View
Publication Type
Journal Article
Author, Analytic
Coy, Andre D; Rankine, Dale R; Taylor, Micheal A.; Nielsen, David C; Cohen, Jane E.
Author Affiliation, Ana.
n/a
Article Title
Increasing the Accuracy and Automation of Fractional Vegetation Cover Estimation from Digital Photographs
Medium Designator
n/a
Connective Phrase
n/a
Journal Title
Remote sensing
Translated Title
n/a
Reprint Status
Refereed
Date of Publication
2016
Volume ID
8
Issue ID
n/a
Page(s)
474
Language
n/a
Connective Phrase
n/a
Location/URL
n/a
ISSN
n/a
Notes
n/a
Abstract
The use of automated methods to estimate fractional vegetation cover (FVC) from digital photographs has increased in recent years given its potential to produce accurate, fast and inexpensive FVC measurements. Wide acceptance has been delayed because of the limitations in accuracy, speed, automation and generalization of these methods. This work introduces a novel technique, the Automated Canopy Estimator (ACE) that overcomes many of these challenges to produce accurate estimates of fractional vegetation cover using an unsupervised segmentation process. ACE is shown to outperform nine other segmentation algorithms, consisting of both threshold-based and machine learning approaches, in the segmentation of photographs of four different crops (oat, corn, rapeseed and flax) with an overall accuracy of 89.6%. ACE is similarly accurate (88.7%) when applied to remotely sensed corn, producing FVC estimates that are strongly correlated with ground truth values....
read more