Landscape modelling using integrated airborne multi-spectral and laser scanning data
Authors: Hill, R.A., Smith, G.M., Fuller, R.M. and Veitch, N.
Journal: International Journal of Remote Sensing
Volume: 23
Issue: 11
Pages: 2327-2334
ISSN: 0143-1161
DOI: 10.1080/01431160110119722
Abstract:By integrating multi-spectral and elevation data from airborne sensors (CASI and ALTM) and adopting a parcel-based approach, a progression is achieved from land-cover classification to landscape modelling. This work involved data integration, per-parcel classification, knowledge-based correction and the derivation of landscape objects. For a 1 km2 study area, a 14 land-cover class vector dataset was generated in which the parcels relate to landscape objects and contain information on their structure and 'terrain' context. At a 1 m spatial resolution, the correspondence between land-cover mapped using the airborne sensor data and identified by Countryside Survey 2000 field surveyors was 88%.
Source: Scopus
Landscape Modelling Using Integrated Airborne Multi-Spectral and Laser Scanning Data
Authors: Hill, R.A., Smith, G.M., Fuller, R.M. and Veitch, N.
Journal: International Journal of Remote Sensing
Volume: 23
Pages: 2327-2334
ISSN: 0143-1161
DOI: 10.1080/01431160110119722
Abstract:By integrating multi-spectral and elevation data from airborne sensors (CASI and ALTM) and adopting a parcel-based approach, a progression is achieved from land-cover classification to landscape modelling. This work involved data integration, per-parcel classification, knowledge-based correction and the derivation of landscape objects. For a 1 km[sup 2] study area, a 14 land-cover class vector dataset was generated in which the parcels relate to landscape objects and contain information on their structure and 'terrain' context. At a 1 m spatial resolution, the correspondence between land-cover mapped using the airborne sensor data and identified by Countryside Survey 2000 field surveyors was 88%.
http://dx.doi.org/10.1080/01431160110119722
Source: Manual
Preferred by: Ross Hill