Imaging phenology; scaling from camera plots to landscapes

W. Nijland*, D. K. Bolton, Nicholas C. Coops, Gordon B. Stenhouse

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Information on the spatial and temporal patterns of plant phenology is important to develop a more comprehensive understanding of food availability and habitat for many animal species. The combination of broad scale, regional climatic, and more localized, site-level drivers presents a challenge when upscaling phenology from the plot to the region. Likewise, developing relationships between ground- or camera-based estimates and satellite imagery remains difficult due to the trade-off between temporal and spatial resolution. Landsat imagery, with its 16 day temporal resolution, is often thought of as being insufficient for timely observation of changes in vegetation throughout the year. However the free availability of the Landsat archive has enabled a major shift in the way Landsat imagery is processed moving towards pixel, rather than scene, based analyses. In this paper we build on previous research by examining the applicability and accuracy of Landsat derived phenology curves beyond deciduous stands into more mixed stands and conifer dominated forest types in the Rocky Mountains and foothills in Alberta, Canada. In addition, we discuss the application of these Landsat phenology curves to phenology of understorey species which are linked to habitat selection for free roaming wildlife, in particular grizzly bears. The agreement between Landsat- and camera-derived estimates of key phenological events was stronger for green-up (RMSE = 7 days) than for senescence (RMSE = 14 days). Our results show that yearly adjustment of green-up and senescence dates using available Landsat observations improved the agreement with camera-derived estimates when compared to average annual curves. Seasonal phenology transition dates accepted as valid ranged from 25% for alpine herbaceous pixels to 75% for closed deciduous, demonstrating the variable success of this approach across land cover types. Season transition dates were rejected if pixels lacked a strong enough green-up signal in Landsat spectral indices or if the estimated dates fell outside of the valid range. We conclude by investigating the spatial patterns of seasonal phenology at the Landsat scale, and assess the relative importance of regional vs. microsite conditions as well as the utility of these data for resource and wildlife management.

Original languageEnglish
Pages (from-to)13-20
Number of pages8
JournalRemote Sensing of Environment
Volume177
DOIs
Publication statusPublished - 1 May 2016
Externally publishedYes

Funding

Andrew Richardson (Harvard University) and Scott Ollinger (University of New Hampshire) provided initial advice and enthusiasm for the camera network plans. Chris Bater was instrumental in helping establish the network and the data for a number of the key years. Funding for this research was generously provided by the Grizzly Bear Program of the Foothills Research Institute located in Hinton, Alberta, Canada, with support from Alberta Innovates Biosolutions and the many funding partners of this research program (additional information available at: http://www.foothillsresearchinstitute.ca /). Additional funding was provided by an NSERC ( RGPIN 311926-13 ) grant to Coops.

Keywords

  • Habitat
  • Landsat
  • Phenology
  • Understorey
  • Vegetation

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