Over the past years, remote sensing imagery made the earth monitoring more effective and valuable through developing different algorithms for feature extraction. One of the significant features are water surfaces. Water features extraction such as pools, lakes and gulfs gained a considerable attention over the past years, as water plays critical role for surviving, planning and protecting water resources. Past worth efforts in water extraction from remote sensed images mainly faced the challenge of misclassification, especially with shadows. Shadows are typical noise objects for water, extraction, as they have almost identical spectrum characteristics, which result difficulty to discriminate between water and shadows in a remote sensing image, especially in the urban region such as Dubai.

Therefore, water extraction algorithm is developed in order to extract water surfaces accurately with shadows elimination. The detection is based on spectral information such as water indices (WIs), and morphological operations. Water indices are used to discriminate water surfaces from lands based on combining two or more water indices such as Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Saturation-value Difference Index (NSVDI), used at an optimum threshold. The morphological operators will be performed using opening by reconstruction to discriminate between water and shadows at an optimum threshold. Both Water Indices and morphological operation results will be infused together in one image that result a binary image of water objects.

The algorithm and final results are compared with ground truth image for accuracy assessment, the results were satisfactory with an accuracy of 95% and higher and very minimum negligible shadows appeared. Moreover the resultant image transformed into vector features in order to create a shape file that can be used and viewed in google earth and Geo software.

Date Published: 18 October 2016
PDF: 13 pages
Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 100041J (18 October 2016); doi: 10.1117/12.2241751

Published in SPIE Proceedings Vol. 10004:
Image and Signal Processing for Remote Sensing XXII
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)