NDLI: Comparative evaluation of seasonal patterns in long time series of satellite image data and simulations of a global vegetation model

Content Provider	IEEE Xplore Digital Library
Author	McCloy, K.R. Lucht, W.
Copyright Year	1980
Abstract	A method has been developed and tested for comparing the complex spatio-temporal patterns present in two long time series of data of the seasonal cycles of vegetation for a large part of the global land surface. These two datasets are derived from global satellite observations (Advanced Very High Resolution Radiometer time series) and from a leading biogeochemical process model of global vegetation [Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM)], respectively. The datasets are completely independent of each other. The parameter compared is the fraction of photosynthetically active radiation. The comparison yields comparative parameters that quantify the differences between the two datasets. These comparative parameter images provide sufficient compression that they can be used for visual analysis so as to better understand the compatibility of, and the discrepancies between, the two datasets. The analysis shows that the LPJ model generally produces good correspondence with natural vegetation where the latter is primarily dependent upon climate. The correspondence was not as good where altitude, geomorphology, or hydrology of an area are the primary determinants of vegetation status. Due to a lack of representation of agriculture in the model, the correspondence with actual vegetative status was also poor where there is significant agricultural activity in an area.
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	140
Ending Page	153
Page Count	14
File Size	2695954
File Format	PDF
ISSN	01962892
Volume Number	42
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vegetation mapping Satellite broadcasting Testing Land surface Radiometry Image coding Image analysis Data analysis Hydrology Agriculture
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

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