期刊论文详细信息
AIMS Environmental Science
Rangeland monitoring using remote sensing: comparison of cover estimates from field measurements and image analysis
April Hulet1  Ryan Jensen2  Steven Petersen3  Bruce Roundy3  Danny Summers4  Ammon Boswell5 
[1] Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, Idaho, 83843, USA;Department of Geography, Brigham Young University, Provo, Utah, 84602, USA;Department of Plant and Wildlife Sciences, Brigham Young University, Provo, Utah, 84602, USA;Great Basin Research Center, Utah Division of Wildlife Resources, Ephraim, Utah, 84627, USA;Natural Resource Conservation Service, Monticello, Utah, 84535, USA;
关键词: Image classification;    canopy cover;    rangeland monitoring;    remote sensing;   
DOI  :  10.3934/environsci.2017.1.1
来源: DOAJ
【 摘 要 】

Rangeland monitoring is important for evaluating and assessing semi-arid plant communities. Remote sensing provides an effective tool for rapidly and accurately assessing rangeland vegetation and other surface attributes such as bare soil and rock. The purpose of this study was to evaluate the efficacy of remote sensing as a surrogate for field-based sampling techniques in detecting ground cover features (i.e., trees, shrubs, herbaceous cover, litter, surface), and comparing results with field-based measurements collected by the Utah Division of Wildlife Resources Range Trent Program. In the field, five 152 m long transects were used to sample plant, litter, rock, and bare-ground cover using the Daubenmire ocular estimate method. At the same location of each field plot, a 4-band (R,G,B,NIR), 25 cm pixel resolution, remotely sensed image was taken from a fixed-wing aircraft. Each image was spectrally classified producing 4 cover classes (tree, shrub, herbaceous, surface). No significant differences were detected between canopy cover collected remotely and in the field for tree (P = 0.652), shrub (P = 0.800), and herbaceous vegetation (P = 0.258). Surface cover was higher in field plots (P < 0.001), likely in response to the methods used to sample surface features by field crews. Accurately classifying vegetation and other features from remote sensed information can improve the efficiency of collecting vegetation and surface data. This information can also be used to improve data collection frequency for rangeland monitoring and to efficiently quantify ecological succession patterns.

【 授权许可】

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