Detecting medusahead (Taeniatherum caput-medusae (L.) Nevski) using high frequency, sequential, globally positioned digital images Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/rx913s62z

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  • Invasive plant species are expanding and transforming vegetative communities across Oregon and throughout the United States. Over the past three decades remote sensing, geographic information system (GIS), and Global Positioning System (GPS) technologies have been integrated to detect and map the distribution of noxious rangeland plants. This study developed low-cost protocols to detect and map Medusahead (Taeniatherum caput-medusae (L.) Nevski) weed infestations using GPS loggers to track aircraft/camera position, altitude, and bearing, as well as Aerial Image Positioning Tool software to geographically rectify and project each aerial image. We then mapped the extent of medusahead in target areas and evaluated patterns of infestation. Flying in a single engine fixed-wing aircraft, images were collected every five seconds, with a total of 10,362 images obtained. All of the aerial images were processed and, on average, 23.9 % of the area was classified as medusahead infested, with 76.1 % without infestation. Each image covered 215 ha (531 acres), with 60% overlap, at a cost of $ 0.54/km². Our study also employed mobile mapping technology to map medusahead on the ground by digitizing infestations using a laptop computer equipped with a GPS antenna and GIS software. Mobile mapping was also done from aircraft, but yielded coarser infestation maps, as the observation distance was greater. These maps covered the full study area. Aerial reconnaissance and mobile survey is cost effective, because thousands of digital images were collected, automatically positioned, and stored.
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  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2011-09-01T15:29:37Z (GMT) No. of bitstreams: 1 Final PhD Dissertation 1_18.pdf: 5643687 bytes, checksum: a558f372e5560a8b50108899cecb1aa0 (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2011-09-06T20:27:35Z (GMT) No. of bitstreams: 1 Final PhD Dissertation 1_18.pdf: 5643687 bytes, checksum: a558f372e5560a8b50108899cecb1aa0 (MD5)
  • description.provenance : Made available in DSpace on 2011-09-06T20:27:36Z (GMT). No. of bitstreams: 1 Final PhD Dissertation 1_18.pdf: 5643687 bytes, checksum: a558f372e5560a8b50108899cecb1aa0 (MD5) Previous issue date: 2011-06-09
  • description.provenance : Submitted by Stephen Ndzeidze (ndzeidzs@onid.orst.edu) on 2011-08-29T14:51:59Z No. of bitstreams: 1 Final PhD Dissertation 1_18.pdf: 5643687 bytes, checksum: a558f372e5560a8b50108899cecb1aa0 (MD5)

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