Salt-marsh characterization, zonation assessment and mapping through a dual-wavelength LiDAR Antoine Collin a, ⁎, Bernard Long a , Phillippe Archambault b a Department of Geosciences, INRS-ETE, Université du Québec, Québec, Canada b Institut des Sciences de la Mer, Université du Québec à Rimouski, Rimouski, Canada abstract article info Article history: Received 6 March 2009 Received in revised form 14 October 2009 Accepted 16 October 2009 Keywords: LiDAR Remote sensing Habitat Salt-marsh Vegetation index Zonation Classification Linking intertidal processes to their natural patterns within a framework of coastal erosion requires monitoring techniques providing high-resolution spatio-temporal data from the scale of processes to this of patterns. The Scanning Hydrographic Operational Airborne LiDAR Survey (SHOALS) consists of a ubiquitous topographic and bathymetric LiDAR (Light Detection And Ranging) system that has become an important technology for generating high-resolution Digital Terrain Models (DTM) and Digital Surface Models (DSM) over intertidal landscapes. The objectives of this project are i) to highlight the capacity of SHOALS Topography and intensity data (Red and Near-InfraRed) to detect intertidal vegetation, ii) to assess the salt-marsh zonation, and iii) to map intertidal habitats and its adjacent coastal areas (Gulf of St. Lawrence, Canada). The study area was selected based on the spectrum of land cover types, encompassing beach, salt-marsh, arable farm and urban coastal environments. Surfaces constructed from the LiDAR survey included DSM, DTM, Normalized Surface Model (NSM), Digital Intensity Model for InfraRed (DIMI), Digital Intensity Model for Red (DIMR), and Normalized Difference LiDAR Vegetation Index Model (NDLVIM), derived from the two previous models. The correlation between the so-called NDLVI and the amount of salt-marsh vegetation, measured in situ, was 0.87 (p b 0.01). Then, LiDAR-assessed salt-marsh ecological zonation allowed finding out intermediate and strong relationships between NDLVI and Topography (r 2 = 0.89, p b 0.038) and Topographic heterogeneity (r 2 = 0.54, p b 0.1394), respectively. Finally, NDLVI and Topography surfaces were classified using maximum likelihood algorithm into 17 classes, whose overall accuracy and kappa coefficient were 91.89% and 0.9088, respectively. These results support that (1) intertidal vegetation can be discriminated by NDLVI, (2) salt-marsh ecological zonation pattern, and (3) accurate coastal land cover maps can be satisfactorily generated from a single LiDAR survey using the NDLVIM and DTM approach. © 2009 Elsevier Inc. All rights reserved. 1. Introduction Intertidal areas are ecoclines between terrestrial and salty or brackish water ecosystems that shelter a myriad of ecological niches, positively correlated with biodiversity, which provide considerable ecological services: disturbance regulation, waste treatment, refugia, food production and recreation (Costanza et al., 1997). Many decades of anthropogenic drying out and poldering turned these natural eco- systems into agrosystems and urban areas. Their spatial and temporal patterns are the consequence of the dynamical equilibrium between hydrological, geomorphic, sediment transport processes, hydrody- namic and biotic components (Bertness et al., 2001). Salt-marsh vegetation communities, i.e., halophytic plants (salt tolerant), play a fundamental role in the Topography (stricto sensu, i.e., the three- dimensional quality of the surface) and stability of coastal wetlands by means of a soil accretion, resulting from incoming flux of organic matter and sediment trapping (Cowles, 1911). Within a context of sea- level rising entailing high rates of erosion, chiefly due to growing power of waves, and artificial fixed shoreline, it is crucial to foster conserve, rebuild and manage intertidal habitats. On the other hand, inherent feedback’s mechanisms, i.e., hydrodynamics and Topography, force typical spatial patterns of vegetal settlement, i.e., zonation, according to the plant individual tolerance of salinity and water table levels. A transect crossing these patches allows to highlight an eco- logical zonation, from the pioneer species to the soil-required ones (Clements, 1936), which might be called a salt-marsh hydrosere. From mudflat colonized by low vegetation, i.e., glassworts (Salicornia spp.) and cordgrasses (Spartina spp.), to high-marsh settled by higher vegetation, e.g., poplars (Populus spp.), edaphic processes occur in complexifying soil structure, and increasing Topographic variability accordingly. Topographic heterogeneity, or rugosity, is an element of habitat complexity, and is a basic ecological factor on intertidal species diversity and richness (Archambault & Bourget, 1996; Morzaria-Luna et al., 2004; Larkin et al., 2008). Remote Sensing of Environment 114 (2010) 520–530 ⁎ Corresponding author. E-mail address: antoinecollin1@gmail.com (A. Collin). 0034-4257/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2009.10.011 Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse