Urban land cover classification from high resolution Geoeye-1 imagery using a lidarbased digital surface model

[摘要] ENGLISH ABSTRACT: Urban planning and management require up-to-date information about urban land cover. Producing such geospatial information is time consuming as it is usually done manually. The classification of such information from satellite imagery is challenging owing to the difficulties associated with distinguishing urban features having similar spectral properties. Therefore, this study evaluates the combination of a digital surface model (DSM) derived from LiDAR data and very high-resolution GeoEye-1 satellite imagery for classifying urban land cover in Cape Town. The value of the DSM was assessed by comparing a land cover product obtained from the GeoEye-1 image to a map produced using both the GeoEye-1 image and the DSM. A systematic segmentation procedure for the two classifications scenarios preceded a supervised (using a support vector machine, K nearest neighbour and classification and regression algorithm tree classifiers) and rule-based classification. The various approaches were evaluated using a combination of methods.When including the DSM in the supervised and rule-based classifications, the overall accuracy and kappa vary between 80% to 83% and 0.74 to 0.77 respectively. When the DSM is excluded, the overall accuracy ranges between 49 to 64% whereas kappa ranges between 0.32 to 0.53 for the two classification approaches. The accuracies obtained are always about 20% higher when the DSM is included. The normalised DSM (nDSM) enabled accurate discrimination of elevated (e.g. buildings) and non-elevated (e.g. paved surfaces) urban features having similar spectral characteristics. The nDSM of at least one-metre resolution and one metre vertical accuracy influenced the accuracy of the results by correctly differentiating elevated from non-elevated.The rule-based approach was more effective than the supervised classification, particularly for extracting water bodies (dams and swimming pools) and bridges. Consequently, a rule-based approach using very high spatial resolution (EHSR) satellite imagery and a LiDAR-derived DSM is recommended for mapping urban land cover.

[发布机构] Stellenbosch University