Canadian Forest Service Publications

The Landsat observation record of Canada: 1972-2012. 2013. White, J.C.; Wulder, M.A. Canadian Journal of Remote Sensing 39(6):1-13.

Year: 2014

Available from: Pacific Forestry Centre

Catalog ID: 35353

Language: English

CFS Availability: PDF (download), PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.5589/m13-053

† This site may require a fee.

Abstract

The Landsat data archive represents more than 40 years of Earth observation, providing a valuable information source for monitoring ecosystem dynamics. In excess of 605000 images of Canada have been acquired by the Landsat program since 1972. Herein we report several spatial and temporal characteristics of the Landsat observation record for Canada (1972–2012), including image availability by year, growing season, sensor, ecozone, and provincial or territorial jurisdiction. In contrast to the global Landsat archive, which is dominated by Enhanced Thematic Mapper Plus (ETM+) data, the majority of archived Landsat images of Canada were acquired by the Thematic Mapper (TM) sensor (57%). Approximately 55% of archived Landsat images were acquired within ± 30 days of 1 August, and 74% of Worldwide Reference System–2 path–row locations in Canada have more than 200 images acquired between 1 June and 30 September. Issues such as cloud cover and the availability of imagery to support pixel-based image compositing and time series analyses are explored and documented. For a pixel-based image compositing scenario whereby images (TM and ETM+) acquired after 1981 with less than 70% cloud cover and a target date of 1 August ± 30 days are considered, 60% of the path–row locations have five or fewer years of missing data in the archive. For time series analyses (i.e., ecosystem monitoring scenario) with the same temporal constraint but with less than 10% cloud cover, only 2% of path–row locations are missing five or fewer years of data, with a mean and median of 17 years of missing data. However, if a broader temporal window (1 June to 30 September) is considered for this scenario, 18% of path–row locations have five or fewer years of missing data. Free and open-access to the Landsat data archive, combined with the continuity of new data collections provided by the recently launched Landsat 8 satellite, offer many opportunities for scientific inquiry concerning the status and trends of Canada's terrestrial ecosystems.

Plain Language Summary

The Landsat Program provides the longest, continuous record of Earth observation data: more than 40 years of Landsat data have been made freely and openly accessible via the internet by the United States Geological Survey. Landsat data brings two key elements to ecosystem monitoring: a spatial dimension that is at a scale appropriate for capturing human impacts, and a temporal dimension that enables retrospective analyses and characterization of changes over the program's extensive lifespan. More than 605,000 images of Canada have been acquired by the Landsat program since 1972. In this publication, we report on the spatial and temporal characteristics of the Landsat observation record for Canada (1972–2012), including image availability by year, growing season, sensor, ecozone, and provincial or territorial jurisdiction. In contrast to the global Landsat archive, which is dominated by Enhanced Thematic Mapper Plus (ETM+) data, the majority of archived Landsat images of Canada were acquired by the Thematic Mapper (TM) sensor (57%). Approximately 55% of archived Landsat images were acquired within ± 30 days of August 1, and 74% of unique path/row (scene) locations in Canada have more than 200 images acquired between June 1 and September 30. The capacity of archived Landsat data to satisfy various application requirements, such as pixel-based image compositing and time series analyses are also analyzed and reported. This paper provides the first systematic assessment of Landsat data archive holdings for Canada, aimed at supporting national applications, monitoring, and reporting initiatives.

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