Research Advance in Forest Informa tion Extractionfrom Hyoerspectral Remote Sensing Data

TAN Bing-xiang; LI Zeng-yuan; CHEN Er-xue; PANG Yong; WU Hong-gan

Volume 21 Issue Z1

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Research Advance in Forest Informa tion Extractionfrom Hyoerspectral Remote Sensing Data

1.
Research Institute of Forest Resource Information Techniques, CAF,Beijing　100091, China

Received Date: 2007-12-10

Abstract

With the development of remote sensing technology, especially the app lication of hyperspectral remotesensing data, more studies were focused on the investigation of forest information p roduction using hyperspectralremote sensing data. In this paper, it described the current state of forest biophysical and biochemical parametersderived from hyperspectral remote sensing data, such as forest species determining, canopy closure estimation andforest leave area index detection. This paper p resented the future trend of the application of hyperspectral remotesensing in forestry.
- hyperspectral remote sensing,
- forest information,
- forest inventory

References

[1]	GreggV, GoetzA F H. Terrestrial imaging spectrometry: current status, future trends[J]. Remote Sens Environ, 1993, 44: 117 - 126
[R]. Report p repared for the Ontario Forest ResearchInstitute, OntarioMinistry of Natural Resources, Sault Ste Marie,ON, 1997a
[3]	Monsch KA, Green R O, EastwoodM L, et al. Imaging spectroscopy and airborne visible / infrared imaging spectrometer(AV IR IS) [J].Remote Sens Environ, 1998, 65: 227 - 248
[R]. p resented at 2003 AV IR ISworkshop, Sheraton Hotel, Pasadena, USA, 2003 ( b)
[5]	浦瑞良,宫　鹏. 高光谱遥感及其应用[M]. 北京:高等教育出版社, 2000
[6]	Goodenough D G, Pearlman J, Hao Chen. Forest Information fromHyperspectral Sensing [C]. Proc IGARSSIV, Anchorage, Alaska,USA, 2004
[7]	MartinM E, Newman S D, Abet J D, et al. Determining forest species composition using high spectral resolution remote sensing data[J]. Remote Sens Environ, 1998, 65: 249 - 254
[8]	宫　鹏,浦瑞良,郁　彬. 不同季相针叶树种高光谱数据识别分析[J]. 遥感学报, 1998, 2 (3) : 211 - 217
[9]	Davison D, Achal S, Mah S, et al. Determination of tree species andtree stem densities in Northern Ontario forest usingAirborne CASI data[C]. Proc of Fourth InternationalAirborne Remote Sensing Conference and Exhibition, Ottario, Canada, 1999, 2: 187 - 196
[10]	Goodenough D G, Bhogal1 A S. Monitoring forests with Hyperionand AL I[C]. Proc IGARSS III, Tporonto, ON, Canada, 2002: 882- 885
[11]	Goodenough D G, Andrew D K, Niemann O. Processing Hyperionand AL I for forest classification [J]. IEEE Tran on Geoscience andRemote Sensing, 2003 ( a) , 41 (6) : 1321 - 1331
[12]	陈尔学,李增元,谭炳香,等. 高光谱数据森林类型统计模式识别方法比较评价[J]. 林业科学, 2007, 43 (1) : 84 - 89
[13]	Price J C. Estimating leaf area index from satellite data [J]. IEEETrans Geosci Remote Sensing, 1993, 31: 727 - 734
[14]	Gong P, ZhangA, Chen J, et al. Ecological land systems classification using multisource data and neural networks [C]. GIS’94,Vancouver B C Canada, February, 1994, 659 - 664
[15]	张培良,郑兰芬,童庆禧. 利用高光谱对生物变量进行估计[J].遥感学报, 1997, 1 (2) : 111 - 114
[16]	Gong P, Greg B, Pu R. Retrieval of surface reflectance and estimation of forest Leaf Area Index (LA I) Using Hyperion, AL I, andAV IR IS[EB /OL]. 2004
[17]	Pu Ruiliang, Peng Gong. Wavelet transform app lied to EO-1 hyperspectral data for forestLA I and crown closuremapp ing[J]. RemoteSensing of Environment, 2004, 91: 212 - 224
[18]	Lee K S, Park Y I, Kim S H. Remote sensing estimation of forestLA I in close canopy situation[C]. Proceedings of the XXth ISPRSCongress, Istanbul, Turkey, 2004: 400 - 404
[19]	谭炳香,李增元,陈尔学,等. Hyperion高光谱数据的森林郁闭度定量估测研究[J]. 北京林业大学学报( EI检索) , 2006, 28(3) : 95 - 101
[20]	Zagolski F, PinelV, Romier J, et al, Forest canopy chemistrywithhigh spectral resolution remote sensing[J]. International Journal ofRemote Sensing, 1996, 17 (6) : 1107 - 1128
[21]	Rock B N, Hoshizaki T, Miller J R. Comparison of in situ and airborne spectral measurements of the blue shift associated with forestdecline[J]. Remote Sens Environ, 1988, 24: 109 - 127
[22]	Carter G A, CibulaW G,Miller R L. Narrow-band reflectance imagery compared with thermal imagery for early detection of p lantstressl[J]. J Plant Physiol, 1996, 148: 515 - 522
[23]	Dendron Resource Surveys Inc. Bioindicators of forest health: Review report
[24]	Wessman C A, Aber J D , Peterson D L. An evaluation of imagingspectrometry for estimating forest canopy chemistry[J]. Int J Remote Sens, 1989, 10: 1293 - 1316
[25]	Johnson L F, Hlavaka C A, Peterson D L, et al. Multivariate analysis ofAV IR IS data for canopy biochemical estimation along the Oregon transect[J]. Remote Sen Environ, 1994, 47: 216 - 230
[26]	Matson P A, Johnson L, Billow C, et al. Seasonal changes in canopy chemistry across the Oregon transect: patterns and spectralmeasurementwith remote sensing[J]. EcolApp l, 1994, 4 (2) : 280- 298
[27]	浦瑞良,宫　鹏. 森林生物化学与CASI高光谱分辨率遥感数据的相关分析[J]. 遥感学报, 1997, 1 (2) : 115 - 123
[28]	Datt B. Visible /near infrared reflectance and chlorophyll content inEucalyputs leaves [J]. Int Remote Sensing, 1999, 20 ( 14) : 2741- 2759
[29]	Goodenough D G, Chen H, Dyk A, et al. Forest Information Products from AV IR IS and Hyperion
[30]	Jerred B. “Scientist Isolate Potassium Signal inWildfire”, NFPA,2000
[31]	Bachmann CM, Dubois K, Fusina R A. Automatic detection of aninvasive p lant species on a barrier island in the Virginia[C]. ProcIGARSS, Sydney, Australia, 2001
[32]	Lass L W, Thill D C, ShafiiB, et al. Detecting spotted knapweed(Centaurea m aculosa) with hyperspectral remote sensing Technology[J]. Weed Technology, 2002, 16: 426 - 432
[33]	Dennison P E, RobertsD A. Examining seasonal changes in canopymoisture using AV IR IS time series data [C]. Proc. 13 th AV IR ISEarth ScienceWorkshop, Pasadena, CA, 2004
[34]	姚延娟,阎广建,王锦地. 多角度遥感数据综合反演叶面积指数方法研究[J]. 遥感学报, 2005, 9 (2) : 117 - 122
[35]	Chen JM, Jane Liu, Leblance S G, et al. Multi2angular op tical remote sensing for assessing vegetation structure and carbon absorption[J]. Remote Sensing of Enviroment, 2003, 84 (4) : 516 - 525
[36]	Gobron Nadine, Bernard Pinty,MichelM. Uniquenes ofmultiangularmeasurements-Part II: Joint retrieval of vegetation structure andphotosynthetic activity from MISR [J]. IEEE Transaction on Geoscience and Remote Sensing, 2002, 40 (7) : 1574 - 1582
[37]	Zhang Y, Tian Y, Myneni R B, et al. Assessing the informationcontent ofmultiangle satellite data formapp ing biomass: I. Statistical analysis [J]. Remote Sensing of the Environment, 2002a , 80(3) : 418 - 434
[38]	Zhang Y, Shabanov N, Knyazikhin Y, et al. Assessing the information content ofmultiangle satellite data formapp ing biomass: II.Theory[J]. Remote Sensing of the Environment, 2002b, 80 ( 3) :435 - 446
[39]	David G G, Andrew D, Hao Chen. Evalution and validation ofCHR IS for national forests [C]. Proc of the 4^th CHR IS/PROBAWorkshop, ESA /ESR IN, Frascati, Italy, 19 - 21 Sep tember, 2006
[40]	Francois K, Pierre D. Forest type discrimination using multi-angleherperspectral data [C]. Proc of the 2^nd CHR IS/PROBA Workshop, ESA /ESR IN, Frascati, Italy, 28 - 30 Ap ril, 2004
[41]	DisneyM, Lewis P, Nich C. Angular variation and photochemicalresponse from CHR IS2PROBA over forest sites in the UK[C]. Procof the 4^th CHR IS/PROBA Workshop, ESA /ESR IN, Frascati, Italy, 19 - 21 Sep. , 2006
[42]	AEROSPACE REPORT (NO. TOR ～2001 ( 8511 ) ～1 ) : Hyperspectral ImageryMarket Forecast [EB /OL]. 2000—2005. http: / /www. losangeles. af. mil/ smc / xr /CPO

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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Proportional views

Research Advance in Forest Informa tion Extractionfrom Hyoerspectral Remote Sensing Data

1. Research Institute of Forest Resource Information Techniques, CAF,Beijing　100091, China

Received Date: 2007-12-10

Abstract: With the development of remote sensing technology, especially the app lication of hyperspectral remotesensing data, more studies were focused on the investigation of forest information p roduction using hyperspectralremote sensing data. In this paper, it described the current state of forest biophysical and biochemical parametersderived from hyperspectral remote sensing data, such as forest species determining, canopy closure estimation andforest leave area index detection. This paper p resented the future trend of the application of hyperspectral remotesensing in forestry.

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Reference (42)

[1]	GreggV, GoetzA F H. Terrestrial imaging spectrometry: current status, future trends[J]. Remote Sens Environ, 1993, 44: 117 - 126
[2]	[R]. Report p repared for the Ontario Forest ResearchInstitute, OntarioMinistry of Natural Resources, Sault Ste Marie,ON, 1997a
[3]	Monsch KA, Green R O, EastwoodM L, et al. Imaging spectroscopy and airborne visible / infrared imaging spectrometer(AV IR IS) [J].Remote Sens Environ, 1998, 65: 227 - 248
[4]	[R]. p resented at 2003 AV IR ISworkshop, Sheraton Hotel, Pasadena, USA, 2003 ( b)
[5]	浦瑞良,宫　鹏. 高光谱遥感及其应用[M]. 北京:高等教育出版社, 2000
[6]	Goodenough D G, Pearlman J, Hao Chen. Forest Information fromHyperspectral Sensing [C]. Proc IGARSSIV, Anchorage, Alaska,USA, 2004
[7]	MartinM E, Newman S D, Abet J D, et al. Determining forest species composition using high spectral resolution remote sensing data[J]. Remote Sens Environ, 1998, 65: 249 - 254
[8]	宫　鹏,浦瑞良,郁　彬. 不同季相针叶树种高光谱数据识别分析[J]. 遥感学报, 1998, 2 (3) : 211 - 217
[9]	Davison D, Achal S, Mah S, et al. Determination of tree species andtree stem densities in Northern Ontario forest usingAirborne CASI data[C]. Proc of Fourth InternationalAirborne Remote Sensing Conference and Exhibition, Ottario, Canada, 1999, 2: 187 - 196
[10]	Goodenough D G, Bhogal1 A S. Monitoring forests with Hyperionand AL I[C]. Proc IGARSS III, Tporonto, ON, Canada, 2002: 882- 885
[11]	Goodenough D G, Andrew D K, Niemann O. Processing Hyperionand AL I for forest classification [J]. IEEE Tran on Geoscience andRemote Sensing, 2003 ( a) , 41 (6) : 1321 - 1331
[12]	陈尔学,李增元,谭炳香,等. 高光谱数据森林类型统计模式识别方法比较评价[J]. 林业科学, 2007, 43 (1) : 84 - 89
[13]	Price J C. Estimating leaf area index from satellite data [J]. IEEETrans Geosci Remote Sensing, 1993, 31: 727 - 734
[14]	Gong P, ZhangA, Chen J, et al. Ecological land systems classification using multisource data and neural networks [C]. GIS’94,Vancouver B C Canada, February, 1994, 659 - 664
[15]	张培良,郑兰芬,童庆禧. 利用高光谱对生物变量进行估计[J].遥感学报, 1997, 1 (2) : 111 - 114
[16]	Gong P, Greg B, Pu R. Retrieval of surface reflectance and estimation of forest Leaf Area Index (LA I) Using Hyperion, AL I, andAV IR IS[EB /OL]. 2004
[17]	Pu Ruiliang, Peng Gong. Wavelet transform app lied to EO-1 hyperspectral data for forestLA I and crown closuremapp ing[J]. RemoteSensing of Environment, 2004, 91: 212 - 224
[18]	Lee K S, Park Y I, Kim S H. Remote sensing estimation of forestLA I in close canopy situation[C]. Proceedings of the XXth ISPRSCongress, Istanbul, Turkey, 2004: 400 - 404
[19]	谭炳香,李增元,陈尔学,等. Hyperion高光谱数据的森林郁闭度定量估测研究[J]. 北京林业大学学报( EI检索) , 2006, 28(3) : 95 - 101
[20]	Zagolski F, PinelV, Romier J, et al, Forest canopy chemistrywithhigh spectral resolution remote sensing[J]. International Journal ofRemote Sensing, 1996, 17 (6) : 1107 - 1128
[21]	Rock B N, Hoshizaki T, Miller J R. Comparison of in situ and airborne spectral measurements of the blue shift associated with forestdecline[J]. Remote Sens Environ, 1988, 24: 109 - 127
[22]	Carter G A, CibulaW G,Miller R L. Narrow-band reflectance imagery compared with thermal imagery for early detection of p lantstressl[J]. J Plant Physiol, 1996, 148: 515 - 522
[23]	Dendron Resource Surveys Inc. Bioindicators of forest health: Review report
[24]	Wessman C A, Aber J D , Peterson D L. An evaluation of imagingspectrometry for estimating forest canopy chemistry[J]. Int J Remote Sens, 1989, 10: 1293 - 1316
[25]	Johnson L F, Hlavaka C A, Peterson D L, et al. Multivariate analysis ofAV IR IS data for canopy biochemical estimation along the Oregon transect[J]. Remote Sen Environ, 1994, 47: 216 - 230
[26]	Matson P A, Johnson L, Billow C, et al. Seasonal changes in canopy chemistry across the Oregon transect: patterns and spectralmeasurementwith remote sensing[J]. EcolApp l, 1994, 4 (2) : 280- 298
[27]	浦瑞良,宫　鹏. 森林生物化学与CASI高光谱分辨率遥感数据的相关分析[J]. 遥感学报, 1997, 1 (2) : 115 - 123
[28]	Datt B. Visible /near infrared reflectance and chlorophyll content inEucalyputs leaves [J]. Int Remote Sensing, 1999, 20 ( 14) : 2741- 2759
[29]	Goodenough D G, Chen H, Dyk A, et al. Forest Information Products from AV IR IS and Hyperion
[30]	Jerred B. “Scientist Isolate Potassium Signal inWildfire”, NFPA,2000
[31]	Bachmann CM, Dubois K, Fusina R A. Automatic detection of aninvasive p lant species on a barrier island in the Virginia[C]. ProcIGARSS, Sydney, Australia, 2001
[32]	Lass L W, Thill D C, ShafiiB, et al. Detecting spotted knapweed(Centaurea m aculosa) with hyperspectral remote sensing Technology[J]. Weed Technology, 2002, 16: 426 - 432
[33]	Dennison P E, RobertsD A. Examining seasonal changes in canopymoisture using AV IR IS time series data [C]. Proc. 13 th AV IR ISEarth ScienceWorkshop, Pasadena, CA, 2004
[34]	姚延娟,阎广建,王锦地. 多角度遥感数据综合反演叶面积指数方法研究[J]. 遥感学报, 2005, 9 (2) : 117 - 122
[35]	Chen JM, Jane Liu, Leblance S G, et al. Multi2angular op tical remote sensing for assessing vegetation structure and carbon absorption[J]. Remote Sensing of Enviroment, 2003, 84 (4) : 516 - 525
[36]	Gobron Nadine, Bernard Pinty,MichelM. Uniquenes ofmultiangularmeasurements-Part II: Joint retrieval of vegetation structure andphotosynthetic activity from MISR [J]. IEEE Transaction on Geoscience and Remote Sensing, 2002, 40 (7) : 1574 - 1582
[37]	Zhang Y, Tian Y, Myneni R B, et al. Assessing the informationcontent ofmultiangle satellite data formapp ing biomass: I. Statistical analysis [J]. Remote Sensing of the Environment, 2002a , 80(3) : 418 - 434
[38]	Zhang Y, Shabanov N, Knyazikhin Y, et al. Assessing the information content ofmultiangle satellite data formapp ing biomass: II.Theory[J]. Remote Sensing of the Environment, 2002b, 80 ( 3) :435 - 446
[39]	David G G, Andrew D, Hao Chen. Evalution and validation ofCHR IS for national forests [C]. Proc of the 4^th CHR IS/PROBAWorkshop, ESA /ESR IN, Frascati, Italy, 19 - 21 Sep tember, 2006
[40]	Francois K, Pierre D. Forest type discrimination using multi-angleherperspectral data [C]. Proc of the 2^nd CHR IS/PROBA Workshop, ESA /ESR IN, Frascati, Italy, 28 - 30 Ap ril, 2004
[41]	DisneyM, Lewis P, Nich C. Angular variation and photochemicalresponse from CHR IS2PROBA over forest sites in the UK[C]. Procof the 4^th CHR IS/PROBA Workshop, ESA /ESR IN, Frascati, Italy, 19 - 21 Sep. , 2006
[42]	AEROSPACE REPORT (NO. TOR ～2001 ( 8511 ) ～1 ) : Hyperspectral ImageryMarket Forecast [EB /OL]. 2000—2005. http: / /www. losangeles. af. mil/ smc / xr /CPO

Research Advance in Forest Informa tion Extractionfrom Hyoerspectral Remote Sensing Data

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通讯作者: 陈斌, bchen63@163.com

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Research Advance in Forest Informa tion Extractionfrom Hyoerspectral Remote Sensing Data

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