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Assessing and monitoring semi-arid shrublands using object-based image analysis and multiple endmember spectral mixture analysis

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Abstract

Arid and semi-arid shrublands have significant biological and economical values and have been experiencing dramatic changes due to human activities. In California, California sage scrub (CSS) is one of the most endangered plant communities in the US and requires close monitoring in order to conserve this important biological resource. We investigate the utility of remote-sensing approaches—object-based image analysis applied to pansharpened QuickBird imagery (QBPS/OBIA) and multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery (SPOT/MESMA)—for estimating fractional cover of true shrub, subshrub, herb, and bare ground within CSS communities of southern California. We also explore the effectiveness of life-form cover maps for assessing CSS conditions. Overall and combined shrub cover (i.e., true shrub and subshrub) were estimated more accurately using QBPS/OBIA (mean absolute error or MAE, 8.9 %) than SPOT/MESMA (MAE, 11.4 %). Life-form cover from QBPS/OBIA at a 25 × 25 m grid cell size seems most desirable for assessing CSS because of its higher accuracy and spatial detail in cover estimates and amenability to extracting other vegetation information (e.g., size, shape, and density of shrub patches). Maps derived from SPOT/MESMA at a 50 × 50 m scale are effective for retrospective analysis of life-form cover change because their comparable accuracies to QBPS/OBIA and availability of SPOT archives data dating back to the mid-1980s. The framework in this study can be applied to other physiognomically comparable shrubland communities.

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Acknowledgments

Scanned color infrared and QuickBird images were acquired with funding from the National Aeronautical and Space Administration (NASA) Research, Education and Applications Solution Network (REASoN) project (cooperative agreement NCC13-03007). The 2005 SPOT 5 image was made available by the University of California, Santa Barbara Resource Center for SPOT Imagery. The research was partly supported by an Association of Environmental Professionals thorough Environmental Research Grant and San Diego State University. The authors thank Drs. Arthur Getis and Cort Willmott for helpful suggestions for statistical analysis for accuracy assessment; Keely Roth and Kris Kuzera for tremendous support for programming; Lloyd Coulter, Dave McKinsey, and Harry Johnson for technical support; and Daniel Hawtree for field work assistance.

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Authors and Affiliations

  1. Argonne National Laboratory, Argonne, IL, 60439, USA

    Yuki Hamada

  2. Department of Geography, San Diego State University, San Diego, CA, 92182-4493, USA

    Yuki Hamada & Douglas A. Stow

  3. Department of Geography, University of California, Santa Barbara, CA, 93106-4060, USA

    Dar A. Roberts & Phaedon C. Kyriakidis

  4. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, 85287, USA

    Janet Franklin

  5. Department of Geography, University of the Aegean, Mytilene, Greece

    Phaedon C. Kyriakidis

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  1. Yuki Hamada
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Correspondence to Yuki Hamada.

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Hamada, Y., Stow, D.A., Roberts, D.A. et al. Assessing and monitoring semi-arid shrublands using object-based image analysis and multiple endmember spectral mixture analysis. Environ Monit Assess 185, 3173–3190 (2013). https://doi.org/10.1007/s10661-012-2781-z

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