Literature DB >> 26305460

Correction: Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification.

Yohannes Ayanu, Christopher Conrad, Anke Jentsch, Thomas Koellner.   

Abstract

Year:  2015        PMID: 26305460      PMCID: PMC4549280          DOI: 10.1371/journal.pone.0137150

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


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There are errors in the first paragraph of the “Predicted undercover cropland” section of the Results. “Hectares per pixel” should read “m2 per pixel.” There are errors in Fig 4 and in its caption. Please see the complete, correct Fig 4 here.
Fig 4

Undercover cropland area predicted from most influential topographic factors identified using Boosted Regression Trees. (pixel size of 100 m2)

There are errors in the caption for S5 Fig. Please view the correct S5 Fig. caption below.

Predicted undercover cropland in m2 per pixel.

Prediction using only most influential factors slope, elevation and east aspect (Fig a). Prediction using all topographic factors slope, elevation, east aspect, west aspect, south aspect and north aspect (Fig b). Pixel size is 100 m2. (PDF) Click here for additional data file.
  1 in total

1.  Unveiling Undercover Cropland Inside Forests Using Landscape Variables: A Supplement to Remote Sensing Image Classification.

Authors:  Yohannes Ayanu; Christopher Conrad; Anke Jentsch; Thomas Koellner
Journal:  PLoS One       Date:  2015-06-22       Impact factor: 3.240

  1 in total

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