Networked web-cameras monitor congruent seasonal development of birches with phenological field observations

Abstract

Ecosystems' potential to provide services, e.g. to sequester carbon, is largely driven by the phenological cycle of vegetation. Timing of phenological events is required for understanding and predicting the influence of climate change on ecosystems and to support analyses of ecosystem functioning. Analyses of conventional camera time series mounted near vegetation has been suggested as a means of monitoring phenological events and supporting wider monitoring of phenological cycle of biomes that is frequently done with satellite earth observation (EO). Especially in the boreal biome, sparsely scattered deciduous trees amongst conifer-dominant forests pose a problem for EO techniques as species phenological signal mix, and render EO data difficult to interpret. Therefore, deriving phenological information from on the ground measurements would provide valuable reference data for earth observed phenology products in a larger scale. Keeping this in mind, we established a network of digital cameras for automated monitoring of phenological activity of vegetation in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. In this study, we used data from 12 sites to investigate how well networked cameras can detect the phenological development of birches (Betula spp.) along a latitudinal gradient. Birches typically appear in small quantities within the dominant species. We tested whether the small, scattered birch image elements allow a reliable extraction of colour indices and the temporal changes therein. We compared automatically derived phenological dates from these birch image elements both to visually determined dates from the same image time series and to independent observations recorded in the phenological monitoring network covering the same region. Automatically extracted season start dates, which were based on the change of green colour fraction in spring, corresponded well with the visually interpreted start of the season, and also to the budburst dates observed in the field. Red colour fraction turned out to be superior to the green colour-based indices in predicting leaf yellowing and fall. The latitudinal gradients derived using automated phenological date extraction corresponded well with the gradients estimated from the 3 phenological field observations. We conclude that small and scattered birch image elements allow reliable extraction of key phenological dates for the season start and end of deciduous species studied here, providing thus important species-specific data for model validation and for explaining the temporal variation in EO phenology products.

Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

“…Here, we have presented a camera network operating in Finland, with cameras mounted in sites ranging from hemiboreal to subarctic regions. So far, we have used the cameras in the analyses of latitudinal trends of birch phenology (Peltoniemi et al, 2018), snow cover , and analyses of Scots pine and wetland CO 2 fluxes (Linkosalmi et al, 2016) with encouraging results. Several possibilities for further research exist, particularly associated with temporal changes of colours in conifer canopies, and changes of snow cover.…”

“…Colour changes in deciduous vegetation and snow cover over the season are distinctive enough to be clearly depicted behind the day-to-day variation due to clouds and irradiation (Peltoniemi et al, 2018;Arslan et al, 2017), but in wetlands and coniferous trees these differences can be more obscure.…”

“…While more detailed radiative transfer analyses may be required to confirm the consequences of pigment and other changing properties of leaves on the colours (Wingate et al, 2015), the clearest phenomena such as budburst and autumn colour peaks can already be extracted with simple time series and break point analyses with fairly good accuracy (e.g. Sonnentag et al, 2012;Klosterman et al, 2014;Wingate et al, 2015;Peltoniemi et al, 2018). Besides vegetation monitoring, time lapse images have been used in snow cover monitoring.…”

Measuring Vegetation Phenology with Near-Surface Remote Sensing in a Temperate Deciduous Forest: Effects of Sensor Type and Deployment

“…However, we found the larger inclination-angle resulted in an earlier POS ( Table 2), indicating that increasing the inclination-angle did not delay the peak of GCC C . The reason for the summer decline of GCC C after the POS and the physiological mechanism of POS are poorly understood and need further exploration [55][56][57][58].…”

Monitoring changes in forestry and seasonal snow using surface albedo during 1982–2016 as an indicator

“…According to observations, cold, snow-rich winters have become more common again in large parts of Europe since 2005 (e.g. Cohen et al, 2010Cohen et al, , 2012Petoukhov and Semenov, 2010;Osborn, 2011). Global climate models have challenges in representing the recent changes in the Arctic.…”