Remote Sensing Letters Vol. 3, No. 3, May 2012, 191–200 Linking ground-based to satellite-derived phenological metrics in support of habitat assessment NICHOLAS C. COOPS*† , THOMAS HILKER† , CHRISTOPHER W. BATER† , MICHAEL A. WULDER‡ , SCOTT E. NIELSEN§ , GREG MCDERMID¶ and GORDON STENHOUSE| †Faculty of Forest Resources Management, University of British Columbia, Vancouver, BC, Canada ‡Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, BC, Canada §Department of Renewable Resources, University of Alberta, Edmonton, AB, Canada ¶Department of Geography, University of Calgary, Calgary, AB, Canada |Foothills Research Institute, Hinton, AB, Canada (Received 20 October 2010; in final form 19 December 2010) Changes in the timing of plant phenology are important indicators of inter-annual climatic variations and are a critical driver of food availability and habitat use for a range of species. A number of remote sensing techniques have recently been developed to observe vegetation cycles throughout the year, including the use of inexpensive visible spectrum digital cameras at the stand level and the use of high temporal frequency Advanced Very High Resolution Radiometer National Oceanic and Atmospheric Administration (AVHRR NOAA) and MODerate resolution Imaging Spectroradiometer (MODIS) imagery at a satellite scale. A fun- damental challenge with using satellite data to track plant phenology, however, is the trade-off between the level of spatial detail and the revisit time provided by the sensor, and the ability to verify the interpretation of phenological activity. One way to address this challenge is to integrate remotely sensed observations obtained at different spatial and temporal scales to provide information that contains both high temporal density and fine spatial resolution observations. In this article, we com- pare measures of vegetation phenology observed from a network of ground-based cameras with satellite-derived measures of greenness derived from a fused broad (MODIS) and fine spatial (Landsat) scale satellite data set. We derive and compare three key indicators of phenological activity including the start date of green-up, start date of senescence and length of growing season from both a ground-based camera network and 30 m spatial resolution synthetic Landsat scenes. Results indi- cate that although field-based estimates, generally, predicted an earlier start and end of the vegetation season than the fused satellite observations, highly significant relationships were found for the prediction of the start (R 2 = 0.65), end (R 2 = 0.72) and length (R 2 = 0.70) of the growing season across all sites. We conclude that some predictable bias exists however unlike visual field measures of the collected data represent both a spectral and a visual archive for later use. *Corresponding author. Email: nicholas.coops@ubc.ca Remote Sensing Letters ISSN 2150-704X print/ISSN 2150-7058 online © 2012 Her Majesty the Queen in the Right of Canada| Natural Resources Canada| Canadian Forest Service http://www.tandf.co.uk/journals DOI: 10.1080/01431161.2010.550330 Downloaded by [The University of British Columbia] at 08:59 04 August 2011