Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series

Abstract- The oceans and coastal areas are dynamic environments in which variability occurs at a wide range of temporal scales, from seconds to years to decades and longer. Some very good time series now exist at specific locations, that permit characterization of this variability as well as of long...

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Main Authors: G. A. Borstad, L. N. Brown, D. B. Fissel
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.7998
http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.158.7998 2023-05-15T15:15:36+02:00 Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series G. A. Borstad L. N. Brown D. B. Fissel The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.7998 http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.7998 http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf text ftciteseerx 2016-01-07T15:36:29Z Abstract- The oceans and coastal areas are dynamic environments in which variability occurs at a wide range of temporal scales, from seconds to years to decades and longer. Some very good time series now exist at specific locations, that permit characterization of this variability as well as of longer-term trends, but for much of the world ocean the in situ data is sparse and such characterization is not possible, or possible only by extrapolation. For these less well-studied areas, satellite imagery and gridded products created from a combination of satellite and in situ data are the only available sources of continuous historical information. Satellite imagery provides regular, spatially synoptic, global information, at spatial resolutions on the order of 1km and temporal resolutions typically measured in days. Some sensors offer higher spatial resolutions but at lower temporal resolution. With accumulated time series of up to 30 years or longer for some satellites and other gridded datasets, we can now begin to use this technology to identify and track long-term change, as well as to characterize shorter-term variability. In this paper we will discuss the analysis of long-term change and trends in marine and coastal environments using examples from recent projects. We will illustrate vegetation changes in and around the Anderson River delta on the Beaufort Sea coast of the Arctic Ocean using 30m spatial resolution Landsat imagery acquired over a 31-year period from 1972 to 2003. Using a temporal classification approach, we map both interannual variability and long-term losses on the mudflats of the delta itself, and gains on the nearby tundra. In a second example, we illustrate how chlorophyll and sea surface temperature (SST) vary locally within the northeast Pacific, and how temporal patterns and trends also vary regionally, using 24 years of weekly 4km resolution sea surface temperature from the Text Arctic Arctic Ocean Beaufort Sea Tundra Unknown Arctic Arctic Ocean Pacific
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description Abstract- The oceans and coastal areas are dynamic environments in which variability occurs at a wide range of temporal scales, from seconds to years to decades and longer. Some very good time series now exist at specific locations, that permit characterization of this variability as well as of longer-term trends, but for much of the world ocean the in situ data is sparse and such characterization is not possible, or possible only by extrapolation. For these less well-studied areas, satellite imagery and gridded products created from a combination of satellite and in situ data are the only available sources of continuous historical information. Satellite imagery provides regular, spatially synoptic, global information, at spatial resolutions on the order of 1km and temporal resolutions typically measured in days. Some sensors offer higher spatial resolutions but at lower temporal resolution. With accumulated time series of up to 30 years or longer for some satellites and other gridded datasets, we can now begin to use this technology to identify and track long-term change, as well as to characterize shorter-term variability. In this paper we will discuss the analysis of long-term change and trends in marine and coastal environments using examples from recent projects. We will illustrate vegetation changes in and around the Anderson River delta on the Beaufort Sea coast of the Arctic Ocean using 30m spatial resolution Landsat imagery acquired over a 31-year period from 1972 to 2003. Using a temporal classification approach, we map both interannual variability and long-term losses on the mudflats of the delta itself, and gains on the nearby tundra. In a second example, we illustrate how chlorophyll and sea surface temperature (SST) vary locally within the northeast Pacific, and how temporal patterns and trends also vary regionally, using 24 years of weekly 4km resolution sea surface temperature from the
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author G. A. Borstad
L. N. Brown
D. B. Fissel
spellingShingle G. A. Borstad
L. N. Brown
D. B. Fissel
Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
author_facet G. A. Borstad
L. N. Brown
D. B. Fissel
author_sort G. A. Borstad
title Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
title_short Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
title_full Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
title_fullStr Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
title_full_unstemmed Examining Change and Long-Term Trends in the Marine Environment Using Satellite-Based Time Series
title_sort examining change and long-term trends in the marine environment using satellite-based time series
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.7998
http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf
geographic Arctic
Arctic Ocean
Pacific
geographic_facet Arctic
Arctic Ocean
Pacific
genre Arctic
Arctic Ocean
Beaufort Sea
Tundra
genre_facet Arctic
Arctic Ocean
Beaufort Sea
Tundra
op_source http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.7998
http://www.aslenv.com/reports/RemoteSensing-Oceans2009.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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