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dc.contributor.authorTran, Trung V. ( )
dc.contributor.authorJulian, Jason P. ( Orcid Icon 0000-0003-1706-4871 )
dc.contributor.authorde Beurs, Kirsten M. ( Orcid Icon 0000-0002-9244-3292 )
dc.date.accessioned2021-06-29T20:48:53Z
dc.date.available2021-06-29T20:48:53Z
dc.date.issued2014-04
dc.identifier.citationTran, T. V., Julian, J. P., & de Beurs, K. M. (2014). Land cover heterogeneity effects on sub-pixel and per-pixel classifications. International Journal of Geo-Information, 3(2), pp. 540-553.en_US
dc.identifier.issn2220-9964
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/13797
dc.description.abstractPer-pixel and sub-pixel are two common classification methods in land cover studies. The characteristics of a landscape, particularly the land cover itself, can affect the accuracies of both methods. The objectives of this study were to: (1) compare the performance of sub-pixel vs. per-pixel classification methods for a broad heterogeneous region; and (2) analyze the impact of land cover heterogeneity (i.e., the number of land cover classes per pixel) on both classification methods. The results demonstrated that the accuracy of both per-pixel and sub-pixel classification methods were generally reduced by increasing land cover heterogeneity. Urban areas, for example, were found to have the lowest accuracy for the per-pixel method, because they had the highest heterogeneity. Conversely, rural areas dominated by cropland and grassland had low heterogeneity and high accuracy. When a sub-pixel method was used, the producer’s accuracy for artificial surfaces was increased by more than 20%. For all other land cover classes, sub-pixel and per-pixel classification methods performed similarly. Thus, the sub-pixel classification was only advantageous for heterogeneous urban landscapes. Both creators and users of land cover datasets should be aware of the inherent landscape heterogeneity and its potential effect on map accuracy.en_US
dc.formatText
dc.format.extent14 pages
dc.format.medium1 file (.pdf)
dc.language.isoen
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.sourceInternational Journal of Geo-Information, 2014, Vol. 3, No. 2, pp. 540-553.
dc.subjectLandsaten_US
dc.subjectClassificationen_US
dc.subjectLand cover heterogeneityen_US
dc.subjectRemote sensingen_US
dc.titleLand Cover Heterogeneity Effects on Sub-Pixel and Per-Pixel Classificationsen_US
dc.typepublishedVersion
txstate.documenttypeArticle
dc.rights.holder© 2014 The Authors.
dc.identifier.doihttps://doi.org/10.3390/ijgi3020540
dc.rights.licenseCreative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
dc.description.departmentGeography


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