Remote Sensing Applications and Decision Support

Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery

[+] Author Affiliations
Saad A. Alsharrah, David A. Bruce, Sekhar Somenahalli, Paul A. Corcoran

University of South Australia, School of Natural and Built Environments Research Centre, GPO Box 2471, Adelaide, Australia

Rachid Bouabid

Ecole Nationale d’Agriculture de Meknes, Km 10, Rte Haj Kaddour, BP S-40 Meknès 50000, Morocco

J. Appl. Remote Sens. 10(3), 036008 (Jul 22, 2016). doi:10.1117/1.JRS.10.036008
History: Received December 23, 2015; Accepted July 7, 2016
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Abstract.  Satellite remote-sensing techniques face challenges in extracting vegetation-cover information in desert environments. The limitations in detection are attributed to three major factors: (1) soil background effect, (2) distribution and structure of perennial desert vegetation, and (3) tradeoff between spatial and spectral resolutions of the satellite sensor. In this study, a modified vegetation shadow model (VSM-2) is proposed, which utilizes vegetation shadow as a contextual classifier to counter the limiting factors. Pleiades high spatial resolution, multispectral (2 m), and panchromatic (0.5 m) images were utilized to map small and scattered perennial arid shrubs and trees. We investigated the VSM-2 method in addition to conventional techniques, such as vegetation indices and prebuilt object-based image analysis. The success of each approach was evaluated using a root sum square error metric, which incorporated field data as control and three error metrics related to commission, omission, and percent cover. Results of the VSM-2 revealed significant improvements in perennial vegetation cover and distribution accuracy compared with the other techniques and its predecessor VSM-1. Findings demonstrated that the VSM-2 approach, using high-spatial resolution imagery, can be employed to provide a more accurate representation of perennial arid vegetation and, consequently, should be considered in assessments of desertification.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Saad A. Alsharrah ; Rachid Bouabid ; David A. Bruce ; Sekhar Somenahalli and Paul A. Corcoran
"Use of shadow for enhancing mapping of perennial desert plants from high-spatial resolution multispectral and panchromatic satellite imagery", J. Appl. Remote Sens. 10(3), 036008 (Jul 22, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.036008


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