Approximate georeferencing and automatic blurred image detection to reduce the costs of UAV use in environmental and agricultural applications
The application of geomatic products in environmental and agricultural applications directly depends on the cost of obtaining these products. This cost is primarily affected by the cost of unmanned aerial vehicles (UAV) and the image acquisition and treatment processes that are conducted to obtain t...
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Published in | Biosystems engineering Vol. 151; pp. 308 - 327 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.11.2016
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Subjects | |
Online Access | Get full text |
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Summary: | The application of geomatic products in environmental and agricultural applications directly depends on the cost of obtaining these products. This cost is primarily affected by the cost of unmanned aerial vehicles (UAV) and the image acquisition and treatment processes that are conducted to obtain the geomatic products. In this study, a methodology was developed to reduce the cost of generating geomatic products by 1) automatically detecting blurred images in a set of images that was captured with a UAV by establishing a numeric indicator that describes the level of blur in the images for a specific camera setting and by 2) eliminating the need to measure ground control points (GCPs) for georeferencing the final geomatic products with the approximate exterior orientation of the images and control points from existing geomatic products. The time that was saved in performing the manual tasks that were required to generate geomatic products, which are the tasks that strongly influence cost, were decreased in our 40 ha case study by 65–69%, which corresponds to a cost savings of €200–225.
•A procedure to reduce the cost of geomatic products obtained with UAVs is developed.•An algorithm to automatically detect blurred images was developed.•Approximate georeferencing geomatic products without using ground control points.•The time required was decreased by 65–69% in the case study of 40 ha. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1537-5110 1537-5129 |
DOI: | 10.1016/j.biosystemseng.2016.09.014 |