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Journal of Applied Remote Sensing

Comparison between WorldView-2 and SPOT-5 images in mapping the bracken fern using the random forest algorithm
Author(s): John O. Odindi; Elhadi E. Adam; Zinhle Ngubane; Onisimo Mutanga; Rob Slotow
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Paper Abstract

Plant species invasion is known to be a major threat to socioeconomic and ecological systems. Due to high cost and limited extents of urban green spaces, high mapping accuracy is necessary to optimize the management of such spaces. We compare the performance of the new-generation WorldView-2 (WV-2) and SPOT-5 images in mapping the bracken fern [<italic<Pteridium aquilinum (L) kuhn</italic<] in a conserved urban landscape. Using the random forest algorithm, grid-search approaches based on out-of-bag estimate error were used to determine the optimal <italic<ntree</italic< and <italic<mtry</italic< combinations. The variable importance and backward feature elimination techniques were further used to determine the influence of the image bands on mapping accuracy. Additionally, the value of the commonly used vegetation indices in enhancing the classification accuracy was tested on the better performing image data. Results show that the performance of the new WV-2 bands was better than that of the traditional bands. Overall classification accuracies of 84.72 and 72.22% were achieved for the WV-2 and SPOT images, respectively. Use of selected indices from the WV-2 bands increased the overall classification accuracy to 91.67%. The findings in this study show the suitability of the new generation in mapping the bracken fern within the often vulnerable urban natural vegetation cover types.

Paper Details

Date Published: 6 November 2014
PDF: 16 pages
J. Appl. Remote Sens. 8(1) 083527 doi: 10.1117/1.JRS.8.083527
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
John O. Odindi, Univ. of KwaZulu-Natal (South Africa)
Elhadi E. Adam, Univ. of KwaZulu-Natal (South Africa)
Univ. of Witwatersrand (South Africa)
Zinhle Ngubane, Univ. of KwaZulu-Natal (South Africa)
Onisimo Mutanga, Univ. of KwaZulu-Natal (South Africa)
Rob Slotow, Univ. of KwaZulu-Natal (South Africa)

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