收稿：2019-05-07，
纸质出版：2020-05-07
移动端阅览
森林火灾是最为常见的灾害之一，严重危及人类生命安全。及时准确监测森林火灾的发生及火场状况，对应对火灾及减少损失至关重要。当前，森林火灾卫星遥感监测主要以低空间分辨率的卫星遥感为主，空间分辨率过低导致无法探测规模较小火灾及掌握详细火场态势。针对这一问题，结合近些年中高空间分辨率卫星观测、共享及处理能力的发展，本文从森林火灾卫星遥感监测的基本原理、当前可用中高空间分辨率卫星数据及其特点、中高分辨率森林着火区监测算法，以及数据共享与云端存储与计算等4个技术环节，对森林火灾中高分辨率卫星遥感监测当前研究现状与存在问题进行了总结，阐述了近实时中高空间分辨率森林火灾监测系统的可行性。近实时中高空间分辨率森林火灾监测系统可对已有低空间分辨率森林火灾监测体系形成重要补充，依托其空间分辨率的优势有助于及早、准确发现小规模火情，进而为森林火灾的防治与管理提供更好支撑。
Forest fires are common disasters that seriously endanger human life. Timely and accurate monitoring of forest fires is essential for fighting fires and reducing losses. At present
active forest fire monitoring mainly uses polar or geostationary orbit satellites with low spatial resolution. The spatial resolution is extremely low
making it difficult to detect small-scale fires and control fire conditions. This paper proposes a near-real-time forest fire monitoring system with medium and high spatial resolutions on the basis of the rapid development of medium and high spatial resolution satellite sensors
data sharing policy
and data processing capabilities in recent years.
This paper summarizes the research status and related shortage in four aspects
namely
basic principles of forest fire monitoring
currently available medium and high spatial resolution satellite data and their characteristics
active forest fire monitoring algorithms and data sharing
and cloud storage and computation
and analyze the feasibility of a near-real-time forest fire monitoring system with medium and high spatial resolutions. The proposed near-real-time fire monitoring system with medium and high spatial resolutions can serve as an important supplement to existing forest fire monitoring systems with coarse resolution. It can early and accurately detect small-scale forest fires and provide support for forest fire prevention and management because of its high spatial resolution.
Csiszar I A and Schroeder W . 2008 . Short-term observations of the temporal development of active fires from consecutive same-day ETM+ and ASTER imagery in the Amazon: implications for active fire product validation . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 1 ( 4 ): 248 - 253 [ DOI: 10.1109/JSTARS.2008.2011377 http://dx.doi.org/10.1109/JSTARS.2008.2011377 ]
Delp C L , Lee C Y , De Weck O , Bishop C , Analzone E , Gostelow R and Dutenhoffer C . 2008 . The challenge of model‐based systems engineering for space systems . Insight , 11 ( 5 ): 14 - 18 [ DOI: 10.1002/inst.200811514 http://dx.doi.org/10.1002/inst.200811514 ]
Drusch M , Del Bello U , Carlier S , Colin O , Fernandez V , Gascon F , Hoersch B , Isola C , Laberinti P , Martimort P , Meygret A , Spoto F , Sy O , Marchese F and Bargellini P . 2012 . Sentinel-2: ESA’s optical high-resolution mission for GMES operational services . Remote sensing of Environment , 120 : 25 - 36 [ DOI: 10.1016/j.rse.2011.11.026 http://dx.doi.org/10.1016/j.rse.2011.11.026 ]
Flannigan M D and Haar T H V . 1986 . Forest fire monitoring using NOAA satellite AVHRR . Canadian Journal of Forest Research , 16 ( 5 ): 975 - 982 [ DOI: 10.1139/x86-171 http://dx.doi.org/10.1139/x86-171 ]
Flasse S P and Ceccato P . 1996 . A contextual algorithm for AVHRR fire detection . International Journal of Remote Sensing , 17 ( 2 ): 419 - 424 [ DOI: 10.1080/01431169608949018 http://dx.doi.org/10.1080/01431169608949018 ]
Fu Y C , Yuan X X , Song Y , Chen M and Guo T S . 2009 . Fire line detection method of forest fire based on Modis image . Journal of Remote Sensing , 13 ( 03 ): 542 - 548
付迎春 , 袁修孝 , 宋妍 , 陈蜜 , 郭泰圣 . 2009 基于MODIS影像的森林火灾火线检测方法 . 遥感学报 , 13 ( 03 ): 542 - 548
Giglio L , Csiszar I , Restás Á , Morisette J T , Schroeder W , Morton D and Justice C O . 2008 . Active fire detection and characterization with the advanced spaceborne thermal emission and reflection radiometer (ASTER) . Remote Sensing of Environment , 112 ( 6 ): 3055 - 3063 [ DOI: 10.1016/j.rse.2008.03.003 http://dx.doi.org/10.1016/j.rse.2008.03.003 ]
Giglio L , Descloitres J , Justice C O and Kaufman Y J . 2003 . An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment, 87( 2 / 3 ): 273 - 282 [ DOI: 10.1016/S0034-4257(03)00184-6 http://dx.doi.org/10.1016/S0034-4257(03)00184-6 ]
Giglio L , Van Der Werf G R , Randerson J T , Collatz G J and Kasibhatla P . 2006 . Global estimation of burned area using MODIS active fire observations . Atmospheric Chemistry and Physics , 6 ( 4 ): 957 - 974 [ DOI: 10.5194/acp-6-957-2006 http://dx.doi.org/10.5194/acp-6-957-2006 ]
Gorelick N , Hancher M , Dixon M , Ilyushchenko S , Thau D and Moore R . 2017 . Google earth engine: planetary-scale geospatial analysis for everyone . Remote Sensing of Environment , 202 : 18 - 27 [ DOI: 10.1016/j.rse.2017.06.031 http://dx.doi.org/10.1016/j.rse.2017.06.031 ]
Goward S N , Masek J G , Williams D L , Irons J R and Thompson R J . 2001 . The Landsat 7 mission: terrestrial research and applications for the 21st century. Remote Sensing of Environment, 78( 1 / 2 ): 3 - 12 [ DOI: 10.1016/S0034-4257(01)00262-0 http://dx.doi.org/10.1016/S0034-4257(01)00262-0 ]
Gu X F and Tong X D . 2015 . Overview of China earth observation satellite programs [space agencies] . IEEE Geoscience and Remote Sensing Magazine , 3 ( 3 ): 113 - 129 [ DOI: 10.1109/MGRS.2015.2467172 http://dx.doi.org/10.1109/MGRS.2015.2467172 ]
Harris R and Baumann I . 2015 . Open data policies and satellite Earth observation . Space Policy , 32 : 44 - 53 [ DOI: 10.1016/j.spacepol.2015.01.001 http://dx.doi.org/10.1016/j.spacepol.2015.01.001 ]
He Q J and Liu C . 2008 An improved algorithm for adaptive fire detection based on Modis data . Journal of Remote Sensing , 12 ( 03 ): 448 - 453 .
何全军 , 刘诚 . 2008 . MODIS数据自适应火点检测的改进算法 . 遥感学报 , 12 ( 03 ): 448 - 453
He Y , Yang J , Ma Y , Liu J B , Chen P , Li X P and Yang Y F . 2016 Fire detection method based on landsat-8 landsat data . Journal of Infrared and Millimeter Wave , 35 ( 05 ): 600 - 608
何阳 , 杨进 , 马勇 , 刘建波 , 陈甫 , 李信鹏 , 杨轶斐 . 2016 基于Landsat-8陆地卫星数据的火点检测方法 . 红外与毫米波学报 , 35 ( 05 ): 600 - 608
Hua L Z and Shao G F . 2017 . The progress of operational forest fire monitoring with infrared remote sensing . Journal of Forestry Research , 28 ( 2 ): 215 - 229 [ DOI: 10.1007/s11676-016-0361-8 http://dx.doi.org/10.1007/s11676-016-0361-8 ]
Kaufman Y J , Justice C O , Flynn L P , Kendall J D , Prins E M , Giglio L , Ward D E , Menzel W P and Setzer A W . 1998 . Potential global fire monitoring from EOS‐MODIS . Journal of Geophysical Research : Atmospheres , 103 ( D24 ): 32215 - 32238 [ DOI: 10.1029/98JD01644 http://dx.doi.org/10.1029/98JD01644 ]
Kumar S S and Roy D P . 2018 . Global operational land imager Landsat-8 reflectance-based active fire detection algorithm . International Journal of Digital Earth , 11 ( 2 ): 154 - 178 [ DOI: 10.1080/17538947.2017.1391341 http://dx.doi.org/10.1080/17538947.2017.1391341 ]
Lentile L B , Holden Z A , Smith A M S , Falkowski M J , Hudak A T , Morgan P , Lewis S A , Gessler P E and Benson N C . 2006 . Remote sensing techniques to assess active fire characteristics and post-fire effects . International Journal of Wildland Fire , 15 ( 3 ): 319 - 345 [ DOI: 10.1071/WF05097 http://dx.doi.org/10.1071/WF05097 ]
Lin Z Y , Chen F , Niu Z , Li B , Yu B , Jia H C and Zhang M M . 2018 . An active fire detection algorithm based on multi-temporal FengYun-3C VIRR data . Remote Sensing of Environment , 211 : 376 - 387 [ DOI: 10.1016/j.rse.2018.04.027 http://dx.doi.org/10.1016/j.rse.2018.04.027 ]
Martell D L . 2015 . A review of recent forest and wildland fire management decision support systems research . Current Forestry Reports , 1 ( 2 ): 128 - 137 [ DOI: 10.1007/s40725-015-0011-y http://dx.doi.org/10.1007/s40725-015-0011-y ]
Martone M , Rizzoli P , Wecklich C , González C , Bueso-Bello J L , Valdo P , Schulze D , Zink M , Krieger G and Moreira A . 2018 . The global forest/non-forest map from TanDEM-X interferometric SAR data . Remote Sensing of Environment , 205 : 352 - 373 [ DOI: 10.1016/j.rse.2017.12.002 http://dx.doi.org/10.1016/j.rse.2017.12.002 ]
Meng R , Dennison P E , Huang C Q , Moritz M A and D'Antonio C . 2015 . Effects of fire severity and post-fire climate on short-term vegetation recovery of mixed-conifer and red fir forests in the Sierra Nevada Mountains of California . Remote Sensing of Environment , 171 : 311 - 325 [ DOI: 10.1016/j.rse.2015.10.024 http://dx.doi.org/10.1016/j.rse.2015.10.024 ]
Oppenheimer C. c 1991 . Thermal distributions of hot volcanic surfaces constrained using three infrared bands of remote sensing data . Geophysical Research Letters , 431 - 434 [ DOI: 10.1029/93GL00500 http://dx.doi.org/10.1029/93GL00500 ]
Rauste Y , Herland E , Frelander H , Soini K , Kuoremaki T and Ruokari A . 1997 . Satellite-based forest fire detection for fire control in boreal forests . International Journal of Remote Sensing , 18 ( 12 ): 2641 - 2656 [ DOI: 10.1080/014311697217512 http://dx.doi.org/10.1080/014311697217512 ]
Roy D P , Wulder M A , Loveland T R , Woodcock C E , Allen R G , Anderson M C , Helder D , Irons J R , Johnson D M , Kennedy R , Scambos T A , Schaaf C B , Schott J R , Sheng Y , Vermote E F , Belward A S , Bindschadler R , Cohen W B , Gao F , Hipple J D , Hostert P , Huntington J , Justice C O , Kilic A , Kovalskyy V , Lee Z P , Lymburner L , Masek J G , McCorkel J , Shuai Y , Trezza R , Vogelmann J , Wynne R H and Zhu Z . 2014 . Landsat-8: science and product vision for terrestrial global change research . Remote Sensing of Environment , 145 : 154 - 172 [ DOI: 10.1016/j.rse.2014.02.001 http://dx.doi.org/10.1016/j.rse.2014.02.001 ]
Schroeder W , Oliva P , Giglio L and Csiszar I A . 2014 . The New VIIRS 375 m active fire detection data product: algorithm description and initial assessment . Remote Sensing of Environment , 143 : 85 - 96 [ DOI: 10.1016/j.rse.2013.12.008 http://dx.doi.org/10.1016/j.rse.2013.12.008 ]
Schroeder W , Oliva P , Giglio L , Quayle B , Lorenz E and Morelli F . 2016 . Active fire detection using Landsat-8/OLI data . Remote Sensing of Environment , 185 : 210 - 220 [ DOI: 10.1016/j.rse.2015.08.032 http://dx.doi.org/10.1016/j.rse.2015.08.032 ]
Schroeder W , Prins E , Giglio L , Csiszar I , Schmidt C , Morisette J and Morton D . 2008 . Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data . Remote Sensing of Environment , 112 ( 5 ): 2711 - 2726 [ DOI: 10.1016/j.rse.2008.01.005 http://dx.doi.org/10.1016/j.rse.2008.01.005 ]
Tan M Y , Chen Z X , Cao X , Chen J , Yang W and Gu Z H . 2007 . Study on the method of using Modis to identify grassland fire traces . Journal of Remote Sensing , 11 ( 03 ): 340 - 349
谭明艳 , 陈仲新 , 曹鑫 , 陈晋 , 杨伟 , 辜智慧 . 2007 . 利用MODIS识别草原火灾迹地方法的研究 . 遥感学报 , 11 ( 03 ): 340 - 349
Vuolo F , Żółtak M , Pipitone C , Zappa L , Wenng H , Immitzer M , Weiss M , Baret F and Atzberger C . 2016 . Data service platform for Sentinel-2 surface reflectance and value-added products: system use and examples . Remote Sensing , 8 ( 11 ): 938 [ DOI: 10.3390/rs8110938 http://dx.doi.org/10.3390/rs8110938 ]
Wulder M A and Coops N C , 2014 . Satellites: Make Earth observations open access . Nature , 513 , 30 – 31 [ DOI: 10.1038/513030a http://dx.doi.org/10.1038/513030a ]
Zheng Y L , Zhao Y D , Liu W P , Liu S B and Yao R T . 2018 . An intelligent wireless system for field ecology monitoring and forest fire warning . Sensors , 18 ( 12 ): 4457 [ DOI: 10.3390/s18124457 http://dx.doi.org/10.3390/s18124457 ]
Zhu Y J , Xing L X , Pan J , Meng T , Wen J C , Wang H H , Qiao Z M and Huang J C . 2011 . Research on recognition method of high temperature ground objects using short wave infrared remote sensing . Remote Sensing Information , 41 ( 06 ): 33 - 36
朱亚静 , 邢立新 , 潘军 , 孟涛 , 闻久成 , 王红红 , 乔振民 , 黄竞铖 . 2011 . 短波红外遥感高温地物目标识别方法研究 . 遥感信息 , 41 ( 06 ): 33 - 36
相关作者
相关机构
京公网安备11010802024621
