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dc.contributor.authorKastens, Jude H.
dc.contributor.authorBrown, J. Christopher
dc.contributor.authorCoutinho, Alexandre Camargo
dc.contributor.authorBishop, Christopher R.
dc.contributor.authorEsquerdo, Júlio César D. M.
dc.date.accessioned2019-01-29T01:48:12Z
dc.date.available2019-01-29T01:48:12Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/1808/27652
dc.descriptionThis dataset was prepared for use in MODIS NDVI-based land cover classification for Mato Grosso, Brazil, which is an Amazonian agricultural frontier. Quantification of the displacement of forests by agriculture (horizontal intensification) and the transition of farm fields from single-cropping to double-cropping (vertical intensification) is necessary for understanding the rapid environmental and social changes that are occurring within this globally important region.en_US
dc.description.abstractThe points associated with ‘ground reference set 1’ and ‘ground reference set 2’ identify fields where agricultural cover information was obtained by Embrapa through farmer interviews. The points associated with ‘supplemental pasture/cerrado’ were identified using aerial and satellite imagery to provide additional ground reference samples for the pasture/cerrado data class. See the following publication for more information (please cite this reference when using these data):

Kastens, J.H., J.C. Brown, A.C. Coutinho, C.R. Bishop, and J.C.D.M. Esquerdo (2017). Soy moratorium impacts on soybean and deforestation dynamics in Mato Grosso, Brazil. PLoS ONE, 12(4): e0176168. DOI: 10.1371/journal.pone.0176168 (https://doi.org/10.1371/journal.pone.0176168 )

Annual attributes beginning with ‘plos’ provide a binary indicator for whether or not the sample was used for development of the 14-year Mato Grosso land cover map set described in the PLOS ONE study (1 = used, 0 = not used). For additional information regarding class structure determination and data preparation and filtering, see the following:

Brown, J.C., J.H. Kastens, A.C. Coutinho, D.C. Victoria, and C.R. Bishop (2013). Classifying Multiyear Agricultural Land Use Data from Mato Grosso Using Time-Series MODIS Vegetation Index Data. Remote Sensing of Environment, 130(3): 39-50. DOI: 10.1016/j.rse.2012.11.009 (http://dx.doi.org/10.1016/j.rse.2012.11.009)
en_US
dc.description.sponsorshipEmbrapaen_US
dc.description.sponsorshipKansas Biological Surveyen_US
dc.rights© 2017 Kastens et al. This is an open access dataset distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectBrazilen_US
dc.subjectAgricultureen_US
dc.subjectCerradoen_US
dc.subjectCottonen_US
dc.subjectDouble-croppingen_US
dc.subjectEmbrapaen_US
dc.subjectGround referenceen_US
dc.subjectMato Grossoen_US
dc.subjectPastureen_US
dc.subjectSingle-croppingen_US
dc.subjectSoybeansen_US
dc.titleMato Grosso, Brazil, ground reference data for crop years 2005-2013 (Dataset)en_US
dc.typeDataseten_US
kusw.kuauthorBrown, J. Christopher
kusw.kudepartmentEnvironmental Studiesen_US
dc.identifier.doi10.17161/1808.27652
dc.rights.accessrightsopenAccessen_US


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© 2017 Kastens et al. This is an open access dataset distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Except where otherwise noted, this item's license is described as: © 2017 Kastens et al. This is an open access dataset distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.