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    Quantifying the carbon storage, distribution, and change of urban trees is vital to understanding the role of vegetation in the urban environment. At present, this is mostly achieved through ground study. This paper presents a method based on the satellite image time series, which can save time and money and greatly speed the process of urban forest carbon storage mapping, and possibly of regional forest mapping. Satellite imagery collected in different decades was used to develop a regression equation to predict the urban forest carbon storage from the Normalized Difference Vegetation Index (NDVI) computed from a time sequence (1985-1999) of Landsat image data. This regression was developed from the 1999 field-based model estimates of carbon storage in Syracuse, NY.

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    Myeong, Soojeong; Nowak, David J.; Duggin, Michael J. 2006. A temporal analysis of urban forest carbon storage using remote sensing. Remote Sensing of Environment. 101: 277-282.


    carbon storage, urban forest, urban environment, NDVI

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