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Remote Sensing
Volume 9
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Erratum to Remote Sens. 2017, 9(6), 546.
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Erratum

Erratum: Chance, E.W., et al. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546

by
Eric W. Chance
1,*,
Kelly M. Cobourn
1,
Valerie A. Thomas
1,
Blaine C. Dawson
2 and
Alejandro N. Flores
2
1
Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute and State University, 310 West Campus Drive, Blacksburg, VA 24061-0324, USA
2
Department of Geosciences, Boise State University, 1910 University Drive, Boise, ID 83725-1535, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(7), 738; https://doi.org/10.3390/rs9070738
Submission received: 7 July 2017 / Revised: 7 July 2017 / Accepted: 10 July 2017 / Published: 18 July 2017
Versions Notes
In the published paper [1], the title and Appendix Tables A4, A5, A7, and A8 contain typographical errors. The correct title and table captions are as follows:
Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors
Table A4. p values for McNemar test of significance in difference between image compositing algorithms for the pixel scale classification accuracy. Values less than 0.05 are highlighted in light grey and those less than 0.01 are highlighted in dark grey.
Table A5. p values for McNemar test of significance in difference between spectral indices for the pixel scale classification accuracy. Values less than 0.05 are highlighted in light grey and those less than 0.01 are highlighted in dark grey.
Table A7. p values for McNemar test of significance in difference between image compositing algorithms for the classification accuracy of supplementary land-use validation points for 2007. Values less than 0.05 are highlighted in light grey and those less than 0.01 are highlighted in dark grey.
Table A8. p values for McNemar test of significance in difference between spectral indices for the classification accuracy of supplementary land-use validation points for 2007. Values less than 0.05 are highlighted in light grey and those less than 0.01 are highlighted in dark grey.
We apologize for any inconvenience caused to the readers by these changes. The changes do not affect the scientific results. The manuscript will be updated and the original will remain online on the article webpage.

Reference

  1. Chance, E.W.; Cobourn, K.M.; Thomas, V.A.; Dawson, B.C.; Flores, A.N. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Composting Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546. [Google Scholar] [CrossRef]

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MDPI and ACS Style

Chance, E.W.; Cobourn, K.M.; Thomas, V.A.; Dawson, B.C.; Flores, A.N. Erratum: Chance, E.W., et al. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546. Remote Sens. 2017, 9, 738. https://doi.org/10.3390/rs9070738

AMA Style

Chance EW, Cobourn KM, Thomas VA, Dawson BC, Flores AN. Erratum: Chance, E.W., et al. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546. Remote Sensing. 2017; 9(7):738. https://doi.org/10.3390/rs9070738

Chicago/Turabian Style

Chance, Eric W., Kelly M. Cobourn, Valerie A. Thomas, Blaine C. Dawson, and Alejandro N. Flores. 2017. "Erratum: Chance, E.W., et al. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546" Remote Sensing 9, no. 7: 738. https://doi.org/10.3390/rs9070738

APA Style

Chance, E. W., Cobourn, K. M., Thomas, V. A., Dawson, B. C., & Flores, A. N. (2017). Erratum: Chance, E.W., et al. Identifying Irrigated Areas in the Snake River Plain, Idaho: Evaluating Performance across Compositing Algorithms, Spectral Indices, and Sensors. Remote Sens. 2017, 9, 546. Remote Sensing, 9(7), 738. https://doi.org/10.3390/rs9070738

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