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REMOTE SENSING FOR LAND & RESOURCES    2012, Vol. 24 Issue (3) : 65-70     DOI: 10.6046/gtzyyg.2012.03.13
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Application of the Temperature-Moisture Index to the Improvement of Remote Sensing Identification Accuracy of Mangrove
ZHANG Xue-hong1, TIAN Qing-jiu2
1. School of Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. International Institute for Earth System Science, Nanjing University, Nanjing 210093, China
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Abstract  The identification accuracy of mangrove by using TM reflective bands is always low due to the similarity of spectra between mangrove and land vegetation,especially water-vegetation mixed pixels. Based on reflective and thermal infrared information in the TM images of different tide levels,the authors proposed temperature-moisture index(TMI). The analytical results show that the thermal infrared band and TMI can obviously improve the separability between mangrove and other objects based on the tide level information. The thermal infrared band and TMI can also significantly increase the classification accuracy of mangrove by using spectral angle mapping (SAM) supervised classification method in comparison with the classification features employed by other researchers. The Kappa coefficient increases by 0.14, and the commission error of mangrove class decreases by 19.9%,suggesting that the remote sensing identification accuracy of mangrove can be improved by using the information of tide level,thermal infrared band and TMI.
Keywords 3S technology      mine hidden geological disaster      three-dimensional identificotion     
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TP751.1

 
  TP753

 
Issue Date: 20 August 2012
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DU Rui-ling
ZHAO Zhi-fang
HONG You-tang
NAN Jun-xiang
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DU Rui-ling,ZHAO Zhi-fang,HONG You-tang, et al. Application of the Temperature-Moisture Index to the Improvement of Remote Sensing Identification Accuracy of Mangrove[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(3): 65-70.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2012.03.13     OR     https://www.gtzyyg.com/EN/Y2012/V24/I3/65
[1] Blasco F,Saemger P,Janodet E.Mangroves as Indicators of Coastal Change [J].Catena,1996,27(3/4):167-178.
[2] Liu K,Li X,Shi X,et al.Monitoring Mangrove Forest Changes Using Remote Sensing and GIS Data with Decision-tree Learning [J].Wetlands,2008,28(2):336-346.
[3] Giri C,Pengra B,Zhu Z,et al.Monitoring Mangrove Forest Dynamics of the Sundarbans in Bangladesh and India Using Multi-temporal Satellite Data from 1973 to 2000 [J].Estuarine,Coastal and Shelf Science,2007,73(1/2):91-100.
[4] Chaudhury M U.Digital Analysis of Remote Sensing Data for Monitoring the Ecological Status of the Mangrove Forests of Sunderbans in Bangladesh [C]//Proceedings of the 23rd International Symposium on Remote Sensing of the Environment,1990,1:493-497.
[5] Aschbacher J,Ofren R S,Delsol J P,et al.An Integrated Comparative Approach to Mangrove Vegetation Mapping Using Advanced Remote Sensing and GIS Technologies:Preliminary Results[J].Hydrobiologia,1995,295(1/3):285-294.
[6] Green E P,Clear C D,Mum P J,et al.Remote Sensing Techniques for Mangrove Mapping [J].International Journal of Remote Sensing,1998,19(5):935-956.
[7] Andriamparany R,Francois F.Dynamics of Mangrove Forests in the Mangoky River Delta,Madagascar,Under the Influence of Natural and Human Factors [J].Forest Ecology and Management,2010,259(6):1161-1169.
[8] Blasco F,Aizpuru M,Gers C.Depletion of the Mangroves of Continental Asia [J].Wetlands Ecology and Management,2001,9(3):245-256.
[9] Thu P M,Pppulus J.Status and Changes of Mangrove Forest in Mekong Delta:Case Study in Tra Vinh,Vietanam[J].Estuarine Coastal and Shelf Science,2007,71(1/2):98-109.
[10] Conchedda G,Laurent D,Philippe M.An Object-based Method for Mapping and Change Analysis in Mangrove Ecosystems [J].ISPRS Journal of Photogrammetry and Remote Sensing,2008,63(5):578-589.
[11] Vaiphasa C,Andrew S K,Willem F B.A Post-classifier for Mangrove Mapping Using Ecological Data [J].ISPRS Journal of Photogrammetry and Remote Sensing,2006,61(1):1-10.
[12] 肖海燕,曾辉,昝启杰,等.基于高光谱数据和专家决策法提取红树林群落类型信息[J].遥感学报,2007,11(4):531-537. Xiao H Y,Zeng H,Zan Q J,et al.Decision Tree Model in Extraction of Mangrove Community Information Using Hyperspectral Image Data [J].Journal of Remote Sensing,2007,11(4):531-537(in Chinese with English Abstract).
[13] Wang L,Sousa W P,Gong P,et al.Comparison of IKONOS and QuickBird Images for Mapping Mangrove Species on the Caribbean Coast of Panama [J].Remote Sensing of Environment,2004,91(3/4): 432-40.
[14] Kovacsa J M,Wang J F,Flores-Verdugoc F.Mapping Mangrove Leaf Area Index at the Species Level Using IKONOS and LAI-2000 Sensors for the Agua Brava Lagoon Mexican Pacific[J].Estuarine,Coastal and Shelf Science,2005,62(1/2):377-384.
[15] Proisy,Coutero P,Fromard F.Predicting and Mapping Mangrove Biomass from Canopy Grain Analysis Using Fourier-based Textural Ordination of IKONOS Images [J].Remote Sensing of Environment,2007,109(3):379-392.
[16] Saleh A.Assessment of Mangrove Vegetation on Abu Minqar Island of the Red Sea [J].Journal of Arid Environments,2007,68(2):331-336.
[17] Jensen J R,Ramset E,Davis B A,et al.The Measurement of Mangrove Characteristics in South-west Florida Using SPOT Multispectral Data[J].Geocartography International,1991,6(2):13-21.
[18] Chander G,Markham B.Revised Landsat-5 TM Radiometric Calibration Procedures and Postcalibration Dynamic Ranges [J].IEEE Transactions on Geoscience and Remote Sensing,2003,41(11):2674-2677.
[19] Vetmote E F,Tanre D,Deuze J L,et al.Second Simulation of the Satellite Signal in the Solar Spectrum,6s:An Overview[J].IEEE Transactions on Geoscience and Remote Sensing,1997,35(3):675-686.
[20] Swain P H,Davis S M.Remote Sensing:The Quantitative Approach[M].New York:McGrowHill Inc,1978.
[21] 朱莱茵,许映军,崔维佳,等.渤海湾西部沿岸地区气温特征的观测研究[J].气象科学,2009,29(5):694-699. Zhu L Y,Xu Y J,Cu W J,et al.The Observation Research of Temperature Impacted by the Sea Land Breeze in the Coastal Area of Western Bohai Bay [J].Scientia Meteorologica Sinica,2009,29(5):694-699(in Chinese with English Abstract).
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