Accuracy in Remotely Sensed Urban Greenery Land Cover

Junqi Zhou + and Jiabing Sun
School of Remote Sensing and Information, Wuhan University, Wuhan 430079, China

Abstract. The paper analyzed and compared the accuracy of urban greenery extraction from the different sensors images with different methods. It is necessary to compare the accuracy for the same area with different images, 30m TM image, 10m SPOT image and 2.44m QUICK BIRD image. Visual interpretation; classification based on the statistical and classification based on object are used to extract the urban Greenery from three kinds of sensors images with different resolution. Urban greenery extraction from high resolution image has higher accuracy using classification based on the object than that based on the statistical classified accuracy. The result shows that the sample and the statistical is the main factor to affect the accuracy by classification based on the statistical, while the segmentation scale is the main factor affect the accuracy by
classification based on object.

Keywords: remote sensor image, image classification, greenery extraction, accuracy comparison.

In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).

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