[1] Mitsch W J, Gosselink J M. Wetlands. New York:Van Nostrand Reinhold Company Inc., 1986.
[2] 鍒樼孩鐜�,鏉庡厗瀵�. 涓夋睙骞冲師鍏稿瀷婀垮湴娴佸煙姘存枃鎯呭娍鍙樺寲杩囩▼鍙婂叾褰卞搷鍥犵礌鍒嗘瀽. 鑷劧璧勬簮瀛︽姤, 2005, 20(4):493~501.
[3] 鐜嬩紵, 闄嗗仴鍋�. 涓夊灍婀垮湴鐢熸�佺郴缁熸湇鍔″姛鑳藉強鍏朵环鍊�. 鐢熸�佸鎶�, 2005, 25(3):404~408.
[4] 鏉庡ぉ瀹�,璧垫櫤鏉�,闊╅箯. 娣卞湷娌虫渤鍙g孩鏍戞灄鍙樺寲鐨勫鏃剁浉閬ユ劅鍒嗘瀽. 閬ユ劅瀛︽姤,2002,6(5):364~370.
[5] Barbara J Kent, Joy Nystrom Mast. Wetland change analysis of San Dieguito Lagoon, California,USA:1928~1994. Wetlands, 2005,25(3):780~787.
[6] L L Bourgeau- chavez, E S Kasischke, S M Brunzell,et al. Analysis of space- borne SAR data for wetland mapping in Virginia riparian ecosystems.International Journal of Remote Sensing,2001, 22(18):3665~3687.
[7] Wataru Takeuchi, Masayuki Tamura, Yoshifumi Yasuoka. Estimation of methane emission from West Siberian wetland by scaling technique between NOAA AVHRR and SPOT HRV.Remote Sensing of Environment, 2003, 85( 1) : 21~29.
[8] Bounlom Vinliam, 鍗炲缓姘�, 鏋楀勾涓�. 3S 鎶�鏈湪闇嶆灄娌虫祦鍩熶笅娓告箍鍦版櫙瑙傛紨鍙樹腑鐨勫簲鐢�. 鍚夋灄澶у瀛︽姤(鍦扮悆绉戝鐗�), 2005, 35(2):221~225.
[9] R Chopra, V K Verma, P K Sharma. Mapping, monitoring and conservation of Harike wetland ecosystem,Punjab, India, through remote sensing.International Journal of Remote Sensing, 2001, 22(1):89~98.
[10] Jessika Tb#yr#, Alain Pietroniro. Towards operational monitoring of a northern wetland using geomatics- based techniques. Remote Sensing of Environment, 2005, 97(2):174~191.
[11] 鍒樼孩鐜�, 鍚曞鍥�, 寮犱笘濂�. 涓夋睙骞冲師娴佸煙婀垮湴鏅澶氭牱鎬у強鍏�50 骞村彉鍖栫爺绌�. 鐢熸�佸鎶�, 2004, 24(7):1472~1480.
[12] 鏉ㄦ案鍏�. 鍥介檯婀垮湴绉戝鐮旂┒杩涘睍鍜屼腑鍥芥箍鍦扮瀛︾爺绌朵紭鍏堥鍩熶笌灞曟湜. 鍦扮悆绉戝杩涘睍, 2002,17(4):508~514.
[13] Bronge L B, Naslund- Landenmark B. Wetland classification for Swedish CORINE Land Cover adopting a semi- automatic interactive approach.Canadian Journal of Remote Sensing,2002,28(2): 139~155.
[14] Rebecca L.Phillips,Ofer Beeri,Edward Shawn DeKeyser. Remote wetland assessment for Missouri coteau prairie glacial basins. Wetlands, 2005,25(2):335~349.
[15] 鍞愬皬骞�,榛勬鏋�. 涓浗婀垮湴鍒嗙被绯荤粺鐨勭爺绌�. 鏋椾笟绉戝鐮旂┒,2003,16(5):531~539.
[16] 鏉滅孩鑹�, 寮犳椽宀�, 寮犳绁�. GIS 鏀寔涓嬬殑婀垮湴閬ユ劅淇℃伅楂樼簿搴﹀垎绫绘柟娉曠爺绌�. 閬ユ劅鎶�鏈笌搴旂敤,2004,19(4):244~248.
[17] 琛d紵瀹�,鏉ㄦ煶,寮犳绁�. 鍩轰簬ETM+褰卞儚鐨勬墡榫欐箍鍦伴仴鎰熷垎绫荤爺绌�. 婀垮湴绉戝, 2004,2(3):208~212.
[18] Julie Noriega Rivera Rio, Diego Fabián Lozano~García. Spatial Filtering of Radar Data (RADARSAT)for Wetlands (Brackish Marshes) Classification. Remote Sensing of Environment,2000, 73( 2) : 143~151.
[19] K S Schmidt, A K Skidmore. Spectral discrimination of vegetation types in a coastal wetland. Remote Sensing of Environment, 2003, 85( 1) : 92~108.
[20] Brian L. Becker, David P. Lusch, Jiaguo Qi.Identifying optimal spectral bands from in situ measurements of Great Lakes coastal wetlands using second- derivative analysis. Remote Sensing of Environment, 2005, 97(2): 238~248.
[21] S P S Kushwaha, R S Dwivedi, B R M Rao. Evaluation of various digital image processing techniques for detection of coastal wetlands using ERS- 1 SAR data. International Journal of Remote Sensing, 2000, 21(3):565~579.
[22] 绔ュ簡绂�,閮戝叞鑺�,鐜嬫檵骞寸瓑. 婀垮湴妞嶈鎴愬儚鍏夎氨閬ユ劅鐮旂┒. 閬ユ劅瀛︽姤, 1997,1(1):50~57.
[23] 鏉滄槬鑻�,鐜嬭偛鍏�,楂樻案鍒氱瓑. 榛戦緳姹熺渷婀垮湴璧勬簮閬ユ劅淇℃伅瑙h瘧鍒嗘瀽. 榛戦緳姹熸皵璞�, 2003,3(1):1~3.
[24] 寮犱簯闇�,鏉庢檽鍏�,闄堜簯娴�. 鑽夊湴妞嶈鐩栧害鐨勫灏哄害閬ユ劅涓庡疄鍦版祴閲忔柟娉曠患杩�. 鍦扮悆绉戝杩涘睍, 2003, 18(1):85~93.
[25] 鐗涙槑棣�, 璧靛簹鏄�. 鍗楀洓婀栧尯婀垮湴淇℃伅閬ユ劅鎻愬彇鎶�鏈爺绌�. 鍥藉湡涓庤嚜鐒惰祫婧愮爺绌�, 2004,(1):51~53.
[26] T X YUE, B XU, J Y LIU. A patch connectivity index and its change in relation to new wetland at the Yellow River Delta. International Journal of Remote Sensing, 2004,25(21):4617~4628.
[27] 寮犲織閿�,璧垫枃鍚�,璐捐悕绛�. 鍖椾含婀垮湴鍒嗘瀽涓庣洃娴�. 鍦扮悆淇℃伅绉戝, 2004, 6(1):53~57.
[28] Miyamoto M, Yoshino K, Nagano T,et al. Use of balloon aerial photography for classification of Kushiro wetland vegetation, Northeastern Japan. Wetlands, 2004, 24(3):701~710.
[29] Dechka J A, Franklin S E, Watmough M D, et al. Classification of wetland habitat and vegetation communities using multi- temporal Ikonos imagery in southern Saskatchewan. Canadian Journal of Remote Sensing, 2002, 28(5):679~685.
[30] 寮犵繆娑�, 闄堟磱, 鐜嬫鼎鐢�. 缁撳悎鑷姩鍒嗗尯涓庡垎灞傚垎鏋愮殑澶氬厜璋遍仴鎰熷浘鍍忓湴鐗╁垎绫绘柟娉�. 閬ユ劅鎶�鏈笌搴旂敤, 2005, 209(3): 322~327.]
[31] Paula F. Houhoulis,William K. Michener. Detecting wetland change: a rule- based approach using NWI and SPOT- XS data. Photogrammetric Engineering and Remote Sensing, 2000, 66(2): 205~211.
[32] Munyati C. Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset. International Journal of Remote Sensing, 2000, 21(9): 1787~1806.
[33] 闄堟按妫�,浠樺皵鏋�. 閯遍槼婀栨箍鍦扮幆澧冨強鍏禡OS- 1 MESSR 閬ユ劅褰卞儚鍒嗘瀽. 鐢熸�佺瀛�,1998,17(2):118~120.
[34] 閭撳姴鏉�,鐜嬪澐,鏉庡悰绛�. 鍐崇瓥鏍戞柟娉曚粠SPOT- 5 鍗槦褰卞儚涓嚜鍔ㄦ彁鍙栨按浣撲俊鎭爺绌�. 娴欐睙澶у瀛︽姤(鍐滀笟涓庣敓鍛界瀛� 鐗�), 2005,31(2): 171~174.
[35] 鍒樺嚡,榛庡,鐜嬫爲鍔熺瓑. 鐝犳睙鍙h繎20 骞寸孩鏍戞灄婀垮湴鐨勯仴鎰熷姩鎬佺洃娴�. 鐑甫鍦扮悊,2005, 25(2):111~116.
[36] Li Deren. 鏉庡痉浠�.鏁板瓧鍦扮悆涓�“涓塖”鎶�鏈�. 涓浗娴嬬粯, 2003,(2):28~31.
[37] Neuenschwander,A.L.,M.M.Crawford,M.J.Provancha.Mapping of coastal wenlands via hyperspectral AVIRIS data. IEEE International Geoscience and Remote Sensing Symposium Proceedings,1998,189~191,USA.
[38] Foudan Salem, Menas Kafatos, Tarek EL- Ghazawi,et al. Hyperspectral image assessment of oil- contaminated wetland.International Journal of Remote Sensing, 2005, 26(4):811~821.
[39] Akira Hirano,Marguerite Madden,Roy Welch. Hyperspectral Image Data for Mapping Wetland Vegetation.Wetlands, 2003,23(2):436~448.
[40] T Schmid, M Koch, J Gumuzzio, et al. A spectral library for a semi- arid wetland and its application to studies of wetland degradation using hyperspectral and multispectral data. International Journal of Remote Sensing, 2004, 25(13):2485~2496.
[41] 寮犵孩, 鑸掑畞, 鍒樺垰. 澶氭椂鐩哥粍鍚堝垎绫绘硶鍦ㄥ湡鍦板埄鐢ㄥ姩鎬佺洃娴嬩腑鐨勫簲鐢�. 姝︽眽澶у瀛︽姤(淇℃伅绉戝鐗�), 2005, 30(2): 131~134.
[42] 寮犳爲娓�, 闄堟槬. 涓夋睙骞冲師婀垮湴閬ユ劅鍒嗙被妯″紡鐮旂┒. 閬ユ劅鎶�鏈笌搴旂敤, 1999, 14( 1) : 54~58.
[43] Lunetta R S,Balogh M E.Application of multi- temporal Landsat 5 TM imagery for wetland identification.Photogrammetric Engineering and Remote Sensing, 1999,65(11):1303~1310.
[44] Maria Gabriela Parmuchi, Haydee Karszenbaum, Patricia Kandus. Mapping wetlands using multi- temporal RADARSAT- 1 data and a decision- based classifier. Canadian Journal of Remote Sensing, 2002, 28(2):175~186.
[45] Ormsby J P, Blanchard B J. Detection of lowland flooding using active micro- wave systems.Photogrammetric Engineering and Remote Sensing, 1985, 51( 3) : 317~328.
[46] Philip A. Townsend. Estimating forest structure in wetlands using multitemporal SAR. Remote Sensing of Environment, 2002, 79( 2~3): 288~304.
[47] Augusteijn MF, Warrender CE. Wetland classification using optical and radar data and neural network classification.International Journal of Remote Sensing,1998,19(8): 1545~1560.
[48] R S Dwivedi, B R MRao. Mapping wetlands of the Sundaban Delta and it’s environs using ERS- 1 SAR data. International Journal of Remote Sensing, 1999,20(11):2235~2247.
[49] D A Roshier, R MRumbachs. Broad- scale mapping of temporary wetlands in arid Australia. Journal of Arid Environments, 2004, 56(2): 249~263.
[50] Haack B. Monitoring wetland changes with remote sensing: an East African example.Environmental Management, 1996, 20 ( 3) : 411~419.
[51] 闆嶅浗鐜�, 鐭虫壙鑻�, 閭遍箯椋�. 宸濊タ鍖楅珮鍘熻嫢灏旂洊鑽夊湴娌欏寲鍙婃箍鍦拌悗缂╁姩鎬侀仴鎰熺洃娴�. 灞卞湴瀛︽姤, 2003, 21( 6) : 758~762.
[52] Bridget Schulte- Hostedde, D Walters, C Powell, D Shrubsole. Wetland management: An analysis of past practice and recent policy changes in Ontario. Journal of Environmental Management, In Press,Available online 20 March 2006.
[53] 娌堟澗骞�,鐜嬪啗,娓镐附鍚涚瓑. 鑻ュ皵鐩栨布娉芥箍鍦伴仴鎰熷姩鎬佺洃娴�. 鍥涘窛鍦拌川瀛︽姤, 2005, 25(2):119~121.
[54] 楠嗗墤鎵�, 鐜嬮挦鏁�, 椹睙娲瓑. 閬ユ劅鍥惧儚鏈�澶т技鐒跺垎绫绘柟娉曠殑EM鏀硅繘绠楁硶. 娴嬬粯瀛︽姤, 2002, 31(3): 234~239.
[55] 鐜嬪渾鍦�, 鏉庝含. 閬ユ劅褰卞儚鍦熷湴鍒╃敤/瑕嗙洊鍒嗙被鏂规硶鐮旂┒缁艰堪. 閬ユ劅淇℃伅, 2004, ( 1) : 53~59.
[56] Peter M. Atkinson. Spatially weighted supervised classification for remote sensing. International Journal of Applied Earth Observation and Geoinformation, 2004,5( 4) : 277~291.
[57] Min Xu, Pakorn Watanachaturaporn, Pramod K. Varshney et al. Decision tree regression for soft classification of remote sensing data. Remote Sensing of Environment,97( 3): 2005: 322~336.
[58] 姹椊, 楠嗗墤鎵�, 鍛ㄦ垚铏庣瓑. 缁撳悎楂樻柉椹皵鍙か闅忔満鍦虹汗鐞嗘ā鍨嬩笌鏀拺鍚戦噺鏈哄湪楂樺垎杈ㄧ巼閬ユ劅鍥惧儚涓婃彁鍙栭亾璺綉. 閬� 鎰熷鎶�, 2005,9(3):271~276.
[59] 闊╂晱, 绋嬬, 鍞愭檽浜瓑. 鍚戞捣鑷劧淇濇姢鍖哄湡鍦拌鐩栧垎绫荤爺绌�. 搴旂敤鐢熸�佸鎶�, 2005, 16( 2) : 296~300.
[60] 闊╂晱, 瀛欑嚂妤犵瓑. 鍩轰簬RS銆丟IS 鎶�鏈殑鎵庨緳娌兼辰婀垮湴鏅鏍煎眬鍙樺寲鍒嗘瀽. 鍦扮悊绉戝杩涘睍, 2005, 24( 6) : 42~49.
[61] Steven A. Sader, Douglas Ahl, et al. Accuracy of landsat- TM and GIS rule- based methods for forest wetland classification in Maine.Remote Sensing of Environment, 1995,53(3):133~144.
[62] 楠嗗墤鎵�. 閬ユ劅褰卞儚鏅鸿兘鍥捐В鍙婂叾鍦板璁ょ煡闂鎺㈢储. 鍦扮悊绉戝杩涘睍, 2000, 19(4): 289~296.
[63] Vapnik V N. The Nature of Statistical Learning Theory. New York: Springer- Verlag,1995.
[64] G Fung O L. Mangasarian.Proximal support vector machine classifiers, D. Lee, et al. (Eds.),Proceedings of the KDD- 2001: Knowledge Discovery and Data Mining, New York:ACMpress,2001, 77~86.
[65] O L Mangasarian, D R Musicant. Lagrangian support vector machines. Journal of Machine Learning Research, 2001, (1): 161~177.
[66] O L Mangasarian, D R Musicant. Active support vector machine classification. Todd K. Leen, Thomas G. Dietterich, and Volker Tresp(Eds.), Advances in Neural Information Processing Systems 13, 2000, 577~583.
[67] Yuh- Jye Lee O L. Mangasarian.SSVM: A smooth support vector machine. Computational Optimization and Applications, 2001, 20(1): 5~22.
[68] C Huang L S. Davis J R G. Townshend. An assessment of support vector machine for land cover classification. International Journal of Remote Sensing, 2002,23(4):725~749.
|