| Title | Accuracy assessment using sub-pixel fractional error matrices of global land cover products derived from satellite data |
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| Author | Latifovic, R; Olthof, I |
| Source | Remote Sensing of Environment vol. 90, no. 2, 2004 p. 153-165, https://doi.org/10.1016/j.rse.2003.11.016 |
| Year | 2004 |
| Alt Series | Natural Resources Canada, Contribution Series 20181229 |
| Publisher | Elsevier BV |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Canada Centre for Remote Sensing Divsion |
| Released | 2004 03 01 |
| Abstract | Information on land cover distribution at regional and global scales has become fundamental for studying global changes affecting ecological and climatic systems. The remote sensing community has
responded to this increased interest by improving data quality and methodologies for extracting land cover information. However, in addition to the advantages provided by satellite products, certain limitations exist that need to be objectively
quantified and clearly communicated to users so that they can make informed decisions on whether and how land cover products should be used. Accuracy assessment is the procedure used to quantify product quality. Some aspects of accuracy assessment
for evaluating four global land cover maps over Canada are discussed in this paper. Attempts are made to quantify limiting factors resulting from the coarse spatial resolution of data used for generating land cover information at regional and global
levels. Sub-pixel fractional error matrices are introduced as a more appropriate way for assessing the accuracy of mixed pixels. For classification with coarse spatial resolution data, limitations of the classification method produce a maximum
achievable accuracy defined as the average percent fraction of dominant land cover of all pixels in the mapped area. Relationships among spatial resolution, landscape heterogeneity and thematic resolution were studied and reported. Other factors that
can affect accuracy, such as misregistration and legend conversion, are also discussed. |
| GEOSCAN ID | 311583 |
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