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Full-Text Articles in Life Sciences
Sea Level Rise Vulnerability Analysis Of Mangrove Ecosystems Using Gis, Kayla Caldwell
Sea Level Rise Vulnerability Analysis Of Mangrove Ecosystems Using Gis, Kayla Caldwell
HCNSO Student Theses and Dissertations
Climate change is accelerating beyond what is natural due to excessive emissions from human activities. The sea level has been rising for many years and is currently at a rate of 3.6 mm/yr. Mangroves are known to only keep pace with a sea level rate of less than 1.2 mm/yr. Mangroves are particularly vulnerable to rising sea levels if they are not able to keep pace through vertical sediment accretion or inland migration. To test the vulnerability of the south Florida mangrove ecosystems to sea level rise, this study analyzed changes in the mangrove forest coverage of the Oleta River …
Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin
Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin
Mathematics, Physics, and Computer Science Faculty Articles and Research
Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent …