Detailed geological mapping in vegetated terrain using airborne multispectral imagery and LiDAR data: An example from the Troodos ophiolite, Cyprus

Practical and financial constraints associated with traditional field-based lithological mapping are often responsible for the generation of maps with insufficient detail and inaccurately located contacts. Remote sensing data, such as aerial photographs and multi- or hyperspectral imagery, offers solutions to many of the limitations associated with field-based surveys. For instance, remotely sensed data can provide more continuous and detailed information for large areas, thus enabling even the most inaccessible terrain to be mapped for only a fraction of the time and cost required for an equivalent field survey. In arid areas with well exposed rocks and soils, high-resolution multi- and hyperspectral imagery is a valuable mapping aid as lithological units can be readily discriminated and mapped by automatically matching image pixel spectra to a set of reference reflectance spectra. However, the use of spectral imagery in all but the most barren terrain is problematic because just small amounts of vegetation cover can obscure or mask the spectra of the underlying geological substrate. Nevertheless, indirect lithological discrimination may be possible if geobotanical relationships with the underlying substrates can be realised. Additionally, airborne Light Detection And Ranging (LiDAR) offers the potential to provide a novel solution to the vegetation problem because accurate and high-resolution topographic data can be acquired in either forested or non-forested terrain, allowing discrimination of individual rock types that typically have distinct topographic characteristics. This study assesses the efficacy of both airborne multispectral imagery and airborne LiDAR for detailed lithological mapping in a vegetated section of the Troodos ophiolite, Cyprus. Mapping algorithms are presented for the individual use of Airborne Thematic Mapper (ATM) imagery and airborne LiDAR data, in addition to their integrated use. The algorithms involve spectral/morphometric characterisation of the four main lithological units—the Basal Group lavas and dykes, pillow lavas, Lefkara Formation chalky marls and alluvium-colluvium—followed by image classification. Despite the problems posed by vegetation, geobotanical relationships and the correlation between lithology and topography were exploited individually to generate detailed lithological maps which define contacts much more accurately than the existing geological maps. Moreover, the mapping accuracy can be significantly enhanced through integration of the two datasets. The results of this study demonstrate the significant potential of airborne multispectral imagery and airborne LiDAR topographic data to aid rapid high-resolution lithological discrimination and the generation of detailed geological maps over large areas of vegetated or non-vegetated terrain.