The Impact of Lidar Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands

Abstract

While airborne lidar data have revolutionized the spatial resolution that elevations can be realized, data limitations are often magnified in coastal settings. Researchers have found that airborne lidar can have a vertical error as high as 60 cm in densely vegetated intertidal areas. The uncertainty of digital elevation models is often left unaddressed; however, in low-relief environments, such as barrier islands, centimeter differences in elevation can affect exposure to physically demanding abiotic conditions, which greatly influence ecosystem structure and function. In this study, we used airborne lidar elevation data, in situ elevation observations, lidar metadata, and tide gauge information to delineate low-lying lands and the intertidal wetlands on Dauphin Island, a barrier island along the coast of Alabama, USA. We compared three different elevation error treatments, which included leaving error untreated and treatments that used Monte Carlo simulations to incorporate elevation vertical uncertainty using general information from lidar metadata and site-specific Real-Time Kinematic Global Position System data, respectively. To aid researchers in instances where limited information is available for error propagation, we conducted a sensitivity test to assess the effect of minor changes to error and bias. Treatment of error with site-specific observations produced the fewest omission errors, although the treatment using the lidar metadata had the most well-balanced results. The percent coverage of intertidal wetlands was increased by up to 80% when treating the vertical error of the digital elevation models. Based on the results from the sensitivity analysis, it could be reasonable to use error and positive bias values from literature for similar environments, conditions, and lidar acquisition characteristics in the event that collection of site-specific data is not feasible and information in the lidar metadata is insufficient. The methodology presented in this study should increase efficiency and enhance results for habitat mapping and analyses in dynamic, low-relief coastal environments.

Coastal wetland adaptation to sea level rise: Quantifying potential for landward migration and coastal squeeze

“…Although coastal scientists have long recognized that landward migration corridors are an important strategy for maximizing the adaptive capacity of coastal wetlands in response to sea level rise (Scavia et al., ; Titus, , ; Williams, Pinzon, et al., ; Woodroffe et al., ), data limitations in many estuaries have hindered efforts to quantify the potential for landward migration and coastal squeeze. In the past decade, the quality and availability of relevant elevation, tidal datum, coastal wetland and land use data have been rapidly improving (Buffington et al., ; Enwright et al., ; Medeiros et al., ; Passeri et al., ). As a result, there has been a large increase in the number of studies that have quantified landward migration and/or coastal squeeze.…”

“…Prior studies have shown that the aerial topographic lidar data used to create DEMs can overpredict elevation by as much as 60 cm in coastal wetlands (Buffington, Dugger, Thorne, & Takekawa, ; Enwright et al., ; Medeiros, Hagen, Weishampel, & Angelo, ). Several techniques have been developed to deal with elevation uncertainty; for example simple lidar processing techniques like the minimum bin approach (Schmid, Hadley, & Wijekoon, ) or the incorporation of error estimates into probabilistic models (Enwright et al., ) to more advanced techniques that determine lidar corrections that are based upon relationships between lidar error and biomass (Buffington et al., ; Medeiros et al., ). These approaches offer exciting advancements and are leading to better elevation products that can be incorporated into wetland habitat change studies.…”

“…Gulf of Mexico hindered efforts to quantify the potential for landward migration and coastal squeeze. In the past decade, the quality and availability of relevant elevation, tidal datum, coastal wetland and land use data have been rapidly improving (Buffington et al, 2016;Enwright et al, 2018;Medeiros et al, 2015;Passeri et al, 2015). As a result, there has been a large increase in the number of studies that have quantified landward migration and/or coastal squeeze.…”

Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure

“…The result of such an operation is a map containing the spatial distribution of the probable errors, which can be used to indicate the likelihood, or probability, of any location falling above or below a specified elevation, thus this approach is called the "probabilistic" method. There is a long history of treating elevation error probabilistically (Hunter and Goodchild, 1995;Fisher, 1998;Zerger et al, 2002;Wechsler and Kroll, 2006), and the approach has been applied successfully in several recent SLR and flooding assessments Leon et al, 2014;Cooper et al, 2015;Enwright et al, 2017;Fereshtehpour and Karamouz, 2018). In using the probabilistic approach, random error fields that match the error distribution characteristics derived from DEM accuracy assessment are generated and applied spatially.…”

Introduction to the Special Issue “Uncertainty in Remote Sensing Image Analysis”

“…Uncertainty, in this case, could therefore be reduced by adapting the methodologies to the different conditions on the three continents. The sixth paper, "The Impact of LiDAR Elevation Uncertainty on Mapping Intertidal Habitats on Barrier Islands" by Nicholas M. Enwright, Lei Wang, Sinéad M. Borchert, Richard H. Day, Laura C. Feher and Michael J. Osland addresses limitations of LiDAR data in coastal settings, in particular addressing the uncertainty of digital elevation models [6]. The paper combines airborne LiDAR elevation data, in situ elevation observations, LiDAR metadata, and tide gauge information on a barrier island along the coast of Alabama, USA.…”