Monitoring an Ecosystem in Crisis: Measuring Seagrass Meadow Loss Using Deep Learning in Mosquito Lagoon, Florida

被引:1
|
作者
Insalaco, Stephanie A. [1 ]
Herrero, Hannah V. [1 ]
Limber, Russ [2 ]
Oliver, Clancy [1 ]
Wolfson, William B. [3 ]
机构
[1] Univ Tennessee, Dept Geog & Sustainabil, Knoxville, TN 37916 USA
[2] Univ Tennessee, Bredesen Ctr, Knoxville, TN USA
[3] Grassroots Guide Serv, Rye, NY USA
来源
关键词
CLASSIFICATION;
D O I
10.14358/PERS.24-00001R2
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
The ecosystem of Mosquito Lagoon, Florida, has been rapidly deteriorating since the 2010s, with a notable decline in keystone seagrass species. Seagrass is vital for many species in the lagoon, but nutrient overloading, algal blooms, boating, manatee grazing, and other factors have led to its loss. To understand this decline, a deep neural network analyzed Landsat imagery from 2000 to 2020. Results showed significant seagrass loss post -2013, coinciding with the 2011-2013 super algal bloom. Seagrass abundance varied annually, with the model performing best in years with higher seagrass coverage. While the deep learning method successfully identified seagrass, it also revealed that recent seagrass coverage is almost non-existent. This monitoring approach could aid in ecosystem recovery if coupled with appropriate policies for Mosquito Lagoon's restoration.
引用
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页码:363 / 370
页数:64
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