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研究生:梁志綱
研究生(外文):Chih-Kang Liang
論文名稱:利用Spot4衛星的Vegetation資料比較NDVI,ARVI,及AFRI植被指數與氣溶膠厚度之關係
論文名稱(外文):Comparison of the NDVI, ARVI and AFRI vegetation index along with their relations with the AOD using SPOT 4 Vegetation data
指導教授:劉振榮劉振榮引用關係
指導教授(外文):Gin-Rong Liu
學位類別:碩士
校院名稱:國立中央大學
系所名稱:大氣物理研究所
學門:自然科學學門
學類:大氣科學學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:68
中文關鍵詞:植被指數衛星
外文關鍵詞:vegetationNDVIARVIAFRIAOD
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Abstract
As mankind’s technological advancements continue at a surprisingly fast rate, the computer models and tools that atmospheric scientists use to analyze and forecast our climate and weather have improved significantly. With the data collecting tools becoming increasingly sophisticated, the data obtained are becoming more and more accurate. In addition, more input data can now be fed into the models to obtain better simulations. One piece of input data that cannot be ignored is information regarding the land cover. The type and distribution of the land cover can seriously affect the climate and weather patterns of the Earth, such as regulating the amount of solar radiation that reenters the atmosphere. The land cover is usually measured through vegetation indexes such as the commonly used normalized difference vegetation index (NDVI). However, due to the fact that the NDVI index is susceptible to various outside influences---most notably the atmospheric disturbance, additional indexes have been developed to counter these effects. This paper explores two such indexes---- the Aerosol Free Vegetation Index (AFRI) and the Atmospherically Resistant Vegetation Index (ARVI). Comparisons were made with the NDVI index to see if they indeed performed better. The relationship of the different outcomes exhibited between the indexes with the aerosol optical depth or AOD was analyzed and exploited to see if this difference could be used in calculating the AOD. In addition, the percentage of the forest cover over Taiwan was calculated with the three vegetation indexes to study their variations. In general, the results showed that the AFRI and ARVI (using a gamma value of one) did indeed perform better than their NDVI counterpart. Unfortunately, the calculation of the AOD did not yield satisfactory results, which may require further study.
Table of Contents
Abstract……………………………………………………………………………….. i
Acknowledgements……………………………………………………………………ii
Table of Contents……………………………………………………………………..iii
Figure Captions……………………………...………………………………………..iv
1.Introduction………………………………………………………………………….1
2. Theoretical Basis
2-1. ARVI description………………………………………………………………3
2-2. AFRI description……………………………………………………………….4
3. Data…………………………………………………………………………………6
4. Methodology
4-1. Vegetation index Comparison………………………………………………….7
4-2. AOD analysis…………………………………………………………………10
4-3. Calculation of the AOD………………………………………………………13
4-4. Forest cover calculation over Taiwan………………………………………...15
5. Analysis and Conclusion…………………………………………………………..16
6. References…………………………………………………………………………20
7. Figures…………………………………………………………….…………...…..23
References曾忠一, 1988: 大氣衛星遙測學. 渤海堂出版社, 630pp.曾忠一, 1988: 大氣輻射. 聯經出版社, 360pp.羅煥奎, 1996: AVHRR資料估算台灣地區植被指數之幾何套合研究. 國立中央大學大氣物理研究所碩士論文, 75頁.劉振榮和林唐煌: 90年度「遙測技術研發計畫 」應用衛星資料建立台灣地區動態植被指數資料庫Ahrens, C. D., 1994: Meteorology Today An Introduction to Weather, Climate, and the Environment, 5th Ed. West Publishing Company, 591pp.Buschmann, C. and Nagel, E., 1993. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation. International Journal of Remote Sensing., 17, 845~862,Carlson, Toby N. and Ripley, David A., 1997: On the Relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index. Remote Sensing Environ., 62, 241~252.Fedosejevs, G., O’Neill, N.T., Royer, A., Teillet, P.M., Bokoye, A.I. and Mcarthur, B. Aerosol Optical Depth for Atmospheric Correction of AVHRR Composite Data. (printed from the Internet)Frank Morring, JR.,2002, Mar 4: Orbiting Gravity Mappers Might Spot Oil Fields. Aviation Week and Space Technology, 56~58French, A.N., Schmugge, T. J. and Kustas, W.P., 2000: Discrimination of Senescent Vegetation Using Thermal Emissivity Contrast. Remote Sensing Environ., 74, 249~254.Karnieli, A., Kaufman, Y. J., Remer, L. and Wald, A., 2001: AFRI---- Aerosol Free Vegetation Index. Remote Sensing Environ., 77, 10~21.Kaufman, Y. J. and Tanre, D., 1992: Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS. IEEEE Trans. Geosci. Remote Sensing., 30 (2), 261~270.Kaufman, Y. J., Wald, A. E., Remer, L. A., Gao, B. C., Li, R. R. and Flynn, L., 1997: The MODIS 2.1μm Channel---Correlation with Visible Reflectance for Use in Remote Sensing of Aerosol. IEEEE Trans. Geosci. Remote Sensing., 35 (2), 1286~1298.Kaufman, Y. J.and Remer, L., 1994: Detection of Forests Using Mid-IR Reflectance: An Application for Aerosol Studies. IEEEE Trans. Geosci. Remote Sensing., 32 (3), 672~683.Liu, G.R., Chen, A.J., Lin, T.H. and Kuo, T.H., 2002: Applying Spot data to estimate the aerosol optical depth and air quality. Environ Modelling ﹠Software., 17, 3-9.R.Borde, D. Ramon, C. Schmechtig and R.Santer,: Extension of the DDV concept to retrieve aerosol properties over land from the Modular Optoelectronic Scanner sensor. (awaiting publishing)Rees, Gareth, 1999 The Remote Sensing Data Book. Cambridge University Press, 262pp.Rouse, J.W., Haas, R.H., Schell, J.A. and Deering, D.W., 1973, Monitoring vegetation systems in the great plains with ERTS. Third ERTS Symposium, Goddard Space Flight Center, Washington, DC. NASA SP-351, 390~317.Tucker, C. J., Fung, I. Yi., Keeling, C. D. and Gammon, R. H., 16 January 1986: Relationship between atmospheric CO2 variations and a satellite-derived vegetation index. Nature., 319, 195~198.The Vegetation receiving station--- A direct link with Vegetation data─p.1~p.2Vane, G., Goetz., and Alexander. F. H., 1993: Terrestrial Imaging Spectrometry: Current Status, Future Trends. Remote Sensing Environ., 44, 117~226.Vegetation─Satellite imagery for studying the biosphere─p.4WebsitesEffects of scattering image (fig.1) http://dweb.ccrs.nrcan.gc.ca/ccrs/db/glossary/gloste.cfm?Language=English&GlosID=40 (from the glossary of the Canada Centre for Remote Sensing Spot 4 satellite image (fig.2)http://www.auslig.gov.au/acres/prod_ser/spotdata.htmOrbital diagram of Spot 4 image (fig.3)http://spot4.cnes.fr/spot4_gb/images/photos/spot450g.gifSwath of Vegetation image (fig.4) http://www.spotimage.fr/images/system/introsat/payload/vegetati/06.jpgVegetation sensor image (fig.5)http://spot4.cnes.fr/spot4_gb/vegetati.htmSeawifs image (fig.14) http://seawifs.gsfc.nasa.gov/cgibrs/level3.pl/S20012812001288.L3m_8D_CHLO.jpg?DAY=11603&PER=8&TYP=chl&IMG=bigColor bar image (fig.14)http://seawifs.gsfc.nasa.gov/SEAWIFS/IMAGES/chlor_colorbar.gifAeronet website: http://aeronet.gsfc.nasa.gov/
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