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dc.contributor.author
Bentivegna, Diego Javier  
dc.contributor.author
Smeda, Reid J.  
dc.contributor.author
Wang, Cuizhen  
dc.date.available
2017-01-16T19:58:44Z  
dc.date.issued
2012-04  
dc.identifier.citation
Bentivegna, Diego Javier; Smeda, Reid J.; Wang, Cuizhen; Detecting Cutleaf Teasel (Dipsacus laciniatus) along a Missouri Highway with Hyperspectral Imagery; Weed Science Society of America; Invasive Plant Science and Management; 5; 2; 4-2012; 155-163  
dc.identifier.issn
1939-7291  
dc.identifier.uri
http://hdl.handle.net/11336/11425  
dc.description.abstract
Cutleaf teasel is an invasive, biennial plant that poses a significant threat to native species along roadsides in Missouri. Flowering plants, together with understory rosettes, often grow in dense patches. Detection of cutleaf teasel patches and accurate assessment of the infested area can enable targeted management along highways. Few studies have been conducted to identify specific species among a complex of vegetation composition along roadsides. In this study, hyperspectral images (63 bands in visible to near-infrared spectral region) with high spatial resolution (1 m) were analyzed to detect cutleaf teasel in two areas along a 6.44-km (4-mi) section of Interstate I-70 in mid Missouri. The identified classes included cutleaf teasel, bare soil, tree/shrub, grass/other broadleaf plants, and water. Classification of cutleaf teasel reached a user’s accuracy of 82 to 84% and a producer’s accuracy of 89% in the two sites. The conditional k value was around 0.9 in both sites. The image-classified cutleaf teasel map provides a practical mechanism for identifying locations and extents of cutleaf teasel infestation so that specific cutleaf teasel management techniques can be implemented.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Weed Science Society of America  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Roadside  
dc.subject
Hyperspectral Remote Sensing  
dc.subject
Weed Detection  
dc.subject.classification
Otras Agricultura, Silvicultura y Pesca  
dc.subject.classification
Agricultura, Silvicultura y Pesca  
dc.subject.classification
CIENCIAS AGRÍCOLAS  
dc.title
Detecting Cutleaf Teasel (Dipsacus laciniatus) along a Missouri Highway with Hyperspectral Imagery  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2017-01-13T19:19:24Z  
dc.identifier.eissn
1939-747X  
dc.journal.volume
5  
dc.journal.number
2  
dc.journal.pagination
155-163  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Lawrence  
dc.description.fil
Fil: Bentivegna, Diego Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida(i); Argentina. University Of Missouri; Estados Unidos  
dc.description.fil
Fil: Smeda, Reid J.. University Of Missouri; Estados Unidos  
dc.description.fil
Fil: Wang, Cuizhen. University Of Missouri; Estados Unidos  
dc.journal.title
Invasive Plant Science and Management  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.bioone.org/doi/abs/10.1614/IPSM-D-10-00053.1  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1614/IPSM-D-10-00053.1