Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment

Abstract

Critical to habitat management is the understanding of not only the location of animal food resources, but also the timing of their availability. Grizzly bear (Ursus arctos) diets, for example, shift seasonally as different vegetation species enter key phenological phases. In this paper, we describe the use of a network of seven ground-based digital camera systems to monitor understorey and overstorey vegetation within species-specific regions of interest. Established across an elevation gradient in western Alberta, Canada, the cameras collected true-colour (RGB) images daily from 13 April 2009 to 27 October 2009. Fourth-order polynomials were fit to an RGB-derived index, which was then compared to field-based observations of phenological phases. Using linear regression to statistically relate the camera and field data, results indicated that 61% (r 2 = 0.61, df = 1, F = 14.3, p = 0.0043) of the variance observed in the field phenological phase data is captured by the cameras for the start of the growing season and 72% (r 2 = 0.72, df = 1, F = 23.09, p = 0.0009) of the variance in length of growing season. Based on the linear regression models, the mean absolute differences in residuals between predicted and observed start of growing season and length of growing season were 4 and 6 days, respectively. This work extends upon previous research by demonstrating that specific understorey and overstorey species can be targeted for phenological monitoring in a forested environment, using readily available digital camera technology and RGB-based vegetation indices.

Optimizing the Timing of Unmanned Aerial Vehicle Image Acquisition for Applied Mapping of Woody Vegetation Species Using Feature Selection

“…To some extent, near-surface cameras can be used also for individual classification [43]. Studies that use near-surface cameras usually examine monoculture canopies of a single species [44] or a small sample of individuals [45,46]. Among the relevant literature, we are not aware of previous attempts to examine a large and representative sample of the local species composition using ground cameras.…”

Monitoring plant condition and phenology using infrared sensitive consumer grade digital cameras

“…Both cameras were controlled by an intervallometer and sealed in a fiberglass housing. The entire system is self-contained and can operate unattended for several months, until available data storage is exhausted (Bater et al, 2011a). The system was mounted on a nearby tree, with the cameras as close to each other as possible.…”

“…The use of consumer-grade digital cameras is recognized as a cost-effective method to obtain high temporal resolution data on vegetation processes ). In phenological research, studies have utilized cameras mounted on fixed locations (Bater et al 2011a;Kurc & Benton 2010;Nijland et al 2012;Richardson et al 2009) or publicly available webcam imagery (Graham et al 2010;Ide & Oguma 2010) to monitor vegetation changes. Because the cameras are ground-based, observations are restricted to individual plant or stand scales and are commonly referred to as 'near sensing' (Jongschaap and Booij, 2004).…”

Exploring the Potential for Automatic Extraction of Vegetation Phenological Metrics from Traffic Webcams

“…Such studies point to the possibility of using other combinations of spectral channels (e.g., Zhao et [45]). Other suggested research avenues include a focus on understorey vegetation [16,61], though this would not be directly applicable using this network, though at different times of year the leaf area of certain trees may allow "background" vegetation to be observed [48,50]. Another avenue could be to examine the variability in the accuracy with which the phenological dates are captured as a function of the timing of the images used.…”