植被指數

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.

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Websites
Effects 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.htm
Orbital diagram of Spot 4 image (fig.3)
http://spot4.cnes.fr/spot4_gb/images/photos/spot450g.gif
Swath of Vegetation image (fig.4) http://www.spotimage.fr/images/system/introsat/payload/vegetati/06.jpg
Vegetation sensor image (fig.5)
http://spot4.cnes.fr/spot4_gb/vegetati.htm
Seawifs image (fig.14) http://seawifs.gsfc.nasa.gov/cgibrs/level3.pl/S20012812001288.L3m_8D_CHLO.jpg?DAY=11603&PER=8&TYP=chl&IMG=big
Color bar image (fig.14)
http://seawifs.gsfc.nasa.gov/SEAWIFS/IMAGES/chlor_colorbar.gif
Aeronet website:
http://aeronet.gsfc.nasa.gov/