Ground-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetation

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dc.contributor.authorCurran M
dc.contributor.authorHodza P
dc.contributor.authorCox S
dc.contributor.authorLanning S
dc.contributor.authorRobertson B
dc.contributor.authorRobinson T
dc.contributor.authorStahl P
dc.date.accessioned2020-10-02T02:16:36Z
dc.date.available2020-10-02T02:16:36Z
dc.date.issued2020en
dc.date.updated2020-06-10T19:26:46Z
dc.description.abstractRangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the ‘travelling salesperson problem’ (TSP) to increase time and cost efficiency. While UAS images can be acquired 2–3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.en
dc.identifier.citationCurran M, Hodza P, Cox S, Lanning S, Robertson B, Robinson T, Stahl P (2020). Ground-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetation. Journal of Visualized Experiments.en
dc.identifier.doihttps://doi.org/10.3791/61052
dc.identifier.issn1940-087X
dc.identifier.urihttps://hdl.handle.net/10092/101098
dc.language.isoen
dc.rightsAll rights reserved unless otherwise stateden
dc.rights.urihttp://hdl.handle.net/10092/17651en
dc.subject.anzsrcFields of Research::40 - Engineering::4013 - Geomatic engineering::401302 - Geospatial information systems and geospatial data modellingen
dc.subject.anzsrcFields of Research::49 - Mathematical sciences::4905 - Statistics::490507 - Spatial statisticsen
dc.subject.anzsrcFields of Research::41 - Environmental sciences::4104 - Environmental management::410402 - Environmental assessment and monitoringen
dc.titleGround-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetationen
dc.typeJournal Articleen
uc.collegeFaculty of Engineering
uc.departmentMathematics and Statistics
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