Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic
1 broadside : ill. Understanding the plant community is vital in grasping the effects of climate change. Functional type, which divides vegetation into vascular plants, lichens, and mosses, aids in this understanding by representing a system of classification capable of predicting vegetation respons...
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ftkalamazoocoll:oai:cache.kzoo.edu:10920/4350 2023-06-11T04:09:03+02:00 Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic Anderson, Erika M. Gamon, John Houston, Stan Heummrich, K. Fred 2002-05-03 application/pdf http://hdl.handle.net/10920/4350 en_US eng Kalamazoo College http://hdl.handle.net/10920/4350 Vegetation surveys Botany -- Arctic regions Presentation 2002 ftkalamazoocoll 2023-04-24T12:49:27Z 1 broadside : ill. Understanding the plant community is vital in grasping the effects of climate change. Functional type, which divides vegetation into vascular plants, lichens, and mosses, aids in this understanding by representing a system of classification capable of predicting vegetation responses to, and on, ecological processes (Chapin et al., 1996). Traditional ecology offers a relatively simple strategy of using visual cover estimates to detect plant functional type, representing an effective yet subjective method. Remote sensing presents a more objective technique of vegetation analysis through the use of electromagnetic radiation (Gamon and Qiu, 1999). Just like traditional methods, hyperspectral remote sensing, which is on the scale of the landscape, differentiates between plant functional type (Gamon and Qui, 1999). This study compares the results of traditional and hyperspectral vegetation analysis to ensure that the hyperspectral method of remote sensing describes the plant community in a meaningful and helpful way. California State University University of Maryland, Baltimore County Kalamazoo College. Department of Biology. Diebold Symposium, 2002 Introduction -- Methods -- Results -- Conclusion -- Bibliography Conference Object Arctic Climate change Kalamazoo College: cache digital archive Arctic |
institution |
Open Polar |
collection |
Kalamazoo College: cache digital archive |
op_collection_id |
ftkalamazoocoll |
language |
English |
topic |
Vegetation surveys Botany -- Arctic regions |
spellingShingle |
Vegetation surveys Botany -- Arctic regions Anderson, Erika M. Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
topic_facet |
Vegetation surveys Botany -- Arctic regions |
description |
1 broadside : ill. Understanding the plant community is vital in grasping the effects of climate change. Functional type, which divides vegetation into vascular plants, lichens, and mosses, aids in this understanding by representing a system of classification capable of predicting vegetation responses to, and on, ecological processes (Chapin et al., 1996). Traditional ecology offers a relatively simple strategy of using visual cover estimates to detect plant functional type, representing an effective yet subjective method. Remote sensing presents a more objective technique of vegetation analysis through the use of electromagnetic radiation (Gamon and Qiu, 1999). Just like traditional methods, hyperspectral remote sensing, which is on the scale of the landscape, differentiates between plant functional type (Gamon and Qui, 1999). This study compares the results of traditional and hyperspectral vegetation analysis to ensure that the hyperspectral method of remote sensing describes the plant community in a meaningful and helpful way. California State University University of Maryland, Baltimore County Kalamazoo College. Department of Biology. Diebold Symposium, 2002 Introduction -- Methods -- Results -- Conclusion -- Bibliography |
author2 |
Gamon, John Houston, Stan Heummrich, K. Fred |
format |
Conference Object |
author |
Anderson, Erika M. |
author_facet |
Anderson, Erika M. |
author_sort |
Anderson, Erika M. |
title |
Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
title_short |
Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
title_full |
Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
title_fullStr |
Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
title_full_unstemmed |
Functionality of Hyperspectral Measurements in Vegetation Analysis: Comparison of Remote Sensing to Traditional Methods in the Alaskan Arctic |
title_sort |
functionality of hyperspectral measurements in vegetation analysis: comparison of remote sensing to traditional methods in the alaskan arctic |
publisher |
Kalamazoo College |
publishDate |
2002 |
url |
http://hdl.handle.net/10920/4350 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_relation |
http://hdl.handle.net/10920/4350 |
_version_ |
1768382742401122304 |