The Landsat observation record of Canada: 1972–2012

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 605 000 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 930 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.

Full text

Research Note / Note de Recherche
The Landsat observation record of Canada:
1972

2012
Joanne C. White and Michael A. Wulder
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
930 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 930 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.
Re
´sume
´.L’archive des donne´es Landsat contient plus de 40 anne´es d’observation de la Terre, fournissant une source
d’information pre´cieuse pour le suivi de la dynamique des e´cosyste`mes. Au-dela` de 605 000 images du Canada ont e´te´
acquises par le programme Landsat depuis 1972. Nous rapportons ici plusieurs caracte´ristiques spatiales et temporelles
de l’archive des observations Landsat du Canada (19722012), y compris la disponibilite´ des images par anne´e, saison de
croissance, capteur, e´ cozone et juridiction provinciale ou territoriale. Contrairement a` l’archive Landsat mondiale, qui est
domine´ e par les donne´es Enhanced Thematic Mapper Plus (ETM), la majorite´ des images Landsat archive´ es du Canada
ont e´te´ acquises par le capteur Thematic Mapper (TM; 57 %). Environ 55 % des images Landsat archive´es ont e´te´ acquises
a` l’inte´rieur de 930 jours du 1er aout, et 74 % des coordonne´es colonnes/lignes WRS-2 au Canada ont plus de 200 images
acquises entre le 1er juin et le 30 septembre. Des proble` mes tels que la couverture nuageuse et la disponibilite´ de l’imagerie
pour la composition d’images par pixel et l’analyse de se´ries temporelles sont explore´es et documente´es. Pour un sce´nario
de composition d’image par pixel dans lequel les images (TM et ETM) acquises apre`s 1981 avec moins de 70 % de
couverture nuageuse et une date cible du 1er aout930 jours sont conside´re´es, 60 % des coordonne´es colonnes/lignes ont
5 anne´ es ou moins de donne´es manquantes dans l’archive. Pour l’analyse des se´ries temporelles (c.-a`-d. sce´ nario de
surveillance de l’e´cosyste` me) avec la meˆme contrainte temporelle, mais avec moins de 10 % de couverture nuageuse,
seulement 2 % des coordonne´ es colonnes/lignes manque 5 ans ou moins de donne´es, avec une moyenne et une me´ diane de
17 ans de donne´ es manquantes. Toutefois, si une feneˆ tre temporelle plus large (1er juin au 30 septembre) est conside´re´e
pour ce sce´nario, 18 % des coordonne´es colonnes/lignes ont 5 ans ou moins de donne´ es manquantes. L’acce` s gratuit et
libre a` l’archive de donne´es Landsat combine´ avec la continuite´ de nouvelles collectes de donne´es fournies par le satellite
Landsat 8 re´cemment lance´ offrent de nombreuses possibilite´s pour la recherche scientifique concernant l’e´tat et les
tendances des e´ cosyste`mes terrestres du Canada.
[Traduit par la Re´daction]
Received 11 September 2013. Accepted 6 November 2013. Published on the Web at http://pubs.casi.ca/journal/cjrs on 13 February 2014.
Joanne C. White
1
, and Michael A. Wulder. Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside
Road, Victoria, BC, V8Z 1M5, Canada.
1
Corresponding author (e-mail: joanne.white@nrcan.gc.ca).
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Introduction
Since 1972 Landsat has provided information on the
status and dynamics of Canada’s terrestrial ecosystems
at a spatial resolution that captures the impacts of human
activities (Townshend and Justice, 1988). Landsat has
played an important role in mapping Canada’s land cover
(Wulder et al., 2008; Olthof et al., 2009), monitoring
disturbance events (Skakun et al., 2003; Schroeder et al.,
2011; Pasher et al., 2013), and characterizing long-term
changes in vegetation cover (Fraser et al., 2009; 2011;
McManus et al., 2012; Valeria et al., 2012). Landsat data
has also been used for a number of other applications,
including the assessment of wildlife habitat (White et al.,
2011; Chen et al., 2013), geomorphological applications
(Tenantetal.,2012;Bolchet al., 2010), and monitoring
of urban expansion (Furberg and Ban, 2012), to name but
a few.
In 1992, the United States Congress mandated the
establishment of a permanent government-held Earth
observation archive, which was to include the long-term
Landsat data record (Goward et al., 2006). Significant
changes to the Landsat data distribution policy in 2008
made the entire Landsat data archive and all newly
acquired Landsat data held by the United States Geolo-
gical Survey (USGS), freely and openly available to the
global community (Woodcock et al., 2008; Wulder et al.,
2012). At the time of writing, more than 12 million
images have been downloaded from the archive since
8 December 2008.
2
Free and open access to the Landsat
archive has greatly increased the use of Landsat data for
science and applications purposes (National Research
Council, 2013), especially for large jurisdictions such as
Canada.
Since the launch of Landsat 1 on 23 July 1972, sensors
onboard the Landsat series of satellites, including Multi-
spectral Scanner (MSS), Thematic Mapper (TM), and
Enhanced Thematic Mapper Plus (ETM), have ac-
quired more than 605 000 images of Canada, providing
the longest continuous Earth observation record of
Canada’s terrestrial ecosystems. MSS data were acquired
by Landsat 15 from 1972 to 1992 (and again briefly
in 2012); TM data were acquired by Landsat 4 and 5
from 1982 until 2011; and ETMdata have been
acquired by Landsat 7 since 1999 (Williams et al., 2006).
In February 2013, Landsat 8 was successfully launched
and is currently acquiring data with two independent
sensors: the Operational Land Imager (OLI) and the
Thermal Infrared Sensor (TIRS). Specifications for
Landsat sensors operating from 1972 to 2012 are sum-
marized in Table 1.
At the time of writing, the Landsat archive is estimated to
hold approximately 4 million images of the globe.
3
Since the
inception of the Landsat program, Canada has played an
active role as an International Cooperator, building a data
receiving station in Prince Albert, Saskatchewan, in 1972,
which was the first station outside the United States to
receive data from Landsat 1 (Draeger et al., 1997). A second
receiving station, built in Gatineau, Quebec, in 1985, further
expanded coverage to the complete land area and coastlines
of Canada. Both receiving stations are operated by the
Canada Centre for Remote Sensing (CCRS), Natural
Resources Canada.
4,5
Due to factors such as onboard recording and downlink
capacity prior to Landsat 8, a global network of receiving
stations known as International Cooperators were re-
quired to receive Landsat data (Goward et al., 2006). A
comprehensive assessment of the global Landsat archive
in 2006 revealed the existence of many spatial and
temporal gaps in the archive arising from a variety of
technical and administrative causes (Goward et al., 2006;
Williams et al., 2006). In an effort to address these gaps,
the USGS has actively sought to repatriate all unique
imagery held by International Cooperators; as of 1 August
2013, more than 2.2 million images have been acquired
from International Cooperators and integrated into the
archive.
6
Approximately 378 355 unique Landsat images
acquired by Canadian receiving stations have been pro-
vided to the USGS since 2009 (Kline, 2013). At the time of
writing, all of these images have been incorporated into
the USGS archive with the exception of 137 000 MSS
images that are currently in the process of being added to
the archive.
7
The USGS stopped acquiring TM data from the Landsat
5 satellite in November 2011*after a 27-year period that far
exceeded its original 3-year design life.
8
Presently, Landsat 7
and 8 acquire image data on a daily basis. Landsat 7 is
projected to have sufficient fuel to enable data acquisition
until 2017.
9
Since 31 May 2003, the Scan Line Corrector
(SLC) of the ETMsensor has been inoperable, resulting in
images with gaps towards the scene edges (Williams et al.,
2006). The SLC-off data acquired after the malfunction
remains of comparable quality to data collected prior to the
malfunction and several approaches have been implemented
to fill in the SLC-off gaps (e.g., Maxwell, 2004; Maxwell
et al., 2007).
To optimize the distribution of images for acquisition of
seasonal, global, cloud-free collections of land observations,
increasingly sophisticated collection plans are implemented.
For instance, the Long-Term Acquisition Plan (LTAP)
described by Arvidson et al. (2001; 2006) ensures that
2
http://landsat.usgs.gov/Landsat_Project_Statistics.php
3
http://landsat.usgs.gov/metadatalist.php (downloaded June 21,
2013).
4
http://www.nrcan.gc.ca/earth-sciences/products-services/satellite-
photography-imagery/satellite-facilities/2348
5
http://landsat.usgs.gov/about_ground_stations.php
6
http://landsat.usgs.gov/about_LU_Vol_7_Issue_4.php#1a
7
http://landsat.usgs.gov/mission_headlines2013.php; see 8 July
2013.
8
http://landsat.usgs.gov/L5_Decommission.php
9
http://landsat.gsfc.nasa.gov/?p1900
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more images are acquired in those areas that are experien-
cing seasonal change (i.e., vegetation growth or senescence).
Building upon these previous experiences, Landsat 8 has a
similar LTAP, although with a greater number of potential
collects per day (more than 400 images per day vs. the 350
images per day acquired by Landsat 7). Landsat 8 also has
large capacity on-board data recorders and high bandwidth
(S-band) downlink enabling all data collected to be stored
and transmitted to a central receiving station (Sioux Falls,
South Dakota) (Irons et al., 2012).
Various studies have examined the Landsat archive, either
to interrogate for global coverage, to support specific
Table 1. Specifications for Landsat sensors operating from 1972 to 2012.
Sensor Satellite Spectral bands WRS Pixel size (m) Revisit (days) Scene size (km)
MSS 1,2,3 Band 4: Visible (0.50.6 mm) 1 60 18 170 185
Band 5: Visible (0.60.7 mm)
Band 6: NIR (0.70.8 mm)
Band 7: NIR (0.81.1 mm)
MSS 4,5 Band 1: Visible (0.50.6 mm) 2 60 16 170 185
Band 2: Visible (0.60.7 mm)
Band 3: NIR (0.70.8 mm)
Band 4: NIR (0.81.1 mm)
TM 4,5 Band 1: Visible (0.450.52 mm) 2 30 (thermal: 120) 16 170 185
Band 2: Visible (0.520.60 mm)
Band 3: Visible (0.630.69 mm)
Band 4: NIR (0.760.90 mm)
Band 5: NIR (1.551.75 mm)
Band 6: Thermal (10.4012.50 mm)
Band 7: MIR (2.082.35 mm)
ETM7 Band 1: Visible (0.450.52 mm) 2 30 (thermal: 60) (pan: 15) 16 170 185
Band 2: Visible (0.520.60 mm)
Band 3: Visible (0.630.69 mm)
Band 4: NIR (0.770.90 mm)
Band 5: NIR (1.551.75 mm)
Band 6: Thermal (10.4012.50 mm)
Band 7: MIR (2.092.35 mm)
Band 8: PAN (0.520.90 mm)
Figure 1. Total number of archived Landsat images acquired for Canada, by year and sensor.
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applications, or to assess holdings for specific jurisdictions
(Fuller et al., 1994; Goward et al., 2006; Ju and Roy, 2007;
Kovalksyy and Roy, 2013). To the authors’ knowledge, no
studies have specifically examined and reported on the
availability of archived Landsat images for Canada. In this
communication, we describe the Landsat observation record
for Canada from 1972 to 2012, providing insights on the
source (i.e., sensor) and spatial and temporal distributions
of Landsat images that have been acquired during this
period. Issues such as cloud cover and the availability of
imagery to support pixel-based image compositing and time
series analyses are also explored and documented.
Data and methods
Metadata for all images held in the Landsat archive were
acquired from the USGS Bulk Metadata Service.
10
Separate
metadata files were acquired for Landsat 13 MSS, Landsat
45 MSS, Landsat 45 TM, Landsat 7 ETM, and
Landsat 7 ETM(SLC-off). The metadata records include
a variety of attributes that vary by sensor. Attributes
common to all sensors used in this analysis included: unique
scene identification number (scene id), sensor, acquisition
date, Worldwide Reference System (WRS) path and row,
and cloud cover percentage (overall and by quadrant).
The WRS is a spatial index used for cataloging Landsat
data. The globe is partitioned into frames, indicating the
extent of each Landsat image, and these frames are defined
using paths (parallel to the ground track of the satellite,
northsouth) and rows (parallel to latitude). Landsat
satellites 13 used WRS-1, and all subsequent Landsat
satellites have used WRS-2. As the WRS-1 and WRS-2
systems differ, it was necessary to harmonize WRS-1
pathrows to WRS-2 pathrows. This was done via a spatial
overlay: digital geographic files for the WRS-1 and WRS-2
were acquired from the USGS
11
and the centroids (points)
of WRS-1 frames were overlaid on the WRS-2 frames
(polygons) and were assigned the corresponding WRS-2
Table 2. Distribution of archived Landsat images of Canada by jurisdiction and ecozone.
Location MSS TM ETMETMSLC-OFF TOTAL
Jurisdiction
Alberta 4 187 18 163 2 971 5 595 30 916
British Columbia 9 168 27 745 5 547 8 861 51 321
Saskatchewan 6 004 19 093 3 014 5 599 33 710
Manitoba 4 653 20 765 3 233 5 533 34 184
Ontario 19 392 44 122 6 504 13 643 83 661
Quebec 16 937 50 245 8 157 12 184 87 523
New Brunswick 2 661 3 152 631 1 268 7 712
Nova Scotia 3 255 2 878 694 1 200 8 027
Prince Edward Island 515 524 126 249 1 414
Newfoundland 10 696 10 119 2 634 3 508 26 957
Yukon 8 097 14 469 3 788 5 810 32 164
Northwest Territories 6 786 50 432 9 489 11 495 78 202
Nunavut 5 676 85 257 16 552 22 705 130 190
Ecozone
Arctic Cordillera 659 6 735 1 602 2 638 11 634
Atlantic Maritime 9 070 10 128 2 055 3 998 25 251
Boreal Cordillera 4 343 10 636 2 579 3 766 21 324
Boreal Plains 4 057 20 884 3 341 5 999 34 281
Boreal Shield East 18 703 30 440 5 513 9 289 63 945
Boreal Shield West 8 240 27 659 4 167 8 119 48 185
Hudson Plains 1 723 12 181 1 774 3 217 18 895
Mixedwood Plains 7 901 9 885 1 488 3 474 22 748
Montane Cordillera 4 191 14 374 2 386 4 456 25 407
Northern Arctic 6 323 73 281 14 621 19 086 113 311
Pacific Maritime 4 596 9 810 2 489 3 648 20 543
Semiarid Prairies 5 106 9 867 1 637 3 326 19 936
Southern Arctic 4 778 42 620 7 404 9 301 64 103
Subhumid Prairies 3 036 7 588 1 239 2 470 14 333
Taiga Cordillera 3 622 6 985 1 768 2 722 15 097
Taiga Plains 2 275 17 398 3 240 4 249 27 162
Taiga Shield East 7 867 18 824 3 269 4 129 34 089
Taiga Shield West 1 537 17 669 2 768 3 763 25 737
10
http://landsat.usgs.gov/metadatalist.php (downloaded June 21,
2013).
11
http://landsat.usgs.gov/worldwide_reference_system_WRS.php
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pathrow. Both WRS-1 and WRS-2 frames overlap, with
the amount of overlap increases with increasing latitude
(Wulder and Seemann, 2001). In cases where the centroid of
a WRS-1 image was found within multiple overlapping
WRS-2 frames, the WRS-1 centroid was arbitrarily assigned
to a single WRS-2 frame (pathrow). After harmonization
of WRS-1 and WRS-2, all metadata records were compiled
into a single database. Data records were subsequently
filtered to retain only those records corresponding to images
with WRS-2 pathrows over Canada’s terrestrial area,
acquired in the period from 1972 to 2012. In total, there
were 1224 unique WRS-2 pathrow locations that were
included in this analysis.
To further characterize the temporal aspects of the
Landsat archive of Canada, we considered a broad defini-
tion for the growing season to be 1 June to 30 September
(Julian dates 152 to 273), acknowledging that this range is
likely too broad for Canada’s northern ecosystems. We also
considered the temporal distribution of images relative to a
target date of 1 August (Julian date 213), which is
considered to be within the growing season of most regions
in Canada (McKenney et al., 2006). We considered two
different scenarios when querying the archive: long-term
ecosystem monitoring (i.e., assuming an image time series
approach) and a pixel-based image compositing scenario
whereby the best available pixel observation, determined
using a set of criteria such as day of year and cloud cover,
are used to build an image composite (e.g., Griffiths et al.,
2013), which can then be used to derive other information
products such as land cover and land cover change.
Landsat imagery was considered suitable for ecosystem
monitoring purposes if it was acquired after 1981 and
within 930 days of 1 August and had less than 10% cloud
cover. Likewise, imagery considered suitable for pixel-based
image compositing was also acquired after 1981 and within
930 days of 1 August but had less than 70% cloud cover.
The 70% threshold has been used previously for Landsat
pixel-based image compositing (Griffiths et al., 2013) and
also ensures a sufficient number of cloud-free ground
control point (GCP) locations to enable accurate geometric
correction. The 1981 threshold was used to exclude MSS
images from consideration in the two aforementioned
scenarios.
MSS era images were explicitly excluded from our
consideration of scenarios for ecosystem monitoring and
pixel-based image compositing for a number of reasons.
First, at the time of writing, the integration of MSS images
provided to the USGS by CCRS is ongoing, so any
interrogation of the archive prior to 1982 would have been
incomplete.
6
Second, MSS imagery does not have the same
spatial resolution as TM and ETMimagery (Table 1)so
special considerations are required to incorporate these data
into pixel-based image compositing or time series ap-
proaches. Third, MSS image products are known to have
lower geometric accuracy than TM and ETMand
therefore require additional processing prior to integration
into these analysis approaches (e.g., Pflugmacher et al.,
2012). Last, the MSS sensor lacks a band in the shortwave
infrared, which is an important spectral region for vegeta-
tion monitoring (Cohen and Goward, 2004).
The Landsat observation record of Canada
(1972

2012)
At the time of writing, there are a total of 605981 images
in the Landsat data archive of Canada. More than half of
these images (57%) are TM, followed by ETMSLC-off
(16%), MSS (16%), and ETM(10%). This contrasts with
the composition of the global USGS Landsat archive,
which has been documented to contain a greater propor-
tion of Landsat 7 ETM(and ETMSLC-off) data
relative to data from other Landsat sensors (Roy et al.,
2010a). This difference in archive composition may be
explained by sun angle limitations that are imposed on
Figure 2. (A) Distance (in days) from a target day of year of
1 August, and (B) cumulative distribution of archived Landsat
images (all sensors) relative to 1 August.
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Landsat 7 acquisitions. Unlike previous Landsat sensors,
Landsat 7 acquisitions are limited in areas with insufficient
sunlight and this limitation has the greatest impact on
acquisitions in high latitude regions such as Canada.
Minimum sun angle constraints for Landsat 7 acquisitions
are 158in the northern hemisphere and 58in the southern
hemisphere.
12
Figure 3. (A) Total number of Landsat images (all sensors) in the archive, by WRS-2 path
row and (B) total number of Landsat images (all sensors) from within the growing season
(1 June to 30 September).
12
http://landsat.usgs.gov/sun_angle_limits_landsat_acquisitions.
php
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The distribution of archived Landsat images for Canada,
by year and by sensor, is illustrated in Figure 1. In 2004 (the
year with the greatest number of Landsat images in the
archive), more than 32 000 images were acquired: 17 531 TM
and 14 652 ETMSLC-off images. Figure 1 indicates the
decline in MSS acquisitions from 1978 to 1982 when both
Landsat 2 and Landsat 3 had technical issues (Goward
et al., 2006), as well as the relatively short-term collection of
ETMprior to the aforementioned SLC failure in 2003. In
2000 there was a marked decrease in TM acquisitions over
Canada, with only 2110 TM images acquired in that year.
Table 2 shows the distribution of archived images by
provincial and territorial jurisdictions and by ecozone.
Although larger jurisdictions and ecozones will have more
pathrow locations (and thereby more images) as a function
of their larger size, northern jurisdictions and ecozones will
have more images as a function of overlap between Landsat
frames. Nunavut has the largest number of Landsat images,
with more than 130 000 in the archive, followed by Quebec
(87 523) and Ontario (83 661). Monitoring of northern
ecosystems can take advantage of significant image overlap
that is approximately 85% at 808latitude, versus 40%
overlap at Canada’s southern border with the United States
(Wulder and Seemann, 2001).
By design, more Landsat images are acquired during the
growing season than in the winter months, an operational
criteria that was fully realized with the advent of the LTAP
for Landsat 7 (Arvidson et al., 2006). Figures 2A and 2B
indicate the within-year distribution of images relative to a 1
August target date: approximately 55% of the archived
Landsat imagery of Canada was acquired within 930 days
of 1 August. The mean Julian day of acquisition of archived
images is 6 July, the median is 9 July, and the mode is 30
July.
The spatial distribution of all archived Landsat images
of Canada by WRS-2 pathrow centroids is shown in
Figure 3A, with southern areas of Canada generally having
more archived imagery per pathrow than more northern
areas. This is primarily a result of the greater number of
receiving stations in the south and their relative catchment
areas as well as the priority given for acquisition of the
conterminous United States and the aforementioned sun
angle limits imposed on Landsat 7 acquisitions. Figure 3B
shows the spatial distribution of archived images for the
growing season exclusively (1 June to 30 September), with
approximately 74% of pathrow locations in Canada’s terres-
trial areas having more than 200 archived images acquired
within this period for the years 19722012.
The quality of the archived images can be evaluated
using the cloud cover percentages reported in the metada-
ta. Methods to determine the percentage of cloud cover in
a given Landsat image have varied by mission: Landsat 15
MSS data were assessed manually, Landsat 45TMdata
were assessed using an Automated Cloud Cover Assess-
ment (ACCA) algorithm (Su, 1984), and Landsat 7 ETM
and ETMSLC-off data are assessed using a more
complex ACCA algorithm (Irish et al., 2006). Cloud cover
is reported overall for the image and separately for each
Figure 4. Distribution of archived Landsat images (all sensors) by their overall reported
proportion cloud cover.
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image quadrant. The distribution of Canada’s Landsat
archived images by their percent cloud cover is bi-modal
(Figure 4), with one-third of images having either less than
10% or more than 90% cloud cover. The relative distribu-
tion of archived images by month of the growing season is
also shown in Figure 4 and indicates that images acquired
in the month of July generally have a lower percent of
cloud cover than images acquired in the month of
September. Figure 5 shows the spatial distribution of TM
and ETMarchived images acquired within the growing
season that have less than 70% (Figure 5A) and less than
10% (Figure 5B) cloud cover, respectively. Overall, approxi-
mately 48% of archived Landsat images of Canada were
acquired within the growing season and of these, 59% have
less than 70% cloud cover, and 19% have less than 10%
cloud cover.
Tolerance for clouds and cloud shadows will depend on
the end user’s application. Pixel-based image compositing
approaches that seek to identify the best available pixel
within a certain temporal window, and which may consider
Figure 5. Spatial distribution of archived Landsat images (TM and ETMonly) according to
different cloud cover requirements.
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images from years prior or subsequent to a given target year
(e.g., Griffiths et al., 2013), will likely tolerate a much greater
proportion of cloud cover (Figure 5A). There is however a
practical limit to the amount of cloud cover that can be
tolerated for image compositing. For example, although
Landsat images with more than 90% cloud cover may be
Figure 6. For each pathrow location, the number of years with no images matching the
specified criteria for two different scenarios used to query the Landsat archive. (A) For a
pixel-based image compositing approach, images (TM and ETMonly) with B70% cloud
cover acquired after 1981 and within 930 days of a target date (1 August) are considered.
(B) For an ecosystem monitoring scenario, images (TM and ETMonly) with B10% cloud
cover acquired after 1981 and within 930 days of a target date (1 August). Forested ecosystems
are shown in green.
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considered useable from a compositing perspective, images
with this amount of cloud cover are difficult to geometri-
cally correct as clouds will obscure GCP locations, thereby
reducing the number of GCPs available for correction (Roy
et al., 2010b). In contrast, ecosystem monitoring applica-
tions may require cloud-free or almost cloud-free imagery
(Figure 5B). Similarly, applications that require knowledge
of conditions on a specific date, such as monitoring of
deforestation events, have a greater need for cloud-free
imagery.
These different cloud cover scenarios are further ex-
plored in Figure 6 where all non-MSS images acquired
after 1981 are considered. Both Figures 6A and 6B indicate
that there are temporal gaps in the archive for these two
scenarios. For a pixel-based image compositing scenario
whereby less than 70% cloud cover and a target date of 1
August 930 days are considered, 60% of the Landsat
pathrow locations are missing five or fewer years of data
(Figure 6A). When combined with the results presented in
Figure 5A for the overall number of images acquired, it
would appear that the Landsat archive of Canada is
capable of supporting a pixel-based image compositing
approach for much of Canada’s terrestrial area. For an
ecosystem monitoring scenario, whereby images likewise
must be acquired within 930 days of 1 August, but with
less than 10% cloud cover, Figure 6B indicates that only 2%
of Landsat pathrow locations are missing five or fewer
years of data. The mean and median number of years with
missing data for this scenario was 17, with the only
Landsat pathrow locations that satisfy the scenario’s
criteria being located in the Prairies Ecozone (with one
exception in southern Ontario for path 17, row 29).
However, if the acquisition date for this scenario is
expanded to include our broader definition of the growing
season (1 June to 30 September), some potential ecosystem
monitoring locations can be identified within the forested
ecosystems of Canada: Figure 7 indicates that with this
broader date range, 18% of Landsat pathrow locations
have five or fewer years of missing data. The cumulative
frequency distributions for WRS-2 pathrow locations for
all scenarios (Figure 8) illustrate the capacity of the
Landsat observation record of Canada to support both
time series and pixel-based image compositing approaches.
For all scenarios, the goal is to minimize the number of
years of missing data, and Figure 8 shows that the more
relaxed cloud cover constraint associated with the pixel-
based image compositing scenario would result in fewer
years of missing data and greater image availability for
subsequent analyses.
Conclusions
With open access to the Landsat data archive, reconstruc-
tion of the history of Canada’s terrestrial ecosystems and
related dynamics is increasingly possible. Knowledge of
prior conditions and trends can inform expectations, aid in
Figure 7. For each pathrow location, the number of years with no images matching the
specified criteria if the temporal constraint for an ecosystem monitoring scenario (see Figure
6B) is expanded from 1 August 930 days to the growing season (1 June to 30 September).
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parameterizing models, and support the identification of
change events. The number and variety of scientific oppor-
tunities that could be pursued with the freely available data
provided by the Landsat archive are limitless. The spatial,
temporal, and cloud cover characteristics of the Landsat
archive for Canada, as documented herein, indicate that
there is a rich repository of quality imagery available that
can support a broad range of methods and approaches,
including pixel-based image compositing and time series
analyses for long-term ecosystem monitoring.
Acknowledgements
This research was undertaken as part of the ‘‘National
Terrestrial Ecosystem Monitoring System (NTEMS):
Timely and detailed national cross-sector monitoring for
Canada’’ project jointly funded by the Canadian Space
Agency (CSA) Government Related Initiatives Program
(GRIP) and the Canadian Forest Service (CFS) of Natural
Resources Canada.
References
Arvidson, T., Gasch, J., and Goward, S.N. 2001. Landsat 7’s long-term
acquisition plan*an innovative approach to building a global image
archive. Remote Sensing of Environment, Vol. 78, No. 12, pp. 1326.
doi: 10.1016/S0034-4257(01)00263-2.
Arvidson,T.,Goward,S.,Gasch,J.,andWilliams,D.2006.Landsat-7
long-term acquisition plan: development and validation. Photo-
grammetric Engineering and Remote Sensing,Vol.72,No.10,
pp. 11371146. doi: 10.14358/PERS.72.10.1137.
Bolch, T., Menounos, B., and Wheate, R. 2010. Landsat-based inventory of
glaciers in western Canada, 19852005. Remote Sensing of Environment,
Vol. 114, No. 1, pp. 127137. doi: 10.1016/j.rse.2009.08.015.
Cohen, W.B., and Goward S.N. 2004. Landsat’s role in ecological
applications of remote sensing. BioScience, Vol. 54, No. 6, pp. 535
545. doi: 10.1641/0006-3568(2004)054[0535:LRIEAO]2.0.CO;2.
Chen, W., Russel, D.E., Gunn, A., Croft, B., Chen, W.R., Fernandes, R.,
Zhao, H., Li, J., Zhang, Y., Koehler, K., Olthof, I., Fraser, R.H.,
Leblanc, S.G., Henry, G.R., White, R.G., and Finstad, G.L. 2013.
Monitoring habitat condition changes during winter and pre-calving
migration for Bathurst Caribou in northern Canada. Biodiversity, Vol.
14, No. 1, pp. 3644. doi: 10.1080/14888386.2012.705110.
Draeger, W.C., Holm, T.N., Lauer, D.T., and Thompson, R.J. 1997. The
availability of Landsat data: past, present, and future. Photogrammetric
Engineering and Remote Sensing, Vol. 63, No. 7, pp. 869875.
Fraser, R.H., and Pouliot, O.D. 2009. Monitoring land cover change
and ecological integrity in Canada’s National Parks. Remote Sensing
of Environment, Vol. 113, No. 7, pp. 13971409. doi: 10.1016/j.rse.2008.
06.019.
Fraser, R.H., Olthof, I., Carrie`re, M., Deschamps, A., and Pouliot, D. 2011.
Detecting long-term changes to vegetation in northern Canada using the
Landsat satellite image archive. Environmental Research Letters, Vol. 6,
No. 4, pp. 19. doi: 10.1088/1748-9326/6/4/045502.
Figure 8. Cumulative frequency distribution of WRS-2 pathrow locations for number of
years with no images matching the specified criteria for the ecosystem monitoring or pixel-
based image compositing scenarios considered.
Canadian Journal of Remote Sensing / Journal canadien de te
´le
´de
´tection
#2014 Government of Canada 465
Downloaded by [Canadian Forest Service] at 14:03 22 September 2015

Fuller, R.M., Groom, G.B., and Wallis, S.M. 1994. The availability
of Landsat TM images of Great Britain. International Journal of
Remote Sensing, Vol. 15, No. 6, pp. 13571362. doi: 10.1080/014311
69408954170.
Furberg, D., and Ban, Y. 2012. Satellite monitoring of urban sprawl and
assessment of its potential environmental impact in the Greater Toronto
Area between 1985 and 2005. Environmental Management, Vol. 50, No.
6, pp. 10681088. doi: 10.1007/s00267-012-9944-0.
Griffiths, P., van der Linden, S., Kuemmerle, T., and Hostert, P. 2013. A
pixel-based Landsat compositing algorithm for large area land cover
monitoring. Journal of Selected Topics in Applied Earth Observations and
Remote Sensing, Vol. 238, pp. 114.
Goward, S., Arvidson, T., Williams, D., Faundeen, J., Irons, J., and Franks, S.
2006. Historical record of Landsat global coverage: Mission operations,
NSLRSDA, and international cooperator stations. Photogrammetric
Engineering and Remote Sensing, Vol. 72, No. 10, pp. 11551169. doi:
10.14358/PERS.72.10.1155.
Irish, R.R., Barker, J.L., Goward, S.N., and Arvidson, T. 2006. Character-
ization of the Landsat 7 ETMAutomated Cloud-Cover Assessment
(ACCA) algorithm. Photogrammetric Engineering and Remote Sensing,
Vol. 72, No. 10, pp. 11791188. doi: 10.14358/PERS.72.10.1179.
Irons, J.R., Dwyer, J.L., and Barsi, J.L. 2012. The next Landsat satellite: the
Landsat Data Continuity Mission. Remote Sensing of Environment, Vol.
122, pp. 1121. doi: 10.1016/j.rse.2011.08.026.
Ju, J., and Roy, D.P. 2007. The availability of cloud-free Landsat ETM
data over the conterminous United States and globally. Remote Sensing
of Environment, Vol. 112, pp. 11961211. doi: 10.1016/j.rse.2007.08.011.
Kline, K. 2013. Landsat operations project report. Landsat Science Team
Meeting, 12 February 2013, Buelton, CA. Available online: http://
landsat.usgs.gov/documents/Kline%20-%20Landsat%20Status%20-%
20LST%202-2013.pdf
Kovalskyy, V., and Roy, D.P. 2013. The global availability of Landsat 5
TM and Landsat 7 ETMland surface observations and implica-
tions for global 30 m Landsat data product generation. Remote
Sensing of Environment,Vol.130,pp.280293. doi: 10.1016/j.rse.
2012.12.003.
Maxwell, S. 2004. Filling Landsat ETMSLC-off gaps using a segmenta-
tion model approach. Photogrammetric Engineering and Remote Sensing,
Vol. 70, No. 10, pp. 11091111.
Maxwell, S.K., Schmidt, G.L., and Storey, J.C. 2007. A multi-scale
segmentation approach to filling gaps in Landsat ETMSLC-off
images. International Journal of Remote Sensing, Vol. 28, No. 23, pp.
53395356. doi: 10.1080/01431160601034902.
McKenney, D., Pedlar, J.H., Papadopol, P., and Hutchinson, M.F. 2006.
The development of 19012000 historical monthly climate models for
Canada and the United States. Agricultural and Forest Meterology, Vol.
138, pp. 6981. doi: 10.1016/j.agrformet.2006.03.012.
McManus, K.M., Morton, D.C., Masek, J.G., Wang, D., Sexton, J.O,
Nagol, J.R., Ropars, P., and Boudreau, S. 2012. Satellite-based evidence
for shrub and graminoid tundra expansion in northern Quebec from
1986 to 2010. Global Change Biology, Vol. 18, No. 7, pp. 23132323. doi:
10.1111/j.1365-2486.2012.02708.x.
National Research Council. 2013. Landsat and Beyond: Sustaining and
Enhancing the Nation’s Land Imaging Program. Washington DC: The
National Academies Press. pp. 73.
Olthof, I., Latifovic, R., and Pouliot, D. 2009. Development of a circa 2000
land cover map of northern Canada at 30 m resolution from Landsat.
Canadian Journal of Remote Sensing, Vol. 35, No. 2, pp. 152165. doi:
10.5589/m09-007.
Pasher, J., Seed, E., and Duffe, J. 2013. Development of boreal ecosystem
anthropogenic disturbance layers for Canada based on 2008 to 2010
Landsat imagery. Canadian Journal of Remote Sensing, Vol. 39, No. 1,
pp. 4258. doi: 10.5589/m13-007.
Pflugmacher, D., Cohen, W.B., and Kennedy, R.E. 2012. Using Landsat-
derived disturbance history (19722010) to predict current forest
structure. Remote Sensing of Environment, Vol. 122, pp. 146165. doi:
10.1016/j.rse.2011.09.025.
Roy, D.P., Ju, J., Mbow, C., Frost, P., and Loveland, T. 2010a. Accessing
free Landsat data via the Internet: Africa’s challenge. Remote Sensing
Letters, Vol. 1, pp. 111117. doi: 10.1080/01431160903486693.
Roy, D.P., Ju, J., Kline, K., Scaramuzza, P.L., Kovalskyy, V., Hansen, M.,
Loveland, T.R., Vermote, E., and Zhang, C. 2010b. Web-enabled
Landsat Data (WELD): Landsat ETMcomposited mosaics of the
conterminous United States. Remote Sensing of Environment, Vol. 114,
pp. 3549. doi: 10.1016/j.rse.2009.08.011.
Schroeder, T.A., Wulder, M.A., Healey, S.P., and Moisen, G.G.
2011. Mapping wildfire and clearcut harvest disturbances in
boreal forests with Landsat time series data. Remote Sensing of
Environment, Vol. 115, No. 6, pp. 14211433. doi: 10.1016/j.rse.2011.
01.022.
Skakun, R.S., Wulder, M.A., and Franklin, S.E. 2003. Sensitivity of
Thematic Mapper Enhanced Wetness Difference Index to detect moun-
tain pine beetle red-attack damage. Remote Sensing of Environment,
Vol. 86, pp. 433443. doi: 10.1016/S0034-4257(03)00112-3.
Su, J.J. 1984. Enhanced ACCA Algorithm. Space Imaging Corporation
Technical Memo IT81-LSD-SA&E Memo. pp. 274.
Tenant, C., Menounos, B., Wheate, R., and Clague, J.J. 2012. Area change
in glaciers in the Canadian Rocky Mountains, 1919 to 2006. Cryosphere,
Vol. 6, No. 6, pp. 15411552. doi: 10.5194/tc-6-1541-2012.
Townshend, J.R.G., and Justice, C.O. 1988. Selecting the spatial resolution
of satellite sensors required for global monitoring of land transforma-
tions. International Journal of Remote Sensing, Vol. 9, No. 2, pp. 187
236. doi: 10.1080/01431168808954847.
Valeria, O., Laamrani, A., and Beaudoin, A. 2012. Monitoring the state of
a large boreal forest region in eastern Canada through the use of
multitemporal classified satellite imagery. Canadian Journal of Remote
Sensing, Vol. 38, No. 1, pp. 91108. doi: 10.5589/m12-014.
White, J.C., Wulder, M.A., Gomez, C., and Stenhouse, G. 2011. A history
of habitat dynamics: Characterizing 35 years of stand replacing
disturbance. Canadian Journal of Remote Sensing,Vol.37,No.2,
pp. 234251. doi: 10.5589/m11-034.
Williams, D.L., Goward, S., and Arvidson, T. 2006. Landsat: Yesterday,
Today, and Tomorrow. Photogrammetric Engineering and Remote Sensing,
Vol. 72, No. 10, pp. 11711178. doi: 10.14358/PERS.72.10.1171.
Woodcock, C.E., Allen, R., Anderson, M., Belward, A., Bindschadler, R.,
Cohen, W., Gao, F., Goward, S.N., Helder, D., Helmer, E., Nemani, R.,
Oreopoulos, L., Schott, J., Thenkabail, P.S., Vermote, E.F., Vogelmann,
J., Wulder, M.A., and Wynne, R. 2008. Free access to Landsat imagery.
Science, Vol. 320, p. 1011. doi: 10.1126/science.320.5879.1011a.
Vol. 39, No. 6, December/de
´cembre 2013
466 #2014 Government of Canada
Downloaded by [Canadian Forest Service] at 14:03 22 September 2015

Wulder, M.A., and Seemann, D. 2001. Spatially partitioning Canada with
the Landsat Worldwide Referencing System. Canadian Journal of
Remote Sensing, Vol. 27, No. 3, pp. 225231.
Wulder, M.A., White, J.C., Cranny, M., Hall, R.J., Luther, J.E., Beaudoin,
A., Goodenough, D.G., and Dechka, J.A. 2008. Monitoring Canada’s
Forests. Part 1: Completion of the EOSD land cover project. Canadian
Journal of Remote Sensing, Vol. 34, No. 6, pp. 549562. doi: 10.5589/
m08-066.
Wulder, M.A., Masek, J.G., Cohen, W.B., Loveland, T.R., and Woodcock,
C.E. 2012. Opening the archive: How free data has enabled the science
and monitoring promise of Landsat. Remote Sensing of Environment,
Vol. 122, pp. 210. doi: 10.1016/j.rse.2012.01.010.
Canadian Journal of Remote Sensing / Journal canadien de te
´le
´de
´tection
#2014 Government of Canada 467
Downloaded by [Canadian Forest Service] at 14:03 22 September 2015