Using ICESat's Geoscience Laser Altimeter System (GLAS) to assess large-scale forest disturbance caused by hurricane Katrina
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作者:
Dolan, Katelyn A.
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Univ New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Dolan, Katelyn A.
[1
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Hurtt, George C.
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Univ New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Univ Maryland, Dept Geog, College Pk, MD 20742 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Hurtt, George C.
[1
,3
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Chambers, Jeffrey Q.
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Tulane Univ, Dept Ecol & Evolutionary Biol, New Orleans, LA 70118 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Chambers, Jeffrey Q.
[2
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Dubayah, Ralph O.
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Univ Maryland, Dept Geog, College Pk, MD 20742 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Dubayah, Ralph O.
[3
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Frolking, Steve
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Univ New Hampshire, Inst Study Earth Oceans & Space, Durham, NH 03824 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Frolking, Steve
[4
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Masek, Jeffrey G.
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NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USAUniv New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
Masek, Jeffrey G.
[5
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机构:
[1] Univ New Hampshire, Inst Study Earth Oceans, Durham, NH 03824 USA
[2] Tulane Univ, Dept Ecol & Evolutionary Biol, New Orleans, LA 70118 USA
[3] Univ Maryland, Dept Geog, College Pk, MD 20742 USA
[4] Univ New Hampshire, Inst Study Earth Oceans & Space, Durham, NH 03824 USA
[5] NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA
In 2005, hurricane Katrina resulted in a large disturbance to U.S. forests. Recent estimates of damage from hurricane Katrina have relied primarily on optical remote sensing and field data. This paper is the first large-scale study to use satellite-based lidar data to quantify changes in forest structure from that event. GLAS data for the years prior to and following hurricane Katrina were compared to wind speed, forest cover, and damage data to assess the adequacy of sensor sampling, and to estimate changes in Mean Canopy Height (MCH) over all areas that experienced tropical force winds and greater. Statistically significant decreases in MCH post-Katrina were found to increase with wind intensity: Tropical Storm Delta MCH = -0.5 m, Category 1 Delta MCH = -2 m, and Category 2 Delta MCH = -4 m. A strong relationship was also found between changes in non-photosynthetic vegetation (Delta NPV), a metric previously shown to be related to storm damage, and post-storm MCH. The season of data acquisition was shown to influence calculations of MCH and MCH loss, but did not preclude the detection of major large-scale patterns of damage. Results from this study show promise for using space-borne lidar for large-scale assessments of forest disturbance, and highlight the need for future data on vegetation structure from space. (C) 2010 Elsevier Inc. All rights reserved.
机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
Ni, Xiliang
Xu, Min
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
Xu, Min
Cao, Chunxiang
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
Cao, Chunxiang
Chen, Wei
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
Chen, Wei
Yang, Bin
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机构:
Baidu Inc, Big Data Lab, China Natl Engn Lab Deep Learning Technol & Appli, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
Yang, Bin
Xie, Bo
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
机构:
Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing Pr, Beijing 100875, Peoples R China
Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R ChinaBeijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Du, Bing
Yuan, Zhanliang
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机构:
Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R ChinaBeijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Yuan, Zhanliang
Bo, Yanchen
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机构:
Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing Pr, Beijing 100875, Peoples R ChinaBeijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Bo, Yanchen
Zhang, Yusha
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机构:
Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
Beijing Normal Univ, Inst Remote Sensing Sci & Engn, Fac Geog Sci, Beijing Engn Res Ctr Global Land Remote Sensing Pr, Beijing 100875, Peoples R ChinaBeijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China