Abstract
Phenological metrics are of potential value as direct indicators of climate change. Usually they are obtained via either satellite imaging or ground based manual measurements; both are bespoke and therefore costly and have problems associated with scale and quality. An increase in the use of camera networks for monitoring infrastructure offers a means of obtaining images for use in phenological studies, where the only necessary outlay would be for data transfer, storage, processing and display. Here a pilot study is described that uses image data from a traffic monitoring network to demonstrate that it is possible to obtain usable information from the data captured. There are several challenges in using this network of cameras for automatic extraction of phenological metrics, not least, the low quality of the images and frequent camera motion. Although questions remain to be answered concerning the optimal employment of these cameras, this work illustrates that, in principle, image data from camera networks such as these could be used as a means of tracking environmental change in a low cost, highly automated and scalable manner that would require little human involvement.
Highlights
One aspect of vegetation dynamics that is receiving increasing attention is that of phenology, the cycle of events that drive the seasonal progression of vegetation through stages of dormancy, active growth and senescence [1,2]
A method that was scalable and transferable to other camera networks of this type was a factor to consider. Accounting for these resulted in a three step approach from image capture to extraction of the phenological metrics desired: Step 1—Image pre-processing to collect images from cameras that are in the same general direction and align them; Step 2—identification of areas of the aligned images that have phenological interest for further analyses determination of the greenness of the areas determined over time; and Step 3—extraction of phenological metrics to be compared with manual inspection of the images
The main reason for images being unsuitable for use included road structures appearing too close to the camera; frequent motion in camera meaning that images available from the most frequently occurring camera angle are very sparse in temporal coverage; and large changes in camera angle which lead to low correlations between images in the temporal sequence
Summary
One aspect of vegetation dynamics that is receiving increasing attention is that of phenology, the cycle of events that drive the seasonal progression of vegetation through stages of dormancy, active growth and senescence [1,2]. The timing of such phenological events is indicative of the impact of both short- and long-term climatic changes on the terrestrial biosphere [3]. Ecosystem services to humans of plants, such as the production of food, fibre and extractable chemical substances, as well as the seasonal suitability of landscapes for recreational activities are impacted by phenology [11]. The continuous and automated monitoring of phenology is a key issue in science [12], and as such should be fully integrated in to a systematic and scientifically credible monitoring programme [13,14]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
