Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain
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. In arid areas with well exposed rocks and soils, high-resolution multi- and hyperspectral imag...
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| Format: | Article |
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Elsevier
2011
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| Online Access: | https://eprints.nottingham.ac.uk/33861/ |
| _version_ | 1848794721759002624 |
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| author | Grebby, Stephen Naden, Jonathan Cunningham, Dickson Tansey, Kevin |
| author_facet | Grebby, Stephen Naden, Jonathan Cunningham, Dickson Tansey, Kevin |
| author_sort | Grebby, Stephen |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. 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 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 underlying geological substrates. The use of ancillary information may help to improve lithological discrimination, especially where geobotanical relationships are absent or where distinct lithologies exhibit inherent spectral similarity. This study assesses the efficacy of airborne multispectral imagery for detailed lithological mapping in a vegetated section of the Troodos ophiolite (Cyprus), and investigates whether the mapping performance can be enhanced through the integration of LiDAR-derived topographic data. In each case, a number of algorithms involving different combinations of input variables and classification routine were employed to maximise the mapping performance. Despite the potential problems posed by vegetation cover, geobotanical associations aided the generation of a lithological map – with a satisfactory overall accuracy of 65.5% and Kappa of 0.54 – using only spectral information. Moreover, owing to the correlation between topography and lithology in the study area, the integration of LiDAR-derived topographic variables led to significant improvements of up to 22.5% in the overall mapping accuracy compared to spectral-only approaches. The improvements were found to be considerably greater for algorithms involving classification with an artificial neural network (the Kohonen Self-Organizing Map) than the parametric Maximum Likelihood Classifier. The results of this study demonstrate the enhanced capability of data integration for detailed lithological mapping in areas where spectral discrimination is complicated by the presence of vegetation or inherent spectral similarities. |
| first_indexed | 2025-11-14T19:20:42Z |
| format | Article |
| id | nottingham-33861 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:20:42Z |
| publishDate | 2011 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-338612020-05-04T16:30:16Z https://eprints.nottingham.ac.uk/33861/ Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain Grebby, Stephen Naden, Jonathan Cunningham, Dickson Tansey, Kevin 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. 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 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 underlying geological substrates. The use of ancillary information may help to improve lithological discrimination, especially where geobotanical relationships are absent or where distinct lithologies exhibit inherent spectral similarity. This study assesses the efficacy of airborne multispectral imagery for detailed lithological mapping in a vegetated section of the Troodos ophiolite (Cyprus), and investigates whether the mapping performance can be enhanced through the integration of LiDAR-derived topographic data. In each case, a number of algorithms involving different combinations of input variables and classification routine were employed to maximise the mapping performance. Despite the potential problems posed by vegetation cover, geobotanical associations aided the generation of a lithological map – with a satisfactory overall accuracy of 65.5% and Kappa of 0.54 – using only spectral information. Moreover, owing to the correlation between topography and lithology in the study area, the integration of LiDAR-derived topographic variables led to significant improvements of up to 22.5% in the overall mapping accuracy compared to spectral-only approaches. The improvements were found to be considerably greater for algorithms involving classification with an artificial neural network (the Kohonen Self-Organizing Map) than the parametric Maximum Likelihood Classifier. The results of this study demonstrate the enhanced capability of data integration for detailed lithological mapping in areas where spectral discrimination is complicated by the presence of vegetation or inherent spectral similarities. Elsevier 2011-01-17 Article PeerReviewed Grebby, Stephen, Naden, Jonathan, Cunningham, Dickson and Tansey, Kevin (2011) Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain. Remote Sensing of Environment, 115 (1). pp. 214-226. ISSN 0034-4257 Lithological mapping Multispectral imagery Airborne LiDAR Troodos ophiolite Self-organizing map Data integration http://www.sciencedirect.com/science/article/pii/S0034425710002592 doi:10.1016/j.rse.2010.08.019 doi:10.1016/j.rse.2010.08.019 |
| spellingShingle | Lithological mapping Multispectral imagery Airborne LiDAR Troodos ophiolite Self-organizing map Data integration Grebby, Stephen Naden, Jonathan Cunningham, Dickson Tansey, Kevin Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title | Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title_full | Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title_fullStr | Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title_full_unstemmed | Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title_short | Integrating airborne multispectral imagery and airborne LiDAR data for enhanced lithological mapping in vegetated terrain |
| title_sort | integrating airborne multispectral imagery and airborne lidar data for enhanced lithological mapping in vegetated terrain |
| topic | Lithological mapping Multispectral imagery Airborne LiDAR Troodos ophiolite Self-organizing map Data integration |
| url | https://eprints.nottingham.ac.uk/33861/ https://eprints.nottingham.ac.uk/33861/ https://eprints.nottingham.ac.uk/33861/ |