞机尾焰、发射的火箭体、进入大气层发生燃烧的物体等。这些高温现象的主要特征就是向外辐射电磁辐射，引起热异常，一旦它们成为被研究者关注的对象，就可以称之为高温目标。传统高温目标的监测手段往往是现场测量，这种监测方法的限制因素很多，比如无法实现大范围的监测，甚至无法到达高温目标现场，如火山喷发、森林火等，有时候我们甚至无法预知高温目标事件发生的时间等等，而应用遥感技术可以实现宏观、快速、大范围监测这些高温目标，弥补了现场测量的缺点。高温目标遥感特征识别技术在环境遥感领域迅速得到了发展，在军事领域也引起了人们的高度重视。
高温目标遥感识别技术一直是遥感科学研究的重点，也是遥感技术应用的重要支撑。利用遥感技术识别高温目标，是地气系统、自然灾害监测、自然资源调查等对地观测技术应用领域的先行基础工作，有着巨大的社会和经济效益。如何从遥感数据中提取高温目标的特征参数，如温度、尾焰、NDVI等信息，并据此来识别高温目标已成为当前的研究热点和难点，同时，也对遥感影像数据处理和应用提出了更高的要求。现有的高温目标识别的算法基本是基于NOAA／AVHRR和EOS／MODIS数据基础上，通过热红外(8～14μm)和近红外(3～4μm)辐亮度值反演亮温，通过亮温异常并结合其他相关信息来判别高温目标，如判断是否为森林、草场火点等。通过热异常识别高温目标是最有潜力的途径之一。
高温目标识别的基础理论和数据处理方法包括高温目标的遥感生成机理和特征反演两大部分。本文在深入研究高温目标遥感成像机理的基础上，从自然灾害监测工程应用的需要出发，着重解决遥感提取高温目标特征的几个关键问题，包括：高温目标遥感特征生成机理，如温度异常特征、空气特征变化、高温过程分析、传感器响应等；提出利用近红外(1.3～3.0μm)识别高温目标的理论、方法；作为生态环境监测方面的应用拓展，提出利用卫星遥感技术监测土法炼焦污染源的技术和方法。
论文首先研究高温目标影像特征识别的遥感机理问题。高温目标和周围环境差异的主要特征是高温目标在燃烧过程中产生了大量的辐射能量，同时还包括烟尘、气体等，这些特征在遥感影像上的响应即遥感影像特征，其识别就是通过这些特征来提取高温目标信息。由于混合像元、组分温度、像元比辐射率和大气等影响，高温目标的遥感特征识别就要困难的多。之后，本文针对以往高温目标遥感特征识别中存在的问题，开展遥感技术监测土法炼焦应用研究，主要创新如下：
(1)改进了高温目标遥感特征识别研究的方法。采用从高温目标遥感特征形成机理分析入手的策略和方案，从太阳光源、高温目标的空间特征、光谱特征、辐射传输模型、大气影响和传感器响应等整个成像链路和相互间的偶合关系入手来研究高温目标遥感影像特征，对于进一步的研究和应用具有重要的意义。
(2)提出利用近红外(0.7～3.0μm)进行高温目标识别的方法。以往进行高温目标识别都是利用热红外卫星数据，本文在详细分析TM传感器对高温目标响应的基础上，提出利用近红外波段(0.7-3.0μm)进行高温目标识别的理论基础，证明其具有探测高温目标的潜力，以草场火、煤火和火山为例，利用近红外技术，对高温目标遥感探测进行了验证研究。
(3)首次提出用卫星遥感技术探测土法炼焦的方法体系。把土法炼焦与热辐射和遥感特征联系起来，利用TM白天数据对山西某地区土法炼焦的遥感探测实验证明，TM7和TM5对土法炼焦产生的高温敏感，TM6对高温异常敏感，但是由于空间分辨率的影响，其对面积小的高温异常不如TM7和TM5敏感。通过TM数据对该区土法炼焦卫星遥感动态监测(1999年和2004年)，监测数据得到了有关部门的认可，TM数据是获得可靠、定量土法炼焦信息的重要工具，拓展了遥感应用范围，为遥感技术用于环境监测方面开拓了一个新的应用领域，成果可以用于其它高温目标的卫星遥感监测上，如火山、森林火、草场火、煤火、土法炼钢、土砖厂等。
(4)改进了Landsat TM数据反演土法炼焦温度方法。整像元温度大于68℃，将使TM6波段达到饱和，通过该方法，利用TM6热红外数据通过对土法炼焦温度反演结果与地面测量结果对比，证明该方法是可行的。
国土资源西南地区科技查新检索站对《遥感技术监测土法炼焦》委托项目进行了成果查新，在对4个查新点查新的基础上，得出的查新结论为“在所查国内外公开发表的文献范围内，除见有本课题组人员的研究成果外，未见有直接与本课题查新点相同或类似的文献内容报道，本课题的研究成果具有新颖性”(见附件Ⅵ)。
High hot spots distribute anywhere either on the earth surface or in the space such as forest fire, grassland fare, active volcano, coal fare. These hot spots cause severe environmental and economic problems. Although satellite remote sensing has been used successfully to detect these spots, a satellite data based concept that can quantify the majority of detected hot spots is still missing. There are many problems about hot spots detecting mechanism using satellite data. This dissertation tests a new generation of satellite instrument TM sensor which explores the potential to determine hot spot radiative energy. This dissertation made choice of Shanxi province as research area. An attempt to detect and monitor indigenous coke-making sites was achieved based on Landsat TM data. The key conclusions are as following:
(1) High hot spots recognition is affected by the solar radiance, spatial character, spectral character, radiance transportation, aerial effect and sensor respond. Analysis procedure of high hot spots is presented for improving the recognition accuracy. This method is important for next research.
(2) Put forward an method for high hot spots recognition using the near infrared (0.7-3.0μm) remote sensing data. The theoretical analysis of Landsat TM sensors outlines the fact the thermal infrared or near infrared (0.7-3.0μm) are effective in registering high temperature spots. TM7 and TM5 have advantage to detect very high temperature spots through some researrch cases wildfire, coal fare and volcano eruption were presented in dissertation.
(3) Indigenous coke-making sites cause severe environmental and economic problems. This dissertation first explores the potential to detect coke-making site based on Landsat TM data (day time). Although TM7 and TM5 spectral radiance of an image contains not only hot spot temperature but also solar reflectance; they are sensitive to be able to register spectral indigenous coke-making radiance. The thermal infrared (TM6) is, however, particularly effective in registering these hot spots. In this dissertation, a new method is presented, which links the indigenous come-making radiance to recognition through TM751 band combination. During five years (from 1999 to 2004 at Shanxi Province), the quantity of indigenous coke-making sites distributed mainly on the plain increased by 10 times and the figures given by local authorities can in fact be approximated. It is thus expected that Landsat TM data will become a crucial tool in obtaining reliable, quantitative information for indigenous coke-making sites.
(4) The present dissertation presents an improved method for surface temperature retrieval algorithm of sub-pixel indigenous coke-making hot spots. The thermal data saturate for temperatures above 68℃and indigenous coke-making sites occupying less than a pixel requires modification of the methodology. The temperature estimation from the method is found to be in good with agreement with ground observations.
高温目标遥感识别技术一直是遥感科学研究的重点，也是遥感技术应用的重要支撑。利用遥感技术识别高温目标，是地气系统、自然灾害监测、自然资源调查等对地观测技术应用领域的先行基础工作，有着巨大的社会和经济效益。如何从遥感数据中提取高温目标的特征参数，如温度、尾焰、NDVI等信息，并据此来识别高温目标已成为当前的研究热点和难点，同时，也对遥感影像数据处理和应用提出了更高的要求。现有的高温目标识别的算法基本是基于NOAA／AVHRR和EOS／MODIS数据基础上，通过热红外(8～14μm)和近红外(3～4μm)辐亮度值反演亮温，通过亮温异常并结合其他相关信息来判别高温目标，如判断是否为森林、草场火点等。通过热异常识别高温目标是最有潜力的途径之一。
高温目标识别的基础理论和数据处理方法包括高温目标的遥感生成机理和特征反演两大部分。本文在深入研究高温目标遥感成像机理的基础上，从自然灾害监测工程应用的需要出发，着重解决遥感提取高温目标特征的几个关键问题，包括：高温目标遥感特征生成机理，如温度异常特征、空气特征变化、高温过程分析、传感器响应等；提出利用近红外(1.3～3.0μm)识别高温目标的理论、方法；作为生态环境监测方面的应用拓展，提出利用卫星遥感技术监测土法炼焦污染源的技术和方法。
论文首先研究高温目标影像特征识别的遥感机理问题。高温目标和周围环境差异的主要特征是高温目标在燃烧过程中产生了大量的辐射能量，同时还包括烟尘、气体等，这些特征在遥感影像上的响应即遥感影像特征，其识别就是通过这些特征来提取高温目标信息。由于混合像元、组分温度、像元比辐射率和大气等影响，高温目标的遥感特征识别就要困难的多。之后，本文针对以往高温目标遥感特征识别中存在的问题，开展遥感技术监测土法炼焦应用研究，主要创新如下：
(1)改进了高温目标遥感特征识别研究的方法。采用从高温目标遥感特征形成机理分析入手的策略和方案，从太阳光源、高温目标的空间特征、光谱特征、辐射传输模型、大气影响和传感器响应等整个成像链路和相互间的偶合关系入手来研究高温目标遥感影像特征，对于进一步的研究和应用具有重要的意义。
(2)提出利用近红外(0.7～3.0μm)进行高温目标识别的方法。以往进行高温目标识别都是利用热红外卫星数据，本文在详细分析TM传感器对高温目标响应的基础上，提出利用近红外波段(0.7-3.0μm)进行高温目标识别的理论基础，证明其具有探测高温目标的潜力，以草场火、煤火和火山为例，利用近红外技术，对高温目标遥感探测进行了验证研究。
(3)首次提出用卫星遥感技术探测土法炼焦的方法体系。把土法炼焦与热辐射和遥感特征联系起来，利用TM白天数据对山西某地区土法炼焦的遥感探测实验证明，TM7和TM5对土法炼焦产生的高温敏感，TM6对高温异常敏感，但是由于空间分辨率的影响，其对面积小的高温异常不如TM7和TM5敏感。通过TM数据对该区土法炼焦卫星遥感动态监测(1999年和2004年)，监测数据得到了有关部门的认可，TM数据是获得可靠、定量土法炼焦信息的重要工具，拓展了遥感应用范围，为遥感技术用于环境监测方面开拓了一个新的应用领域，成果可以用于其它高温目标的卫星遥感监测上，如火山、森林火、草场火、煤火、土法炼钢、土砖厂等。
(4)改进了Landsat TM数据反演土法炼焦温度方法。整像元温度大于68℃，将使TM6波段达到饱和，通过该方法，利用TM6热红外数据通过对土法炼焦温度反演结果与地面测量结果对比，证明该方法是可行的。
国土资源西南地区科技查新检索站对《遥感技术监测土法炼焦》委托项目进行了成果查新，在对4个查新点查新的基础上，得出的查新结论为“在所查国内外公开发表的文献范围内，除见有本课题组人员的研究成果外，未见有直接与本课题查新点相同或类似的文献内容报道，本课题的研究成果具有新颖性”(见附件Ⅵ)。
High hot spots distribute anywhere either on the earth surface or in the space such as forest fire, grassland fare, active volcano, coal fare. These hot spots cause severe environmental and economic problems. Although satellite remote sensing has been used successfully to detect these spots, a satellite data based concept that can quantify the majority of detected hot spots is still missing. There are many problems about hot spots detecting mechanism using satellite data. This dissertation tests a new generation of satellite instrument TM sensor which explores the potential to determine hot spot radiative energy. This dissertation made choice of Shanxi province as research area. An attempt to detect and monitor indigenous coke-making sites was achieved based on Landsat TM data. The key conclusions are as following:
(1) High hot spots recognition is affected by the solar radiance, spatial character, spectral character, radiance transportation, aerial effect and sensor respond. Analysis procedure of high hot spots is presented for improving the recognition accuracy. This method is important for next research.
(2) Put forward an method for high hot spots recognition using the near infrared (0.7-3.0μm) remote sensing data. The theoretical analysis of Landsat TM sensors outlines the fact the thermal infrared or near infrared (0.7-3.0μm) are effective in registering high temperature spots. TM7 and TM5 have advantage to detect very high temperature spots through some researrch cases wildfire, coal fare and volcano eruption were presented in dissertation.
(3) Indigenous coke-making sites cause severe environmental and economic problems. This dissertation first explores the potential to detect coke-making site based on Landsat TM data (day time). Although TM7 and TM5 spectral radiance of an image contains not only hot spot temperature but also solar reflectance; they are sensitive to be able to register spectral indigenous coke-making radiance. The thermal infrared (TM6) is, however, particularly effective in registering these hot spots. In this dissertation, a new method is presented, which links the indigenous come-making radiance to recognition through TM751 band combination. During five years (from 1999 to 2004 at Shanxi Province), the quantity of indigenous coke-making sites distributed mainly on the plain increased by 10 times and the figures given by local authorities can in fact be approximated. It is thus expected that Landsat TM data will become a crucial tool in obtaining reliable, quantitative information for indigenous coke-making sites.
(4) The present dissertation presents an improved method for surface temperature retrieval algorithm of sub-pixel indigenous coke-making hot spots. The thermal data saturate for temperatures above 68℃and indigenous coke-making sites occupying less than a pixel requires modification of the methodology. The temperature estimation from the method is found to be in good with agreement with ground observations.
引文
[1] Ahern E, Janetos A. C., and E. Langham, 1998. Global Observation of Forest Cover: One Component of CEOS' Integrated Global Observing Strategy. Proceedings of the 27th International Symposium on Remote Sensing of Environment, Tromso, Norway, June 8-12.
[2] Anke Tetzlaff, 2004. Coal fire quantification using ASTER, ETM and BIRED satellite instrument data: [dissertation], Faculty of Geosciences, Ludwig-Maximilians-University,60-65.
[3] Arino, O., and J.M. Mellinotte, 1998. The 1993 Africa fire map. Int. J. Rem. Sens., 19: 2019- 2023.
[4] Arino, O. and Melinotte, J. M., 1995. Fire Index Atlas. Earth Obser. Quart. 50: 11-16.
[5] Arino, O., Melinotte, J. M., and Calabresi, G.: 1993. Fire, cloud, land, water: The 'Ionia' AVHRR CD-Browser of ESRIN. EOQ 41, ESA, EST EC, Noordwijk, July.
[6] Arino, O., and J-M. Rosaz, 1999. 1997 and 1998 World ATSR Fire Atlas using ERS-2 ATSR-2 Data. Proceedings of the Joint Fire Science Conference, Boise, 15-17, June.
[7] Barbosa, EM., J.-M. Gregoire, and J.M.C. Pereira, 1999. An algorithm for extracting burned areas from time series of AVHRR GAC data applied at continental scale. Rem. Sens. Environ, 69: 253-263.
[8] Bardintzeff, J.M., and Deniel, C., 1992. Magmatic evolution of Pacaya and Cerro Chiquito volcanological complex, Guatemala. Bulletin of Volcanology, 54: 267-283.
[9] Berk, A., Berstein, L. S., and Robertson, D. C. 1989. MODTRAN: A Moderate Resolution Model for Lowtran 7, GLTR-89-0122.
[10] Bernstein, R. L. 1982. Sea Surface Temperature Estimation Using the NOAA 6 Satellite Advanced Very High Resolution Radiometer. Journal of Geophysical Research, 87: 9455-9455.
[11] Becker, F., and Li, Z. L. 1990. Towards a local split window method over land surfaces. Int. J. Remote Sens. 3: 369-393.
[12] Becker F, Li Z. L. 1990. Towards a local split window method over land surfaces.International. Journal of Remote Sensing, 11 (3): 369-393.
[13] Belward, A.S., P.J. Kennedy and J.M. Gregoire, 1994.Limitation and potential of AVHRR GAC data for continental scale fire studies. Int. J. Rem. Sens., 15: 2215-2234.
[14] Belward, A.S., J.-M. Gregoire, G. D'Souza, S. Trigg, M. Trigg, M. Hawkes, J.-M. Serca, J.-L. Tireford, J.-M. Charlot, R. Vuattoux, In situ, real time fire detection using NOAA/AVHRR data. Proceedings of the VIA VHRR Data User's Meeting, 29.
[15] Belgirate, Italy, 29th June - 2nd July 1993, published by EUMETSAT, Darmstadt, Germany, EUM P 12, ISSN 10159576, 333-339.
[16]Bhattacharya BK, Dadhwal VK, 2003. Retrieval and validation of land surface temperature (LST) from NOAA AVHRR thermal images of Gujarat, India. Int J Remote Sensing 24: 1197-1206.
[17]Binenko, V. I., Dyachnenko, L.N.et al., 1974. Infrared mapping of large forest fires. In Atmospheric Radiation Studies, edited by K. Y. Kondratev (Keter Publishing House), p. 213.
[18] Boles, S. H. and Verbyla, D. L.: 1999, Effect of scan angle on AVHRR fire detection accuracy in interior Alaska, Int. J. Remote Sens. 20: 3437-3443.
[19] Cahoon, D.R., Jr., J.S. Levine, P. Minnis, G.M. Tennille, T.W. Yip, P.W. Heck, and B.J. Stocks, 1991. The Great Chinese Fire of 1987: A View from Space, Global Biomass Burning: Atmospheric, Climate, and Biospheric Implications, J.S. Levine, editor, MIT Press, Cambridge, MA, 61-66.
[20] Cahoon, D.R., Jr., B.J. Stocks, J.S. Levine, W.R. Cofer III, K.P. O'Neill, , 1992. Seasonal distribution of African savanna fires. Nature, 359: 812-815.
[21] Cahoon, D.R., Jr., B.J. Stocks, J.S. Levine, W.R. Cofer, and J.M. Pierson, 1994. Satellite analysis of the severe 1987 forest fires in northern China and southeastern Sibera. J. Geophys. Res., 99: 18627-18638.
[22] Cahoon, D. R., Stocks, B. J., Alexander, M. E., Baum, B. A., and Goldammer, J. G.: 2000. Wildland fire detection from space: Theory and application, In: J. L. Innes, M. Beniston and M. M. Verstraete, (eds.) Biomass Burning and its Inter-Relationships with the Climate System, Kluwer Academic Publishers, The Netherlands.
[23] Chatterjee, R.S., 2006. Coal fire mapping from satellite thermal IR data-A case example in Jharia Coalfield, Jharkhand, India. ISPRS Journal of Photogrammetry & Remote Sensing, 60: 113-128.
[24] Chesner, C.A., and Rose, W.I., 1984, Geochemistry and evolution of the Fuego volcanic complex, Guatemala. Journal of Volcanology and Geothermal Research, v. 21, p. 25-44.
[25] CHEN, W., 1992. Digital image processing application for coal fire remote sensing investigation. Remote Sensing for Land and Resources, 12: 21-24.
[26] Chuvieco, E., and R.G. Congalton, 1988. Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3: 41-53.
[27] Chu, A., Y. J. Kaufman, L. A. Remer, B. N. Holben, 1998. Remote sensing of smoke from MODIS Airborne Simulator During SCAR-B Experiment. J. Geophys. Res., 103: 31979-31988.
[28] Chuvieco, E., and R.G. Congalton, 1988. Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3: 41-53.
[29] Chuvieco, E., and M.P. Martin, 1994. A simple method for fire growth monitoring using AVHRR channel3 data. Int. J. Rem. Sens., 15: 3141-3146.
[30] Coakley, Jr, J.A. and F.P. Bretherton, 1982. Cloud cover from high-resolution scanner data: detecting and allowing for partially filled fields of view. J. Geophy. Res., 87: 4917-4932.
[31] CO. Justice, J.D. Kendall, P.R. Dowty, R.J. Scholes, 1996. Satellite remote sensing of fires during the SAFARI campaign using NOAA AVHRR data. J. Geophys. Res., 101 (D19) 23851-23863.
[32] Cresswell MP, Morse AP, Thomson MC, Connor SJ, 1999. Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model. Int J Remote Sensing, 20: 1125-1132.
[33] Crutzen, Paul J., 1976. The possible importance of CSO for the sulfate layer of the stratosphere .Geophysical Research Letters, 3(2): 73-76.
[34] Crutzen, P.J., L.E. Heidt, J.P. Krasnec, W.H. Pollock, and W. Seiler, 1979. Biomass burning as a source of atmospheric gases CO, H_2, N_2O, NO, CH_3CL and COS. Nature, 282: 253-256.
[35] Crutzen, P.J., and M.O. Andreae, 1990. Biomass burning in the tropics: Impact on atmospheric chemistry and biogeochemical cycle. Science, 250:1669-1678.
[36] D. A. Rothery, 1988. Volcano Monitoring Using Short Wavelength Infrared Data from Satellite. J. Geophy Res., 93: 7993-8008.
[37] Deschamps P Y, Phulpin T., 1980. Atmospheric corrections of infrared measurements of sea surface temperature using channels at 3.7μm, Hand 12 μm. Boundary Layer Meteorology, 18: 131-143.
[38] Dozier, J., 1981. A method for satellite identification of surface temperature fields of subpixel resolution. Rem. Sen. Environ., 11: 221-229.
[39] Duffield, W.A., Heiken, G.H., Wohletz, K.H., Maassen, L.W., Dengo, G, and McKee, E.H., 1989. Geology & geothermal potential of the Tecuamborro volcano area of Guatemala. Geothermal Resource Council Transactions, v. 13, p. 125-131.
[40]Dwyer, E., J.-M. Gregoire and J.-P. Malingreau, 1998. A global analysis of vegetation fires using satellite images: Spatial and temporal dynamics. Ambio, 27: 175-181.
[41] Eggers, A.A., Chavez, D., 1979. Temporal gravity variations at Pacaya volcano, Guatemala. Journal of Volcanology and Geothermal Research, v. 6, p. 391-402.
[42] Elvidge, C. D., Hobson, V. R., Baugh, K. E., Dietz, J. B., Shimabujuro, Y. E., Krug, T., Novo, E. M. L. M., and Echevarria, F. R.: 2001. DMSP-OLS estimation of tropical forest area impated by surface fires in Roraima, Brazil: 1995 versus 1998. Int. J. Remote Sens. 22: 2661-2673.
[43] Eric F. Vet-mote, Didier Tanre, Jean Luc Deuze, Maurice Herman, and Jean-Jacques Morcrette, 1997. Second Simulation of the Satellite Signal in the Solar Spectrum, 6s: An Overview[J]. IEEE Transactions on Geoscience and Remote Sensing, 35(3): 675-686
[44] Eva, H., and S. Flasse, 1996. Contextual and muliple-threshold algorithms for regional active fire detection with AVHRR data. Rem. Sens. Rev., 14: 333-351.
[45] Eva, H.D., and E. Lambin, 1998. Burnt area mapping in central Africa using AATSR data. Int. J. Rem. Sens., 18: 3473-3497.
[46] Flannigan, M.D., and T.H. Vonder Haar, 1986. Forest fire monitoring using NOAA satellite AVHRR, Can. J. Forest Res., 16: 975-982.
[47] Flasse, S.P., and P. Ceccato, 1996. A contextual algorithm for AVHRR fire detection, Int. J. Rem. Sens., 17: 419-424.
[48] Flynn, L. P., & Mouginis-Mark, P. J., 1994. Temperature of an active lava channel from spectral measurements, Kilauea Volcano, Hawaii. Bulletin of Volcanology, 56:297-301.
[49] Flynn, LP, Wright, R, Garbeil, H, Harris, AJL, and Pilger, E., 2002. A global thermal alert using MODIS: initial results from 2000-2001. Advances in Environmental Monitoring and Modeling, 1: 5-36.
[50] Francis, P. W., & McAllister, R., 1986. Volcanology from space: using the Landsat Thematic Mapper in the Central Andes. EOS — Transactions of the American Geophysical Union, 67, 170-171.
[51] Franca, J.R, J.M. Brustet, J. Fontan, 1993. Multispectral remote sensing of biomass burning in West Africa, J. Atmos. Chem., 22: 81-110.
[52] Fraser R H, Li Z. , Cihlar J., 2000. Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest. Remote Sens. Environ. 74: 362-376.
[53] Francois Petitcolin, Eric Vermote, 2002. Land surface reflectance, emissivity and temperature from MODIS middle and thermal infrared data. Remote sensing of environment, 83: 112-134.
[54]Giglio, L., J.D. Kendall, and C. O. Justice, 1999. Evaluation of global fire detection using simulated AVHRR infrared data. Int. J. Rem. Sens., 20: 1947-1985.
[55] Gorodetskii, A. K. 1985. Earth surface temperature determined from angular radiance distribution in atmospheric windows.Soviet Journal of Remote Sensing, 2: 981-996.
[56] Grégoire J-M., D. R. Cahoon, D. Stroppiana, Z. Li, S. Pinnock, H. Eva, O. Arino, J.M. Rosaz, and I. Csiszar, Forest fire monitoring and mapping for GOFC: current products and information networks based on NOAA-AVHRR, ERS-ATSR, and SPOT-VGT, Rem. Sens. Environ., this publication, 2000.
[57] Greenberg, J. P., and Zimmerman, P. R., 1984, No-nmethane hydrocarbons in remote tropical, continental, and marine atmospheres, J. Geophys. Res., 89: 4767-4778.
[58] Harris, A. J. L., Flynn, L. P., Dean, K., Pilger, E., Wooster, M., Okubo, C, Mouginis-Mark, P., Garbeil, H., Thornber, C, De la Cruz-Reyna, S.,Rothery, D., & Wright, R. (2000a). Real-time monitoring of volcanic hot spots with satellites. Remote Sensing of Active Volcanism, AGU Geophysical Monograph Series, 116, 139-159.
[59] Harris, A. J. L., Flynn, L. P.. Keszthelyi, L., Mouginis-Mark, P. J., Rowland, S. K., & Resing, J. A., 1998. Calculation of lava effusion rates from Landsat TM data. Bulletin of Volcanology, 60: 52-71.
[60] Harris, A. J. L., & Stevenson, D. S., 1997. Thermal observations of degassing open conduits and fumaroles at Stromboli and Vulcano using remotely sensed data. Journal of Volcanology and Geothermal Research, 76: 175—198.
[61]Horton, K.A., 1995. Airborne and satellite infrared imaging spectroscopy of active volcanism at Kilauea volcano, Hawaii. PhD Dissertation, University of Hawaii, 343 pp.
[62] Hovis, W.A. Jr., 1966. Infrared spectral reflectance of some common minerals. Apl. Opt., 5: 245-248.
[63] http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp
[64] http://landsat.usgs.gov/gallery/interactive/
[65] http://landsat.usgs.gov/gallery/main/
[66] http://srtm.csi.cgiar.org/
[67] http://www.esa.int/esaCP/index.html
[68] http://www.nasa.gov/
[69] http://www.fire.uni-freiburg.de/
[70] http://www.nfiieos.cn/html/eos/modis-eos.htm
[71] http://www.nfiieos.cn/html/project/home.htm
[72] http://volcanoes.usgs.gov/About/What/Monitor/RemoteSensing/RemoteSensing.html
[73] http://volcano.und.edu/vwdocs/volc_images/south_america/guat/fuego.html
[74] http://volcano.und.edu/vwdocs/current_volcs/pacaya/pacaya.html
[75] Ichoku, C., Y. Kaufman, L. Giglio, Z. Li, R. Fraser, J.-Z. Jin, B. Park, 2003. Comparative analysis of daytime fire detection algorithms using AVHRR data for the 1995 fire season in Canada: Perspective for MODIS. Int. J. Remote Sensing, 24(8): 1669-1690.
[76] Inoue, T., 1987. A cloud type classification with NOAA-7 split-window measurements. J. Geophy. Res., 92: 3991-4000.
[77] I. M. Watson, V. J. Realmuto, W. I. Rose, et al. 2004. Thermal infrared remote sensing of volcanic emissions using the moderate resolution imageing spectradiometer. Int. J. Remote Sensing, 135: 75-89.
[78] Jennifer M. Robinson, 1991. Firefrom space: Global fire evaluation using infrared remote sensing. Int. J. Remote Sensing, 12(1): 3-24.
[79] Jesus San-Miguel-Ayanz, Nicolas Ravail, Vaino Kelha, and Anibal Ollerd: 2005, Active Fire Detection for Fire Emergency anagement: Potential and Limitations Operational Use of Remote Sensing. Natural Hazards (2005) 35: 361-376.
[80] J. C. Roger, E. F. Vermote., 1998. A Method to Retrieve the Reflectivity Signature at 3.75μm from AVHRR Data. Remote Sensing of Environment, 64:103-114.
[81] John J.Qu, WeiGao, Menas Kafatos etc. 2006. Earth Science Satellite Remote Sensing, Volume I: Science and Instruments. Beijing: TSINGHUA UNIVERSITY PRESS.
[82] Justice, C., J.P. Malingreau, A.W. Setzer, 1993. Remote sensing of fires: Potential and limitations, Fire in the Environment (P.J. Crutzen and J.G. Goldammer, Eds.), pp. 77-88,
[83] Justice, C.O., and J.P. Malingreau (editors), 1993. The IGBP-DIS Satellite Fire Detection Algorithm Workshop Technical Report, IGBP-DIS Working Paper 9, NASA/GSFC, Greenbelt, Maryland, USA, February.
[84] Justice, CO., Kendall, J.D., Dowty, P.R., Scholes, R.J., 1996. Satellite remote sensing of fires during the SAFARI campaign using NOAA advanced very high resolution radiometer data. J. Geophy. Res, 101: 23851-23863.
[85] Justice, C. O., & Korontzi, S. (2001). A review of the status of satellite fire monitoring and the requirements for global environmental change research. In F. J. Ahern, J. Goldammer, & C. O. Justice (Eds.), Global and regional wildland fire monitoring from space: planning a coordinated international effort (pp. 1- 18). The Hague: SPB Academic Publishing.
[86] Justice, C. O., Giglio, L., Korontzi, S., Owens, J., Morissette, J. T., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F., and Kaufman, Y.: 2002, The MODIS fire product. Remote Sens. Environ, 3: 244—262.
[87] Kasischke, E.S., N.H.F. French, P. Harrell, N. Christensen, Jr., S.L. Ustin, D. Barry, 1993. Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data. Rem. Sen. Environ., 45: 61-71.
[88] Kaufman, Y. J., TUCKER, C. J., and FUNG, I., 1990. Remote sensing of biomass burning in the tropics. Journal of Geophysical Research, 95: 9927 - 9939.
[89] Kaufman, Y. J., L. Remer, 1994. Detection of forests using mid-IR reflectance: An application for aerosol studies. IEEE J. Geosc. Rem. Sens., 32: 672-683.
[90] Kaufman, Y.J., D. Tanre, and D.E. Ward, 1994. Remote sensing of biomass burning in the Amazon. Rem. Sens. Rev, 10: 51-90.
[91] Kaufman, Y. J. and R. S. Fraser, 1997. The effect of smoke particles on clouds and climate forcing. Science, 277, 1636-1639.
[92] Kaufman, Y. J., D. Tanre, L. Remer, E. Vermote, A. Chu, and B. N. Holben, 1997. Remote Sensing of Tropospheric Aerosol from EOS-MODIS over the Land Using Dark Targets and Dynamic Aerosol Models. J. Geophys. Res., 102: 17051-17067.
[93] Kaufman, Y.J., C. Justice, L. Flynn, J. Kendall, E. Prins, D.E. Ward, P. Menzel, and A. Setzer, 1998a. Potential global fire monitoring from EOS-MODIS, J. Geophy. Res., 103: 32215-32238.
[94] Kaufman, Y J., R. G Kleidman, M. D. King, 1998b. SCAR-B Fires in the Tropics: properties and their remote sensing from EOS-MODIS. J. Geophys. Res., 103: 31955-31969.
[95] Kneizys, F. X., Shettle. E. P.. Abreu, L. W, Chetwynd, J. H., Anderson, G. P., Gallery, W. O., Selby, J. E. A., & Clough, S. A., 1988. Users'guide to LOWTRAN 7. Air Force Geophysical Laboratory. Environmental Research Paper, 10: 101 -137.
[96] Kennedy, P.J., Belward, A.S., Gregoire, J.-M., 1994. An improved approach to fire monitoring in West Africa using AVHRR data. Int. J. Remote Sens, 15: 2235-2255.
[97] Kelha, V., Rauste, T., Hame, T., Septon, T., Buongiorno, A., Frauenberger, O., Soini, K., Vena¨ la¨ inen, A., San Miguel-Ayanz, J., and Vainio, T.: 2001, Promotion of space tecnologies for supporting the management of natural disasters: Earth observation technologies for decision support 'Fire Risk Management in Finland, Final report to the European Space Agency, VTT Automation, Espoo, Finland.
[98] KONG Xiang-sheng, Fang-Miao, Yuyang Dong , Hongfu Liu etc., 2005, Short Wavelength Infrared images for Indigenous Coke-Making Sites Monitoring in China P(?)eedings of the IEEE International Geoscience and Remote Sensing Symposium, (IGARSS'05), July 25-29, Seoul, Korea, vol. III, pp. 1785-1789
[99]Labed J, Stoll M P. 1991. Spatial Variability of Land Surface Emissivity in the Thermal Infrared Band: Spectral Signature and Effective Surface Temperature. Remote Sensing of Environment, 38: 1-17.
[100] Langaas S., 1992. Temporal and spatial distribution of Savannah fires in Senegal and the Gambia, West Africa, 1989-90, derived from muilti-temporal AVHRR night images. Int. J. Wildland Fire, 2: 21-36.
[101] Langaas S., 1993. A parameterised bispectral model for savanna fire detection using AVHRR night images. Int. J. Remote Sens., 14: 2245-2262.
[102] Lee, T.M., and RM. Tag, 1990. Improved detection of hotspots using the AVHRR 3.7 um channel. Bull. Amer. Meteoro. Soc. 71: 1722-1730.
[103] Xiaowen Li, Alan H Strahler, Mark A Friedl, 1999. A Conceptual Model for Effective Directional Emissivity from Nonisothermal Surfaces. IEEE Trans. Geosci. Remote Sens., 34 (5): 2508 -2517.
[104] Li, Z., H. Barker, and L. Moreau, 1995. The variable effect of clouds on atmospheric absorption of solar radiation. Nature, 376: 486-490.
[105] Li, Z., 1998. Influence of absorbing aerosols on the solar surface radiation budget. J. Climate, 11:5-17.
[106] Li, Z., Cihlar, J., Moreau, L., Huang, F., Lee, B., 1997. Monitoring fire activities in the boreal ecosystem. J. Geophy Res., 102: 29611-29624.
[107] Li, Z., S. Nadon, J. Cihlar, B. Stocks, 2002. Satellite mapping of Canadian boreal forest fires: Evaluation and comparison of algorithms. Int. J. Rem. Sens., 21:3071-3082.
[108] Li, Z., S. Nadon, J. Cihlar, 2002. Satellite detection of Canadian boreal forest fires: Development and application of an algorithm- Int. J. Rem. Sens., 21: 3057-3069.
[109] Li, Z., Khananian, A., Fraser, R., and Cihlar, J. 2001. Automatic Detection of Fire Smoke Using Artificial Neural Networks and Threshold Approaches Applied to AVHRR Imagery, IEEE T. Geosci. Remote Sens, 39: 1859-1870.
[110] Louis Giglioa, Jacques Descloitres, Christopher O. Justice, Yoram J. Kaufman, 2003. An Enhanced Contextual Fire Detection Algorithm for MODIS, Remote Sensing of Environment, 87: 273-282.
[111] Luke R Flynn, Andrew J.L. Harris, Robert Wright, 2001. Improved identification of volcanic features using Landsat 7 ETM+. Remote Sensing of Environment, 78: 180-193.
[112] Lyon, R. J. P., 1965.Analysis of rocks by spectral infrared emission (8～ 25μm). Economic Geology, 60: 715-736.
[113] Malingreau, J.R, 1990. The contribution of remote sensing to the global monitoring of fires in tropical and sub-tropical ecosystems. In: Fire in the Tropical Biota, edited by J.G. Goldammer, pp. 337-370. Berlin: Springer-Verlag.
[114] Malingreau J.R and C.J. Tucker, 1988. Large scale deforestation in the south-eastern Amazon basin. Ambio, 17: 49-55.
[115] Matson, M., & Dozier, J. 1981. Identification of subresolution high temperature sources using a thermal IR sensor. Photogrammetric Engineering and Remote Sensing, 47:1311 -1318.
[116] Matson M, Schneider S R., 1984. Fire Dectection Using the NOAA Series Satellite. NOAA Technical Report NESDIS 7.
[117] Matson, M., G Stephens, and J. Robinson., 1987. Fire detection using data from the NOAA-N satellites. International Journal of Remote Sensing, 8: 961-970.
[118] Maul, George A., 1981. Application of GOES visible-infrared data to quantifying mesoscale ocean surface temperture. Journal of Geophysical Research, Volume 86, Issue C9, p. 8007-8021.
[119] Malingreau, J.R and Justice, C.O., (editors), 1997. The IGBP-DIS Satellite Fire Detection Algorithm Workshop Technical Report, IGBP-DIS Working Paper 17, NASA/GSFC, Greenbelt, Maryland, USA, February.
[120] Martin, R, Ceccato, R, Flasse, S., and Downey, I., 1999. Fire detection and fire growth monitoring using satellite data. Remote Sensing of Large Wildfires in the European Mediterranean Basin. Chuvieco, E., (Ed.). Springer-Verlag Berlin/Heidelberg 3-540-65767-3, Ⅻ, 212 pp.
[121] Matson, M., & Dozier, J., 1981. Identification of subresolution high temperature sources using a thermal IR sensor. Photogrammetric Engineering and Remote Sensing, 47:1311-1318.
[122] Matson, M., G. Stephens, and J. Robinson, 1987. Fire detection using data from the NOAA-N satellites. Int. J. Rein. Sens., 8:961-970.
[123] McClain, E. R, 1981. Multiple atmospheric-window techniques for satellite-derived sea surface temperatures. COSPAR/SCOR/IUCRM Symposium, Oceanography from space, edited by J. Gower, Plenum Press, New York, 73-85.
[124] McClain, E. R, W.G. Pichel and C.C. Walton, 1985. Comparative performance of AVHRR-based multichannel sea surface temperatures. J. Geophys. Res. 90: 11587-11601.
[125] McClelland, L., Simkin, T., Summers, M., Nielsen, E., and Stein, T.C., 1989. Global Volcanism 1975-1985. Englewood Cliffs, New Jersey, Prentice Hall, 655 p.
[126] McMillin, L. M., 1975. Estimation of sea surface temperature from two infrared window measurements with different absorption. Journal of Geophysical Research., 80(36): 5113-5117.
[127] McClam, E P, and Abel, P G, 1977. Remote sensing of ocean temperature. Conference on Satellite Application to Marine Operation, New Orleans, LA, 15-17 November 1977,pp 1-9.
[128] McClam, E P, and Abel, P G.., 1980. Multiple atmospheric-window techniques for satellite-derived sea surface temperatures. COSPAR/SCOR/IUCRM Symposium, Oceanography from Space, Venice Italy 26-30 May.
[129] Mercado, R., Rose, W.I., and Matias, O., 1988. Eruptive history and volcanic hazard assessment of Fuego, Guatemala (abs.). Eos, Transactions of the American Geophysical Union, v. 69, p. 506.
[130] Menzel, W.P., E.C. Cutrim, and E.M. Prins, 1991. Geostationary satellite estimation of biomass burning in Amazonia during BASE-A. Global Biomass Burning (J.S. Levine, Ed), MIT Press, Cambridge, MA, 41-46.
[131] Muirhead, K. and A. Cracknell, 1985. Straw burning over Great Britain detected by AVHRR. Int. J. Rem. Sens., 6: 827-833.
[132] Nerry, F., LABED, J. and STOLL, M. P, 1988. Emissivity signatures in the thermal IR band for remote sensing: calibration procedure and method of measurement. Applied Optics, 27: 758-764.
[133] Oppenheimer, C., 1991. Lava flow cooling estimated from Landsat Thematic Mapper infrared data: the Lonquimay eruption (Chile, 1989).Journal of Geophysical Research, 96: 21865-21878.
[134] Oppenheimer, C, 1993. Infrared surveillance of crater lakes using satellite data. Journal of Volcanology and Geothermal Research, 55: 117-128.
[135] Oppenheimer, C, 1997. Remote sensing of the colour and temperature of volcanic lakes. Int. J. Remote Sensing, 18: 3 -37.
[136] Oppenheimer, C., 1998. Satellite observation of active carbonatite volcanism at 01 Dionyo Lengai, Tanzania. Int. J. Remote Sensing, 19: 55-64.
[137] Pereira, M.C., and A.W. Setzer, 1993. Spectral characteristics of deforestation fires in NOAA/AVHH images. Int. J. Rem. Sens., 14: 583-597.
[138] Pereira, J.M.C., 1999. A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping. IEEE Trans. Geosci. Remote Sens, 37: 217-226.
[139] Prata A. J. and Cechet R. P., 1999. An Assessment of the Accuracy of LandSurface Temperature Determination fromthe GMS-5 VISSR. Remote Sens. Environ, 67: 1—14.
[140] Prins, E.M., and W.P. Menzel, 1994. Trends in South American biomasss burning detected with the GOES VISSR radiometer atmospheric sounder from 1983 to 1991. J. Geophy.Res., 99: 16719-16735.
[141] Prins, E.M. and W.P. Menzel, 1992. Geostationary satellite detection of biomass burning in South America. Int. J. Remote Sensing, 13: 2783-2799.
[142] Prabhakara, C, Dalu, G, and Kunde, V. G.., 1974. Estimation of sea surface temperature from remote sensing in the 11 to 13 μm window region. J. Geophys. Res. 79(33): 5039-5044.
[143] Rauste, Y., E. Herland, H. Frelander, K. Soini, T. Kuoremaki, and A. Ruokari, 1997. Satellitebased forest fire detection for fire control in boreal forests. Int. J. Rem. Sens., 18:2641-2656.
[144] Razafimpanilo, H., R. Frouin, S.F. Iacobellis, and R.C.J. Somerville, 1995. Methodology for estimating burned area from AVHRR reflectance data. Rem. Sen. Environ., 54:273-289.
[145] Reid JS, Hobbs PV, Rangno AL, Hegg DA, 1999. Relationships between cloud droplet effective radius, liquid water content, and droplet concentration for warm clouds in Brazil embedded in biomass smoke. Journal of Geophyical Research, 104: 6145-6153.
[146] Robinson, J.M., 1991. Fire from space: Global fire evaluation using infrared remote sensing. Int. J. Rem. Sen., 12: 3-24.
[147] Robock, A. and M. Matson, 1983. Circumglobal transport of the EI Chichon volcano dust cloud. Science, 221:195-197.
[148] Rouse, J. W., Haas, R. H., Schell, J. A., and Deering, D. W., 1973. Monitoring vegetation systems in the great plains with ERTS. In 3rd ERTS Symposium, NASA SP-351, NASA, Washington, DC, Vol. 1, pp. 309-317.
[149] Salisbury, J.W., and D.M. D'Aria, 1994. Emissivity of terrestrial materials in the 3-5 μm atmospheric window. Rem. Sens. Envion. 47: 345-361.
[150] Setzer A.W., and M.C. Pereira, 1991. Operational detection of fires in Brazil with NOAAAVHRR, 24th Symp. Rem. Sens. Environ. Rio de Janeiro, Brazil, May.
[151] Setzer, A.W. and M.C. Pereira, 1991b. Amazonian biomass burnings in 1987 and an estimate of their tropospheric emission. Ambio, 20: 19-22.
[152] Setzer, A.W. and M.C. Pereira, 1992. Operational detection of fires in Brazil with NOAAAVHRR. Proc. 24th Int. Symp. Remote Sensing of the Environ., pp 469-482, Rio de Janeiro.
[153] Shunlin Liang, Hongliang Fang, Mingzhen Chen, et al, 2002. Validating MODISland surface reflectance and albedo products: methods and preliminary results. Remote sensing of environment, 83: 149-162.
[154] Setzer, A.W, M.C. Pereira, and Jr.A.C. Pereira, 1994. Satellite studies of biomass burning in Amazonia - some practical aspects. Rem. Sens. Rev., 10: 91-103.
[155] Setzer, A.W. and Malingreau, J.P., 1996. AVHRR monitoring of vegetation fires in the tropics: Toward the development of a global product. Biomass Burning and Global Change, (ed. J.S. Levine), p. 25-39, The MIT Press, Cambridge, Massachusetts, London, England.
[156] SINGH, S. M., 1988. Brightness temperature algorithms for Landsat Thematic Mapper data. Remote Sensing of Environment, 24: 509-512.
[157] Suits, G.H., 1989. Natural Sources, in The Infrared Handbook, Ed. W.L. Wolfe and G.J. Zissis, MI, pp. 3.1-3.154 (Ann Arbor, E.R.I.M.),
[158] Takashima, T., and Takayama, Y., 981. Emissivity and reflectance of the model sea surface for the use of AVHRR data of NOAA satellites. Pap. Meteorol. Geophys. 32(4): 267-274.
[159] Tapas Ranjian Martha, A. Bhattacharya, K. Vinod Kumar, 2005. Coal-fire detection and monitoring in Raniganj coalfield, India-A remote sensing approach. Current Science, 88(1): 21-24.
[160] Thomas Schmugge, Andrew French, Jerry C. Ritchiea, etc, 2002. Temperature and emissivity separation from multispectral thermal infrared observations. Remote Sensing of Environment, 79: 189-198.
[161] Voigt S., Tetzlaff A., Zhang J., et al., 2004. Integrating satellite remote sensing techniques for detection and analysis of uncontrolled coal seam fires in North China. International Journal of Coal Geology, 59:121-136.
[162] Wright, R., Flynn, LP, Garbeil, H, Harris, AJL, and Pilger, E., 2002. Automated volcanic eruption detection using MODIS. Remote Sensing of Environment, 82: 135-155.
[163] Wright, R., Flynn, LP, Garbeil, H, Harris, AJL, and Pilger, E., 2004. MODVOLC: near-real-time thermal monitoring of global volcanism. Journal of Volcanology and Geothermal Research, 135: 29-49.
[164] Yogesh Kant a, K.V.S. Badarinath, 1998. A method for estimatingthe land surface temperature from satellite data using emissivity derived from vegetation index. Current Science, 75: 139-145.
[165] Yogesh Kant a, K.V.S. Badarinath, 2002. Sub-pixel fire detection using Landsat-TM thermal data. Infrared Physics & Technology, 43: 383-387.
[166] Yogesh Kant, V. Krishna Prasad, K.V.S. Badarinath, 2000. Algorithm for detection of active fire zones using NOAA AVHRR data. Infrared Physics & Technology, 4: 29-34.
[167] Y.J. Kaufman, A.W. Setzer, C.O. Justice, C.J. Tucker, M.O. Pereria, I. Fung, 1990. Remote sensing of biomass burning in the tropics, in: Goldammer (Ed.). Fire in the Tropical Biota, Springer-Verlag, New York, pp. 371-399.
[168] Wan Z., Li zhaoliang, 1997. A physical-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Transaction on Geoscience and Remote Sensing, 35(4): 980-996.
[169] Zhang R H, Li Z L, Tang X, et al., 2002. Relativity of isothermal definitionand its scaling effects in quantitative thermal infrared remotesensing. Proceedings Of The First International Symposium On Recent Advance In Quantitative Remote Sensing, Valencia, p590-597.
[170] Zhang X., van Genderen, J.L. Kroonenberg, S.B., 1998. A method to evaluate the capability of Landsat-5 TM band 6 data for sub-pixel coal fare detection. International Journal of Remote Sensing, 18:3279-3288.
[171] Zhengming Wan, 1999. MODIS Land-Surface Temperature Algorithm theoretical basic document (version3.3.) Institute for Computational Earth System Science University of California, Santa Barbara.
[172] Zhukov, B., Oertel, D., 2001. Hot Spot Detection and Analysis Algorithm for the BIRD Mission, Algorithm Theoretical Basic Document (ATBD). DLR, Berlin, Germany.
[173] Zhengming Wan, Yulin Zhang, Qincheng Zhang, et al., 2002. Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote sensing of environment, 83:163-180.
[174] WARNER, T. A., and CHEN, X., 2001. Normalization of Landsat thermal imagery for the effects of solar heating and topography. International Journal of Remote Sensing, 22: 773-788.
[175] 陈述彭。“数字地球”战略及其制高点[J]。遥感学报，1999，3(4)：247-253。
[176] 陈良富，柳钦火。用Monte2Carlo方法模拟连续植被热辐射方向性[J]。遥感学报，2000，4 (4)：261—265。
[177] 陈良富，庄家礼，徐希儒。非同温混合像元热辐射有效比辐射率概念及其验证[J]。科学通报，2000，45(1)：22—29。
[178] 崔平，杨敏，朱玉廷，等，2004。焦炭和无烟煤混合物的热性质研究[J]。钢铁，39(7)：16-18。
[179] 范学良，程晓舫，许军。基于光谱辐射信息的高温目标图像识别。中国工程科学，2004，6(6)：57-62。
[180] 范闻捷，徐希孺。陆面组分温度的综合反演研究[J]。中国科学D，2005，35(10)：989-996。
[181] 郭华东，杨崇俊。建设国家对地观测体系，构筑“数字地球”[J]。遥感学报1999，3(2)：90-93。
[182] 何秋生，王新明，盛国英，等。炼焦过程中单环芳烃排放及源特征[J]。环境科学，2005，26，(5)：17-21。
[183] 何秋生，王新明，赵利容，等。炼焦过程中挥发性有机物成分谱特征初步研究[J]。中国环境监测，2005，21(1)：61—65。
[184] 国土资源部。截至2001年全国矿产储量简表[R]。北京：国土资源部，2002。
[185] 胡震峰。热红外遥感应用研究[J]。科技情报开发与经济，2004，14(1)：143-145。
[186] 康高峰，雷学武，万余庆，等。遥感技术在煤矿区地质灾害中的应用[J]。中国煤田地质，2000，12(2)：23-25。
[187] 孔祥生，苗放，刘鸿福，董宇阳。遥感技术在监测和评价土法炼焦污染源中的应用[J]。成都理工大学学报(自然科版)，2005，32(1)：92-96。
[188] 孔祥生，苗放，刘鸿福，董宇阳。利用多时相Landsat遥感图像数据对土法炼焦点进行动态监测—以山西省东南部地区为例[J]。遥感技术与应用，2005，20(5)：460-464。
[189] 刘诚，李亚军，赵长海，等。气象卫星亚像元火点面积和亮温估算方法[J]。应用气象学报，2004，15(3)：273-280。
[190] 李德仁。地球空间信息学的机遇[J]。武汉大学学报(信息科学版)，2004，29(9)：753-756。
[191] 李小文、汪骏发、王锦地、柳钦火。多角度与热红外遥感[M]。北京：科学出版社，2001。
[192] [美]P．H．斯韦恩S．M．戴维主编，朱振福等译。遥感定量方法[M]。北京：科学出版社，1984。
[193] 孙吉福，吴雁林。HJ-1卫星CCD相机入射光谱辐射亮度的分析[J]。航天返回与遥感，2003，24(2)：34-42。
[194] 田国良。热红外遥感[M]。北京：电子工业出版社，2006。
[195] 童庆禧。关于我国空间对地观测系统发展战略的若干思考[J]。中国测绘，2005，04：46-49。
[196] 徐冠华。论热红外遥感中的基础研究[J]。中国科学，2000，30(增刊)：1-5。
[197] 肖青，柳钦火，李小文，等，2003。热红外发射率光谱的野外测量方法与土壤热红外发射率特性研究。红外与毫米波学报，22，(5)：373-378。
[198] 徐希孺，陈良富，庄家礼。基于多角度热红外遥感的混合像元组分温度演化反演方法[J]。中国科学，D辑，2001，31(1)；81-88。
[199] 徐希孺，范闻捷，陈良富。开放的复杂目标热辐射特性的矩阵表达式[J]。中国科学，D辑，2001，31(12)：1046-1051。
[200] 徐希孺，柳钦火，陈家宜。遥感陆面温度[J]。北京大学学报(自然科学版)，1998，34(2-3)：248-253。
[201] 严文福，郑明东，宁万青，等。火道温度随结交时间与换向时间变化规律的研究[J]。煤炭学报，2004，29(1)：93-96。
[202] 杨国栋，吴涛，马小东。焦化厂周围农业土壤中芳烃类物质的污染状况[J]。农业环境保护，2000，19(2)：93-95。
[203] 杨国栋，石晓枫，杨靖辉，等．山西省焦炭生产地区的农村环境现状及污染防治对策[J]。环境保护，1998，(11)：15-20。
[204] 王文革。普朗克定律的一个新推论[J]，宇航计测技术，2005，25(2)：13-15。
[205] 王运明，诸葛端惠。土法焦化过程中的大气污染及对儿童机体免疫机能的影响[J]．职业与健康，2003，19(12)81-82。
[206] 王毅编著。2006，国际新一代对地观测系统的发展及其应用，北京：气象出版社。
[207] 尹达人，许龙生。关于热辐射体光谱“蓝移”问题的讨论[J]。红外技术，2000，22(5)：51-53。
[208] 杨国栋，孟庆珍。焦炭生产对空气以及土壤的污染调查[J]。环境与健康杂志，2000，17(1)：31-33。
[209] 虞继舜主编。煤化学[M]。北京：冶金工业出版社，2003。
[210] 张仁华，李召良，孙晓敏等。非同温系统中基尔霍夫定律的适用性和热量平衡原理[J]．中国科学D辑地球科学，2004，34(4)：350-358．
[2] Anke Tetzlaff, 2004. Coal fire quantification using ASTER, ETM and BIRED satellite instrument data: [dissertation], Faculty of Geosciences, Ludwig-Maximilians-University,60-65.
[3] Arino, O., and J.M. Mellinotte, 1998. The 1993 Africa fire map. Int. J. Rem. Sens., 19: 2019- 2023.
[4] Arino, O. and Melinotte, J. M., 1995. Fire Index Atlas. Earth Obser. Quart. 50: 11-16.
[5] Arino, O., Melinotte, J. M., and Calabresi, G.: 1993. Fire, cloud, land, water: The 'Ionia' AVHRR CD-Browser of ESRIN. EOQ 41, ESA, EST EC, Noordwijk, July.
[6] Arino, O., and J-M. Rosaz, 1999. 1997 and 1998 World ATSR Fire Atlas using ERS-2 ATSR-2 Data. Proceedings of the Joint Fire Science Conference, Boise, 15-17, June.
[7] Barbosa, EM., J.-M. Gregoire, and J.M.C. Pereira, 1999. An algorithm for extracting burned areas from time series of AVHRR GAC data applied at continental scale. Rem. Sens. Environ, 69: 253-263.
[8] Bardintzeff, J.M., and Deniel, C., 1992. Magmatic evolution of Pacaya and Cerro Chiquito volcanological complex, Guatemala. Bulletin of Volcanology, 54: 267-283.
[9] Berk, A., Berstein, L. S., and Robertson, D. C. 1989. MODTRAN: A Moderate Resolution Model for Lowtran 7, GLTR-89-0122.
[10] Bernstein, R. L. 1982. Sea Surface Temperature Estimation Using the NOAA 6 Satellite Advanced Very High Resolution Radiometer. Journal of Geophysical Research, 87: 9455-9455.
[11] Becker, F., and Li, Z. L. 1990. Towards a local split window method over land surfaces. Int. J. Remote Sens. 3: 369-393.
[12] Becker F, Li Z. L. 1990. Towards a local split window method over land surfaces.International. Journal of Remote Sensing, 11 (3): 369-393.
[13] Belward, A.S., P.J. Kennedy and J.M. Gregoire, 1994.Limitation and potential of AVHRR GAC data for continental scale fire studies. Int. J. Rem. Sens., 15: 2215-2234.
[14] Belward, A.S., J.-M. Gregoire, G. D'Souza, S. Trigg, M. Trigg, M. Hawkes, J.-M. Serca, J.-L. Tireford, J.-M. Charlot, R. Vuattoux, In situ, real time fire detection using NOAA/AVHRR data. Proceedings of the VIA VHRR Data User's Meeting, 29.
[15] Belgirate, Italy, 29th June - 2nd July 1993, published by EUMETSAT, Darmstadt, Germany, EUM P 12, ISSN 10159576, 333-339.
[16]Bhattacharya BK, Dadhwal VK, 2003. Retrieval and validation of land surface temperature (LST) from NOAA AVHRR thermal images of Gujarat, India. Int J Remote Sensing 24: 1197-1206.
[17]Binenko, V. I., Dyachnenko, L.N.et al., 1974. Infrared mapping of large forest fires. In Atmospheric Radiation Studies, edited by K. Y. Kondratev (Keter Publishing House), p. 213.
[18] Boles, S. H. and Verbyla, D. L.: 1999, Effect of scan angle on AVHRR fire detection accuracy in interior Alaska, Int. J. Remote Sens. 20: 3437-3443.
[19] Cahoon, D.R., Jr., J.S. Levine, P. Minnis, G.M. Tennille, T.W. Yip, P.W. Heck, and B.J. Stocks, 1991. The Great Chinese Fire of 1987: A View from Space, Global Biomass Burning: Atmospheric, Climate, and Biospheric Implications, J.S. Levine, editor, MIT Press, Cambridge, MA, 61-66.
[20] Cahoon, D.R., Jr., B.J. Stocks, J.S. Levine, W.R. Cofer III, K.P. O'Neill, , 1992. Seasonal distribution of African savanna fires. Nature, 359: 812-815.
[21] Cahoon, D.R., Jr., B.J. Stocks, J.S. Levine, W.R. Cofer, and J.M. Pierson, 1994. Satellite analysis of the severe 1987 forest fires in northern China and southeastern Sibera. J. Geophys. Res., 99: 18627-18638.
[22] Cahoon, D. R., Stocks, B. J., Alexander, M. E., Baum, B. A., and Goldammer, J. G.: 2000. Wildland fire detection from space: Theory and application, In: J. L. Innes, M. Beniston and M. M. Verstraete, (eds.) Biomass Burning and its Inter-Relationships with the Climate System, Kluwer Academic Publishers, The Netherlands.
[23] Chatterjee, R.S., 2006. Coal fire mapping from satellite thermal IR data-A case example in Jharia Coalfield, Jharkhand, India. ISPRS Journal of Photogrammetry & Remote Sensing, 60: 113-128.
[24] Chesner, C.A., and Rose, W.I., 1984, Geochemistry and evolution of the Fuego volcanic complex, Guatemala. Journal of Volcanology and Geothermal Research, v. 21, p. 25-44.
[25] CHEN, W., 1992. Digital image processing application for coal fire remote sensing investigation. Remote Sensing for Land and Resources, 12: 21-24.
[26] Chuvieco, E., and R.G. Congalton, 1988. Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3: 41-53.
[27] Chu, A., Y. J. Kaufman, L. A. Remer, B. N. Holben, 1998. Remote sensing of smoke from MODIS Airborne Simulator During SCAR-B Experiment. J. Geophys. Res., 103: 31979-31988.
[28] Chuvieco, E., and R.G. Congalton, 1988. Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3: 41-53.
[29] Chuvieco, E., and M.P. Martin, 1994. A simple method for fire growth monitoring using AVHRR channel3 data. Int. J. Rem. Sens., 15: 3141-3146.
[30] Coakley, Jr, J.A. and F.P. Bretherton, 1982. Cloud cover from high-resolution scanner data: detecting and allowing for partially filled fields of view. J. Geophy. Res., 87: 4917-4932.
[31] CO. Justice, J.D. Kendall, P.R. Dowty, R.J. Scholes, 1996. Satellite remote sensing of fires during the SAFARI campaign using NOAA AVHRR data. J. Geophys. Res., 101 (D19) 23851-23863.
[32] Cresswell MP, Morse AP, Thomson MC, Connor SJ, 1999. Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model. Int J Remote Sensing, 20: 1125-1132.
[33] Crutzen, Paul J., 1976. The possible importance of CSO for the sulfate layer of the stratosphere .Geophysical Research Letters, 3(2): 73-76.
[34] Crutzen, P.J., L.E. Heidt, J.P. Krasnec, W.H. Pollock, and W. Seiler, 1979. Biomass burning as a source of atmospheric gases CO, H_2, N_2O, NO, CH_3CL and COS. Nature, 282: 253-256.
[35] Crutzen, P.J., and M.O. Andreae, 1990. Biomass burning in the tropics: Impact on atmospheric chemistry and biogeochemical cycle. Science, 250:1669-1678.
[36] D. A. Rothery, 1988. Volcano Monitoring Using Short Wavelength Infrared Data from Satellite. J. Geophy Res., 93: 7993-8008.
[37] Deschamps P Y, Phulpin T., 1980. Atmospheric corrections of infrared measurements of sea surface temperature using channels at 3.7μm, Hand 12 μm. Boundary Layer Meteorology, 18: 131-143.
[38] Dozier, J., 1981. A method for satellite identification of surface temperature fields of subpixel resolution. Rem. Sen. Environ., 11: 221-229.
[39] Duffield, W.A., Heiken, G.H., Wohletz, K.H., Maassen, L.W., Dengo, G, and McKee, E.H., 1989. Geology & geothermal potential of the Tecuamborro volcano area of Guatemala. Geothermal Resource Council Transactions, v. 13, p. 125-131.
[40]Dwyer, E., J.-M. Gregoire and J.-P. Malingreau, 1998. A global analysis of vegetation fires using satellite images: Spatial and temporal dynamics. Ambio, 27: 175-181.
[41] Eggers, A.A., Chavez, D., 1979. Temporal gravity variations at Pacaya volcano, Guatemala. Journal of Volcanology and Geothermal Research, v. 6, p. 391-402.
[42] Elvidge, C. D., Hobson, V. R., Baugh, K. E., Dietz, J. B., Shimabujuro, Y. E., Krug, T., Novo, E. M. L. M., and Echevarria, F. R.: 2001. DMSP-OLS estimation of tropical forest area impated by surface fires in Roraima, Brazil: 1995 versus 1998. Int. J. Remote Sens. 22: 2661-2673.
[43] Eric F. Vet-mote, Didier Tanre, Jean Luc Deuze, Maurice Herman, and Jean-Jacques Morcrette, 1997. Second Simulation of the Satellite Signal in the Solar Spectrum, 6s: An Overview[J]. IEEE Transactions on Geoscience and Remote Sensing, 35(3): 675-686
[44] Eva, H., and S. Flasse, 1996. Contextual and muliple-threshold algorithms for regional active fire detection with AVHRR data. Rem. Sens. Rev., 14: 333-351.
[45] Eva, H.D., and E. Lambin, 1998. Burnt area mapping in central Africa using AATSR data. Int. J. Rem. Sens., 18: 3473-3497.
[46] Flannigan, M.D., and T.H. Vonder Haar, 1986. Forest fire monitoring using NOAA satellite AVHRR, Can. J. Forest Res., 16: 975-982.
[47] Flasse, S.P., and P. Ceccato, 1996. A contextual algorithm for AVHRR fire detection, Int. J. Rem. Sens., 17: 419-424.
[48] Flynn, L. P., & Mouginis-Mark, P. J., 1994. Temperature of an active lava channel from spectral measurements, Kilauea Volcano, Hawaii. Bulletin of Volcanology, 56:297-301.
[49] Flynn, LP, Wright, R, Garbeil, H, Harris, AJL, and Pilger, E., 2002. A global thermal alert using MODIS: initial results from 2000-2001. Advances in Environmental Monitoring and Modeling, 1: 5-36.
[50] Francis, P. W., & McAllister, R., 1986. Volcanology from space: using the Landsat Thematic Mapper in the Central Andes. EOS — Transactions of the American Geophysical Union, 67, 170-171.
[51] Franca, J.R, J.M. Brustet, J. Fontan, 1993. Multispectral remote sensing of biomass burning in West Africa, J. Atmos. Chem., 22: 81-110.
[52] Fraser R H, Li Z. , Cihlar J., 2000. Hotspot and NDVI differencing synergy (HANDS): a new technique for burned area mapping over boreal forest. Remote Sens. Environ. 74: 362-376.
[53] Francois Petitcolin, Eric Vermote, 2002. Land surface reflectance, emissivity and temperature from MODIS middle and thermal infrared data. Remote sensing of environment, 83: 112-134.
[54]Giglio, L., J.D. Kendall, and C. O. Justice, 1999. Evaluation of global fire detection using simulated AVHRR infrared data. Int. J. Rem. Sens., 20: 1947-1985.
[55] Gorodetskii, A. K. 1985. Earth surface temperature determined from angular radiance distribution in atmospheric windows.Soviet Journal of Remote Sensing, 2: 981-996.
[56] Grégoire J-M., D. R. Cahoon, D. Stroppiana, Z. Li, S. Pinnock, H. Eva, O. Arino, J.M. Rosaz, and I. Csiszar, Forest fire monitoring and mapping for GOFC: current products and information networks based on NOAA-AVHRR, ERS-ATSR, and SPOT-VGT, Rem. Sens. Environ., this publication, 2000.
[57] Greenberg, J. P., and Zimmerman, P. R., 1984, No-nmethane hydrocarbons in remote tropical, continental, and marine atmospheres, J. Geophys. Res., 89: 4767-4778.
[58] Harris, A. J. L., Flynn, L. P., Dean, K., Pilger, E., Wooster, M., Okubo, C, Mouginis-Mark, P., Garbeil, H., Thornber, C, De la Cruz-Reyna, S.,Rothery, D., & Wright, R. (2000a). Real-time monitoring of volcanic hot spots with satellites. Remote Sensing of Active Volcanism, AGU Geophysical Monograph Series, 116, 139-159.
[59] Harris, A. J. L., Flynn, L. P.. Keszthelyi, L., Mouginis-Mark, P. J., Rowland, S. K., & Resing, J. A., 1998. Calculation of lava effusion rates from Landsat TM data. Bulletin of Volcanology, 60: 52-71.
[60] Harris, A. J. L., & Stevenson, D. S., 1997. Thermal observations of degassing open conduits and fumaroles at Stromboli and Vulcano using remotely sensed data. Journal of Volcanology and Geothermal Research, 76: 175—198.
[61]Horton, K.A., 1995. Airborne and satellite infrared imaging spectroscopy of active volcanism at Kilauea volcano, Hawaii. PhD Dissertation, University of Hawaii, 343 pp.
[62] Hovis, W.A. Jr., 1966. Infrared spectral reflectance of some common minerals. Apl. Opt., 5: 245-248.
[63] http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp
[64] http://landsat.usgs.gov/gallery/interactive/
[65] http://landsat.usgs.gov/gallery/main/
[66] http://srtm.csi.cgiar.org/
[67] http://www.esa.int/esaCP/index.html
[68] http://www.nasa.gov/
[69] http://www.fire.uni-freiburg.de/
[70] http://www.nfiieos.cn/html/eos/modis-eos.htm
[71] http://www.nfiieos.cn/html/project/home.htm
[72] http://volcanoes.usgs.gov/About/What/Monitor/RemoteSensing/RemoteSensing.html
[73] http://volcano.und.edu/vwdocs/volc_images/south_america/guat/fuego.html
[74] http://volcano.und.edu/vwdocs/current_volcs/pacaya/pacaya.html
[75] Ichoku, C., Y. Kaufman, L. Giglio, Z. Li, R. Fraser, J.-Z. Jin, B. Park, 2003. Comparative analysis of daytime fire detection algorithms using AVHRR data for the 1995 fire season in Canada: Perspective for MODIS. Int. J. Remote Sensing, 24(8): 1669-1690.
[76] Inoue, T., 1987. A cloud type classification with NOAA-7 split-window measurements. J. Geophy. Res., 92: 3991-4000.
[77] I. M. Watson, V. J. Realmuto, W. I. Rose, et al. 2004. Thermal infrared remote sensing of volcanic emissions using the moderate resolution imageing spectradiometer. Int. J. Remote Sensing, 135: 75-89.
[78] Jennifer M. Robinson, 1991. Firefrom space: Global fire evaluation using infrared remote sensing. Int. J. Remote Sensing, 12(1): 3-24.
[79] Jesus San-Miguel-Ayanz, Nicolas Ravail, Vaino Kelha, and Anibal Ollerd: 2005, Active Fire Detection for Fire Emergency anagement: Potential and Limitations Operational Use of Remote Sensing. Natural Hazards (2005) 35: 361-376.
[80] J. C. Roger, E. F. Vermote., 1998. A Method to Retrieve the Reflectivity Signature at 3.75μm from AVHRR Data. Remote Sensing of Environment, 64:103-114.
[81] John J.Qu, WeiGao, Menas Kafatos etc. 2006. Earth Science Satellite Remote Sensing, Volume I: Science and Instruments. Beijing: TSINGHUA UNIVERSITY PRESS.
[82] Justice, C., J.P. Malingreau, A.W. Setzer, 1993. Remote sensing of fires: Potential and limitations, Fire in the Environment (P.J. Crutzen and J.G. Goldammer, Eds.), pp. 77-88,
[83] Justice, C.O., and J.P. Malingreau (editors), 1993. The IGBP-DIS Satellite Fire Detection Algorithm Workshop Technical Report, IGBP-DIS Working Paper 9, NASA/GSFC, Greenbelt, Maryland, USA, February.
[84] Justice, CO., Kendall, J.D., Dowty, P.R., Scholes, R.J., 1996. Satellite remote sensing of fires during the SAFARI campaign using NOAA advanced very high resolution radiometer data. J. Geophy. Res, 101: 23851-23863.
[85] Justice, C. O., & Korontzi, S. (2001). A review of the status of satellite fire monitoring and the requirements for global environmental change research. In F. J. Ahern, J. Goldammer, & C. O. Justice (Eds.), Global and regional wildland fire monitoring from space: planning a coordinated international effort (pp. 1- 18). The Hague: SPB Academic Publishing.
[86] Justice, C. O., Giglio, L., Korontzi, S., Owens, J., Morissette, J. T., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F., and Kaufman, Y.: 2002, The MODIS fire product. Remote Sens. Environ, 3: 244—262.
[87] Kasischke, E.S., N.H.F. French, P. Harrell, N. Christensen, Jr., S.L. Ustin, D. Barry, 1993. Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data. Rem. Sen. Environ., 45: 61-71.
[88] Kaufman, Y. J., TUCKER, C. J., and FUNG, I., 1990. Remote sensing of biomass burning in the tropics. Journal of Geophysical Research, 95: 9927 - 9939.
[89] Kaufman, Y. J., L. Remer, 1994. Detection of forests using mid-IR reflectance: An application for aerosol studies. IEEE J. Geosc. Rem. Sens., 32: 672-683.
[90] Kaufman, Y.J., D. Tanre, and D.E. Ward, 1994. Remote sensing of biomass burning in the Amazon. Rem. Sens. Rev, 10: 51-90.
[91] Kaufman, Y. J. and R. S. Fraser, 1997. The effect of smoke particles on clouds and climate forcing. Science, 277, 1636-1639.
[92] Kaufman, Y. J., D. Tanre, L. Remer, E. Vermote, A. Chu, and B. N. Holben, 1997. Remote Sensing of Tropospheric Aerosol from EOS-MODIS over the Land Using Dark Targets and Dynamic Aerosol Models. J. Geophys. Res., 102: 17051-17067.
[93] Kaufman, Y.J., C. Justice, L. Flynn, J. Kendall, E. Prins, D.E. Ward, P. Menzel, and A. Setzer, 1998a. Potential global fire monitoring from EOS-MODIS, J. Geophy. Res., 103: 32215-32238.
[94] Kaufman, Y J., R. G Kleidman, M. D. King, 1998b. SCAR-B Fires in the Tropics: properties and their remote sensing from EOS-MODIS. J. Geophys. Res., 103: 31955-31969.
[95] Kneizys, F. X., Shettle. E. P.. Abreu, L. W, Chetwynd, J. H., Anderson, G. P., Gallery, W. O., Selby, J. E. A., & Clough, S. A., 1988. Users'guide to LOWTRAN 7. Air Force Geophysical Laboratory. Environmental Research Paper, 10: 101 -137.
[96] Kennedy, P.J., Belward, A.S., Gregoire, J.-M., 1994. An improved approach to fire monitoring in West Africa using AVHRR data. Int. J. Remote Sens, 15: 2235-2255.
[97] Kelha, V., Rauste, T., Hame, T., Septon, T., Buongiorno, A., Frauenberger, O., Soini, K., Vena¨ la¨ inen, A., San Miguel-Ayanz, J., and Vainio, T.: 2001, Promotion of space tecnologies for supporting the management of natural disasters: Earth observation technologies for decision support 'Fire Risk Management in Finland, Final report to the European Space Agency, VTT Automation, Espoo, Finland.
[98] KONG Xiang-sheng, Fang-Miao, Yuyang Dong , Hongfu Liu etc., 2005, Short Wavelength Infrared images for Indigenous Coke-Making Sites Monitoring in China P(?)eedings of the IEEE International Geoscience and Remote Sensing Symposium, (IGARSS'05), July 25-29, Seoul, Korea, vol. III, pp. 1785-1789
[99]Labed J, Stoll M P. 1991. Spatial Variability of Land Surface Emissivity in the Thermal Infrared Band: Spectral Signature and Effective Surface Temperature. Remote Sensing of Environment, 38: 1-17.
[100] Langaas S., 1992. Temporal and spatial distribution of Savannah fires in Senegal and the Gambia, West Africa, 1989-90, derived from muilti-temporal AVHRR night images. Int. J. Wildland Fire, 2: 21-36.
[101] Langaas S., 1993. A parameterised bispectral model for savanna fire detection using AVHRR night images. Int. J. Remote Sens., 14: 2245-2262.
[102] Lee, T.M., and RM. Tag, 1990. Improved detection of hotspots using the AVHRR 3.7 um channel. Bull. Amer. Meteoro. Soc. 71: 1722-1730.
[103] Xiaowen Li, Alan H Strahler, Mark A Friedl, 1999. A Conceptual Model for Effective Directional Emissivity from Nonisothermal Surfaces. IEEE Trans. Geosci. Remote Sens., 34 (5): 2508 -2517.
[104] Li, Z., H. Barker, and L. Moreau, 1995. The variable effect of clouds on atmospheric absorption of solar radiation. Nature, 376: 486-490.
[105] Li, Z., 1998. Influence of absorbing aerosols on the solar surface radiation budget. J. Climate, 11:5-17.
[106] Li, Z., Cihlar, J., Moreau, L., Huang, F., Lee, B., 1997. Monitoring fire activities in the boreal ecosystem. J. Geophy Res., 102: 29611-29624.
[107] Li, Z., S. Nadon, J. Cihlar, B. Stocks, 2002. Satellite mapping of Canadian boreal forest fires: Evaluation and comparison of algorithms. Int. J. Rem. Sens., 21:3071-3082.
[108] Li, Z., S. Nadon, J. Cihlar, 2002. Satellite detection of Canadian boreal forest fires: Development and application of an algorithm- Int. J. Rem. Sens., 21: 3057-3069.
[109] Li, Z., Khananian, A., Fraser, R., and Cihlar, J. 2001. Automatic Detection of Fire Smoke Using Artificial Neural Networks and Threshold Approaches Applied to AVHRR Imagery, IEEE T. Geosci. Remote Sens, 39: 1859-1870.
[110] Louis Giglioa, Jacques Descloitres, Christopher O. Justice, Yoram J. Kaufman, 2003. An Enhanced Contextual Fire Detection Algorithm for MODIS, Remote Sensing of Environment, 87: 273-282.
[111] Luke R Flynn, Andrew J.L. Harris, Robert Wright, 2001. Improved identification of volcanic features using Landsat 7 ETM+. Remote Sensing of Environment, 78: 180-193.
[112] Lyon, R. J. P., 1965.Analysis of rocks by spectral infrared emission (8～ 25μm). Economic Geology, 60: 715-736.
[113] Malingreau, J.R, 1990. The contribution of remote sensing to the global monitoring of fires in tropical and sub-tropical ecosystems. In: Fire in the Tropical Biota, edited by J.G. Goldammer, pp. 337-370. Berlin: Springer-Verlag.
[114] Malingreau J.R and C.J. Tucker, 1988. Large scale deforestation in the south-eastern Amazon basin. Ambio, 17: 49-55.
[115] Matson, M., & Dozier, J. 1981. Identification of subresolution high temperature sources using a thermal IR sensor. Photogrammetric Engineering and Remote Sensing, 47:1311 -1318.
[116] Matson M, Schneider S R., 1984. Fire Dectection Using the NOAA Series Satellite. NOAA Technical Report NESDIS 7.
[117] Matson, M., G Stephens, and J. Robinson., 1987. Fire detection using data from the NOAA-N satellites. International Journal of Remote Sensing, 8: 961-970.
[118] Maul, George A., 1981. Application of GOES visible-infrared data to quantifying mesoscale ocean surface temperture. Journal of Geophysical Research, Volume 86, Issue C9, p. 8007-8021.
[119] Malingreau, J.R and Justice, C.O., (editors), 1997. The IGBP-DIS Satellite Fire Detection Algorithm Workshop Technical Report, IGBP-DIS Working Paper 17, NASA/GSFC, Greenbelt, Maryland, USA, February.
[120] Martin, R, Ceccato, R, Flasse, S., and Downey, I., 1999. Fire detection and fire growth monitoring using satellite data. Remote Sensing of Large Wildfires in the European Mediterranean Basin. Chuvieco, E., (Ed.). Springer-Verlag Berlin/Heidelberg 3-540-65767-3, Ⅻ, 212 pp.
[121] Matson, M., & Dozier, J., 1981. Identification of subresolution high temperature sources using a thermal IR sensor. Photogrammetric Engineering and Remote Sensing, 47:1311-1318.
[122] Matson, M., G. Stephens, and J. Robinson, 1987. Fire detection using data from the NOAA-N satellites. Int. J. Rein. Sens., 8:961-970.
[123] McClain, E. R, 1981. Multiple atmospheric-window techniques for satellite-derived sea surface temperatures. COSPAR/SCOR/IUCRM Symposium, Oceanography from space, edited by J. Gower, Plenum Press, New York, 73-85.
[124] McClain, E. R, W.G. Pichel and C.C. Walton, 1985. Comparative performance of AVHRR-based multichannel sea surface temperatures. J. Geophys. Res. 90: 11587-11601.
[125] McClelland, L., Simkin, T., Summers, M., Nielsen, E., and Stein, T.C., 1989. Global Volcanism 1975-1985. Englewood Cliffs, New Jersey, Prentice Hall, 655 p.
[126] McMillin, L. M., 1975. Estimation of sea surface temperature from two infrared window measurements with different absorption. Journal of Geophysical Research., 80(36): 5113-5117.
[127] McClam, E P, and Abel, P G, 1977. Remote sensing of ocean temperature. Conference on Satellite Application to Marine Operation, New Orleans, LA, 15-17 November 1977,pp 1-9.
[128] McClam, E P, and Abel, P G.., 1980. Multiple atmospheric-window techniques for satellite-derived sea surface temperatures. COSPAR/SCOR/IUCRM Symposium, Oceanography from Space, Venice Italy 26-30 May.
[129] Mercado, R., Rose, W.I., and Matias, O., 1988. Eruptive history and volcanic hazard assessment of Fuego, Guatemala (abs.). Eos, Transactions of the American Geophysical Union, v. 69, p. 506.
[130] Menzel, W.P., E.C. Cutrim, and E.M. Prins, 1991. Geostationary satellite estimation of biomass burning in Amazonia during BASE-A. Global Biomass Burning (J.S. Levine, Ed), MIT Press, Cambridge, MA, 41-46.
[131] Muirhead, K. and A. Cracknell, 1985. Straw burning over Great Britain detected by AVHRR. Int. J. Rem. Sens., 6: 827-833.
[132] Nerry, F., LABED, J. and STOLL, M. P, 1988. Emissivity signatures in the thermal IR band for remote sensing: calibration procedure and method of measurement. Applied Optics, 27: 758-764.
[133] Oppenheimer, C., 1991. Lava flow cooling estimated from Landsat Thematic Mapper infrared data: the Lonquimay eruption (Chile, 1989).Journal of Geophysical Research, 96: 21865-21878.
[134] Oppenheimer, C, 1993. Infrared surveillance of crater lakes using satellite data. Journal of Volcanology and Geothermal Research, 55: 117-128.
[135] Oppenheimer, C, 1997. Remote sensing of the colour and temperature of volcanic lakes. Int. J. Remote Sensing, 18: 3 -37.
[136] Oppenheimer, C., 1998. Satellite observation of active carbonatite volcanism at 01 Dionyo Lengai, Tanzania. Int. J. Remote Sensing, 19: 55-64.
[137] Pereira, M.C., and A.W. Setzer, 1993. Spectral characteristics of deforestation fires in NOAA/AVHH images. Int. J. Rem. Sens., 14: 583-597.
[138] Pereira, J.M.C., 1999. A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping. IEEE Trans. Geosci. Remote Sens, 37: 217-226.
[139] Prata A. J. and Cechet R. P., 1999. An Assessment of the Accuracy of LandSurface Temperature Determination fromthe GMS-5 VISSR. Remote Sens. Environ, 67: 1—14.
[140] Prins, E.M., and W.P. Menzel, 1994. Trends in South American biomasss burning detected with the GOES VISSR radiometer atmospheric sounder from 1983 to 1991. J. Geophy.Res., 99: 16719-16735.
[141] Prins, E.M. and W.P. Menzel, 1992. Geostationary satellite detection of biomass burning in South America. Int. J. Remote Sensing, 13: 2783-2799.
[142] Prabhakara, C, Dalu, G, and Kunde, V. G.., 1974. Estimation of sea surface temperature from remote sensing in the 11 to 13 μm window region. J. Geophys. Res. 79(33): 5039-5044.
[143] Rauste, Y., E. Herland, H. Frelander, K. Soini, T. Kuoremaki, and A. Ruokari, 1997. Satellitebased forest fire detection for fire control in boreal forests. Int. J. Rem. Sens., 18:2641-2656.
[144] Razafimpanilo, H., R. Frouin, S.F. Iacobellis, and R.C.J. Somerville, 1995. Methodology for estimating burned area from AVHRR reflectance data. Rem. Sen. Environ., 54:273-289.
[145] Reid JS, Hobbs PV, Rangno AL, Hegg DA, 1999. Relationships between cloud droplet effective radius, liquid water content, and droplet concentration for warm clouds in Brazil embedded in biomass smoke. Journal of Geophyical Research, 104: 6145-6153.
[146] Robinson, J.M., 1991. Fire from space: Global fire evaluation using infrared remote sensing. Int. J. Rem. Sen., 12: 3-24.
[147] Robock, A. and M. Matson, 1983. Circumglobal transport of the EI Chichon volcano dust cloud. Science, 221:195-197.
[148] Rouse, J. W., Haas, R. H., Schell, J. A., and Deering, D. W., 1973. Monitoring vegetation systems in the great plains with ERTS. In 3rd ERTS Symposium, NASA SP-351, NASA, Washington, DC, Vol. 1, pp. 309-317.
[149] Salisbury, J.W., and D.M. D'Aria, 1994. Emissivity of terrestrial materials in the 3-5 μm atmospheric window. Rem. Sens. Envion. 47: 345-361.
[150] Setzer A.W., and M.C. Pereira, 1991. Operational detection of fires in Brazil with NOAAAVHRR, 24th Symp. Rem. Sens. Environ. Rio de Janeiro, Brazil, May.
[151] Setzer, A.W. and M.C. Pereira, 1991b. Amazonian biomass burnings in 1987 and an estimate of their tropospheric emission. Ambio, 20: 19-22.
[152] Setzer, A.W. and M.C. Pereira, 1992. Operational detection of fires in Brazil with NOAAAVHRR. Proc. 24th Int. Symp. Remote Sensing of the Environ., pp 469-482, Rio de Janeiro.
[153] Shunlin Liang, Hongliang Fang, Mingzhen Chen, et al, 2002. Validating MODISland surface reflectance and albedo products: methods and preliminary results. Remote sensing of environment, 83: 149-162.
[154] Setzer, A.W, M.C. Pereira, and Jr.A.C. Pereira, 1994. Satellite studies of biomass burning in Amazonia - some practical aspects. Rem. Sens. Rev., 10: 91-103.
[155] Setzer, A.W. and Malingreau, J.P., 1996. AVHRR monitoring of vegetation fires in the tropics: Toward the development of a global product. Biomass Burning and Global Change, (ed. J.S. Levine), p. 25-39, The MIT Press, Cambridge, Massachusetts, London, England.
[156] SINGH, S. M., 1988. Brightness temperature algorithms for Landsat Thematic Mapper data. Remote Sensing of Environment, 24: 509-512.
[157] Suits, G.H., 1989. Natural Sources, in The Infrared Handbook, Ed. W.L. Wolfe and G.J. Zissis, MI, pp. 3.1-3.154 (Ann Arbor, E.R.I.M.),
[158] Takashima, T., and Takayama, Y., 981. Emissivity and reflectance of the model sea surface for the use of AVHRR data of NOAA satellites. Pap. Meteorol. Geophys. 32(4): 267-274.
[159] Tapas Ranjian Martha, A. Bhattacharya, K. Vinod Kumar, 2005. Coal-fire detection and monitoring in Raniganj coalfield, India-A remote sensing approach. Current Science, 88(1): 21-24.
[160] Thomas Schmugge, Andrew French, Jerry C. Ritchiea, etc, 2002. Temperature and emissivity separation from multispectral thermal infrared observations. Remote Sensing of Environment, 79: 189-198.
[161] Voigt S., Tetzlaff A., Zhang J., et al., 2004. Integrating satellite remote sensing techniques for detection and analysis of uncontrolled coal seam fires in North China. International Journal of Coal Geology, 59:121-136.
[162] Wright, R., Flynn, LP, Garbeil, H, Harris, AJL, and Pilger, E., 2002. Automated volcanic eruption detection using MODIS. Remote Sensing of Environment, 82: 135-155.
[163] Wright, R., Flynn, LP, Garbeil, H, Harris, AJL, and Pilger, E., 2004. MODVOLC: near-real-time thermal monitoring of global volcanism. Journal of Volcanology and Geothermal Research, 135: 29-49.
[164] Yogesh Kant a, K.V.S. Badarinath, 1998. A method for estimatingthe land surface temperature from satellite data using emissivity derived from vegetation index. Current Science, 75: 139-145.
[165] Yogesh Kant a, K.V.S. Badarinath, 2002. Sub-pixel fire detection using Landsat-TM thermal data. Infrared Physics & Technology, 43: 383-387.
[166] Yogesh Kant, V. Krishna Prasad, K.V.S. Badarinath, 2000. Algorithm for detection of active fire zones using NOAA AVHRR data. Infrared Physics & Technology, 4: 29-34.
[167] Y.J. Kaufman, A.W. Setzer, C.O. Justice, C.J. Tucker, M.O. Pereria, I. Fung, 1990. Remote sensing of biomass burning in the tropics, in: Goldammer (Ed.). Fire in the Tropical Biota, Springer-Verlag, New York, pp. 371-399.
[168] Wan Z., Li zhaoliang, 1997. A physical-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data. IEEE Transaction on Geoscience and Remote Sensing, 35(4): 980-996.
[169] Zhang R H, Li Z L, Tang X, et al., 2002. Relativity of isothermal definitionand its scaling effects in quantitative thermal infrared remotesensing. Proceedings Of The First International Symposium On Recent Advance In Quantitative Remote Sensing, Valencia, p590-597.
[170] Zhang X., van Genderen, J.L. Kroonenberg, S.B., 1998. A method to evaluate the capability of Landsat-5 TM band 6 data for sub-pixel coal fare detection. International Journal of Remote Sensing, 18:3279-3288.
[171] Zhengming Wan, 1999. MODIS Land-Surface Temperature Algorithm theoretical basic document (version3.3.) Institute for Computational Earth System Science University of California, Santa Barbara.
[172] Zhukov, B., Oertel, D., 2001. Hot Spot Detection and Analysis Algorithm for the BIRD Mission, Algorithm Theoretical Basic Document (ATBD). DLR, Berlin, Germany.
[173] Zhengming Wan, Yulin Zhang, Qincheng Zhang, et al., 2002. Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote sensing of environment, 83:163-180.
[174] WARNER, T. A., and CHEN, X., 2001. Normalization of Landsat thermal imagery for the effects of solar heating and topography. International Journal of Remote Sensing, 22: 773-788.
[175] 陈述彭。“数字地球”战略及其制高点[J]。遥感学报，1999，3(4)：247-253。
[176] 陈良富，柳钦火。用Monte2Carlo方法模拟连续植被热辐射方向性[J]。遥感学报，2000，4 (4)：261—265。
[177] 陈良富，庄家礼，徐希儒。非同温混合像元热辐射有效比辐射率概念及其验证[J]。科学通报，2000，45(1)：22—29。
[178] 崔平，杨敏，朱玉廷，等，2004。焦炭和无烟煤混合物的热性质研究[J]。钢铁，39(7)：16-18。
[179] 范学良，程晓舫，许军。基于光谱辐射信息的高温目标图像识别。中国工程科学，2004，6(6)：57-62。
[180] 范闻捷，徐希孺。陆面组分温度的综合反演研究[J]。中国科学D，2005，35(10)：989-996。
[181] 郭华东，杨崇俊。建设国家对地观测体系，构筑“数字地球”[J]。遥感学报1999，3(2)：90-93。
[182] 何秋生，王新明，盛国英，等。炼焦过程中单环芳烃排放及源特征[J]。环境科学，2005，26，(5)：17-21。
[183] 何秋生，王新明，赵利容，等。炼焦过程中挥发性有机物成分谱特征初步研究[J]。中国环境监测，2005，21(1)：61—65。
[184] 国土资源部。截至2001年全国矿产储量简表[R]。北京：国土资源部，2002。
[185] 胡震峰。热红外遥感应用研究[J]。科技情报开发与经济，2004，14(1)：143-145。
[186] 康高峰，雷学武，万余庆，等。遥感技术在煤矿区地质灾害中的应用[J]。中国煤田地质，2000，12(2)：23-25。
[187] 孔祥生，苗放，刘鸿福，董宇阳。遥感技术在监测和评价土法炼焦污染源中的应用[J]。成都理工大学学报(自然科版)，2005，32(1)：92-96。
[188] 孔祥生，苗放，刘鸿福，董宇阳。利用多时相Landsat遥感图像数据对土法炼焦点进行动态监测—以山西省东南部地区为例[J]。遥感技术与应用，2005，20(5)：460-464。
[189] 刘诚，李亚军，赵长海，等。气象卫星亚像元火点面积和亮温估算方法[J]。应用气象学报，2004，15(3)：273-280。
[190] 李德仁。地球空间信息学的机遇[J]。武汉大学学报(信息科学版)，2004，29(9)：753-756。
[191] 李小文、汪骏发、王锦地、柳钦火。多角度与热红外遥感[M]。北京：科学出版社，2001。
[192] [美]P．H．斯韦恩S．M．戴维主编，朱振福等译。遥感定量方法[M]。北京：科学出版社，1984。
[193] 孙吉福，吴雁林。HJ-1卫星CCD相机入射光谱辐射亮度的分析[J]。航天返回与遥感，2003，24(2)：34-42。
[194] 田国良。热红外遥感[M]。北京：电子工业出版社，2006。
[195] 童庆禧。关于我国空间对地观测系统发展战略的若干思考[J]。中国测绘，2005，04：46-49。
[196] 徐冠华。论热红外遥感中的基础研究[J]。中国科学，2000，30(增刊)：1-5。
[197] 肖青，柳钦火，李小文，等，2003。热红外发射率光谱的野外测量方法与土壤热红外发射率特性研究。红外与毫米波学报，22，(5)：373-378。
[198] 徐希孺，陈良富，庄家礼。基于多角度热红外遥感的混合像元组分温度演化反演方法[J]。中国科学，D辑，2001，31(1)；81-88。
[199] 徐希孺，范闻捷，陈良富。开放的复杂目标热辐射特性的矩阵表达式[J]。中国科学，D辑，2001，31(12)：1046-1051。
[200] 徐希孺，柳钦火，陈家宜。遥感陆面温度[J]。北京大学学报(自然科学版)，1998，34(2-3)：248-253。
[201] 严文福，郑明东，宁万青，等。火道温度随结交时间与换向时间变化规律的研究[J]。煤炭学报，2004，29(1)：93-96。
[202] 杨国栋，吴涛，马小东。焦化厂周围农业土壤中芳烃类物质的污染状况[J]。农业环境保护，2000，19(2)：93-95。
[203] 杨国栋，石晓枫，杨靖辉，等．山西省焦炭生产地区的农村环境现状及污染防治对策[J]。环境保护，1998，(11)：15-20。
[204] 王文革。普朗克定律的一个新推论[J]，宇航计测技术，2005，25(2)：13-15。
[205] 王运明，诸葛端惠。土法焦化过程中的大气污染及对儿童机体免疫机能的影响[J]．职业与健康，2003，19(12)81-82。
[206] 王毅编著。2006，国际新一代对地观测系统的发展及其应用，北京：气象出版社。
[207] 尹达人，许龙生。关于热辐射体光谱“蓝移”问题的讨论[J]。红外技术，2000，22(5)：51-53。
[208] 杨国栋，孟庆珍。焦炭生产对空气以及土壤的污染调查[J]。环境与健康杂志，2000，17(1)：31-33。
[209] 虞继舜主编。煤化学[M]。北京：冶金工业出版社，2003。
[210] 张仁华，李召良，孙晓敏等。非同温系统中基尔霍夫定律的适用性和热量平衡原理[J]．中国科学D辑地球科学，2004，34(4)：350-358．