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Sea-level rise vulnerability mapping using LiDAR DEMs

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Date Issued:
2014
Summary:
Global sea-level rise SLR is projected to accelerate over the next century, with research indicating that global mean sea level may rise 18–48 cm by 2050, and 50–140 cm by 2100. Decision-makers, faced with the problem of adapting to SLR, utilize elevation data to identify assets that are vulnerable to inundation. This paper reviews techniques and challenges stemming from the use of Light Detection and Ranging LiDAR Digital Elevation Models DEMs in support of SLR decision-making. A significant shortcoming in the methodology is the lack of comprehensive standards for estimating LiDAR error, which causes inconsistent and sometimes misleading calculations of uncertainty. Workers typically aim to reduce uncertainty by analyzing the difference between LiDAR error and the target SLR chosen for decision-making. The practice of mapping vulnerability to SLR is based on the assumption that LiDAR errors follow a normal distribution with zero bias, which is intermittently violated. Approaches to correcting discrepancies between vertical reference systems for land and tidal datums may incorporate tidal benchmarks and a vertical datum transformation tool provided by the National Ocean Service VDatum. Mapping a minimum statistically significant SLR increment of 32 cm is difficult to achieve based on current LiDAR and VDatum errors. LiDAR DEMs derived from ‘ground’ returns are essential, yet LiDAR providers may fail to remove returns over vegetated areas successfully. LiDAR DEMs integrated into a GIS can be used to identify areas that are vulnerable to direct marine inundation and groundwater inundation reduced drainage coupled with higher water tables. Spatial analysis can identify potentially vulnerable ecosystems as well as developed assets. A standardized mapping uncertainty needs to be developed given that SLR vulnerability mapping requires absolute precision for use as a decision-making tool.
Title: Sea-level rise vulnerability mapping using LiDAR DEMs.
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Name(s): Cooper, Hannah M.
Fletcher, Chip
Chen, Qi
Graduate College
Barbee, Matthew
Zhang, Caiyun
Type of Resource: text
Genre: Abstract
Date Created: 2014
Date Issued: 2014
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 1 p.
Language(s): English
Summary: Global sea-level rise SLR is projected to accelerate over the next century, with research indicating that global mean sea level may rise 18–48 cm by 2050, and 50–140 cm by 2100. Decision-makers, faced with the problem of adapting to SLR, utilize elevation data to identify assets that are vulnerable to inundation. This paper reviews techniques and challenges stemming from the use of Light Detection and Ranging LiDAR Digital Elevation Models DEMs in support of SLR decision-making. A significant shortcoming in the methodology is the lack of comprehensive standards for estimating LiDAR error, which causes inconsistent and sometimes misleading calculations of uncertainty. Workers typically aim to reduce uncertainty by analyzing the difference between LiDAR error and the target SLR chosen for decision-making. The practice of mapping vulnerability to SLR is based on the assumption that LiDAR errors follow a normal distribution with zero bias, which is intermittently violated. Approaches to correcting discrepancies between vertical reference systems for land and tidal datums may incorporate tidal benchmarks and a vertical datum transformation tool provided by the National Ocean Service VDatum. Mapping a minimum statistically significant SLR increment of 32 cm is difficult to achieve based on current LiDAR and VDatum errors. LiDAR DEMs derived from ‘ground’ returns are essential, yet LiDAR providers may fail to remove returns over vegetated areas successfully. LiDAR DEMs integrated into a GIS can be used to identify areas that are vulnerable to direct marine inundation and groundwater inundation reduced drainage coupled with higher water tables. Spatial analysis can identify potentially vulnerable ecosystems as well as developed assets. A standardized mapping uncertainty needs to be developed given that SLR vulnerability mapping requires absolute precision for use as a decision-making tool.
Identifier: FA00005809 (IID)
Collection: FAU Student Research Digital Collection
Note(s): The Fifth Annual Graduate Research Day was organized by Florida Atlantic University’s Graduate Student Association. Graduate students from FAU Colleges present abstracts of original research and posters in a competition for monetary prizes, awards, and recognition
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00005809
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.