We Must all Pay More Attention to Rigor in Accuracy Assessment: Additional Comment to "The Improvement of Land Cover Classification by Thermal Remote Sensing". Remote Sens, 2015, 7, 8368-8390

Despite recent calls for statistically robust and transparent accuracy assessment [1], further attention to rigor is still needed. Here I take the opportunity of a disputed accuracy assessment recently published in Remote Sensing [2,3,4] to highlight some issues regarding sampling design, response design and analysis that I often find as a reviewer, and that I too have neglected in the past, among them: (i) use of a sampling design that is purposive instead of probability based; (ii) use of suboptimal label allocation procedures for reference data; and (iii) incorrect computation of accuracy estimates and lack of reporting of confidence intervals. Following the good practices in [1] will enhance the scientific credibility of our discipline.

• Publication year

  2016

• Venue

  Remote Sensing

• Publication date

  2016-03-26

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.3390/rs8040288
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Response to Johnson B.A. Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on "The Improvement of Land Cover Classification by Thermal Remote Sensing". Remote Sens 2015, 7, 8368-8390

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• The Improvement of Land Cover Classification by Thermal Remote Sensing

  2015influential reference
• Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on "The Improvement of Land Cover Classification by Thermal Remote Sensing". Remote Sensing 2015, 7(7), 8368-8390

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