Time Series Analysis of Environmental Ecosystems: case of Morocco
Evidence from NOAA AVHRR Satellite Data
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The NOAA AVHRR is considered to be one of the largest image archives ever gathered in the history of remote sensing. Although designed to support meteorological applications, The NOAA AVHRR s ability to produce an index of relatively green vegetation biomass, coupled with its ability to virtually produce cloud-free monthly composites has now yielded an extraordinary time series more than 20 years in length. This book looks at the potential of the archive as a tool for understanding environmental dynamics in arid and semi-arid regions.The principal tool used in this investigation was a Principa...
The NOAA AVHRR is considered to be one of the
largest image archives ever gathered in the history
of remote sensing. Although designed to support
meteorological applications, The NOAA AVHRR s
ability to produce an index of relatively green
vegetation biomass, coupled with its ability to
virtually produce cloud-free monthly composites has
now yielded an extraordinary time series more than
20 years in length. This book looks at the potential
of the archive as a tool for understanding
environmental dynamics in arid and semi-arid regions.
The principal tool used in this investigation was a
Principal Components-based time series analysis
(TSA). Using a set of 240 monthly composite multi-
band AVHRR images for Morocco, a 20-year time series
of monthly NDVI images was analyzed
This analysis should help shed some light on this
new approach and should be essentially useful to
professionals in remote sensing, or to anyone who
may be considering utilizing NOAA AVHRR data for
environmental dynamics analysis.
largest image archives ever gathered in the history
of remote sensing. Although designed to support
meteorological applications, The NOAA AVHRR s
ability to produce an index of relatively green
vegetation biomass, coupled with its ability to
virtually produce cloud-free monthly composites has
now yielded an extraordinary time series more than
20 years in length. This book looks at the potential
of the archive as a tool for understanding
environmental dynamics in arid and semi-arid regions.
The principal tool used in this investigation was a
Principal Components-based time series analysis
(TSA). Using a set of 240 monthly composite multi-
band AVHRR images for Morocco, a 20-year time series
of monthly NDVI images was analyzed
This analysis should help shed some light on this
new approach and should be essentially useful to
professionals in remote sensing, or to anyone who
may be considering utilizing NOAA AVHRR data for
environmental dynamics analysis.
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