[Personnel: Last_Name='SERVICES', Middle_Name='CLIENT', First_Name='GEOGRATIS']
Canada-wide 1-km AVHRR Composite Maps based on GEOCOMP Data enhanced with ABC3v2 SoftwareEntry ID: Canada_GeoGratis_DataABC3Softwa
Abstract: *** NOTE: See note at end if using Windows or NT to uncompress files. The file
format of the data is PCI .pix format. ***
Local Area Coverage (LAC) data collected by the Canada Centre for Remote
Sensing (CCRS) from the Advanced Very High Resolution Radiometer (AVHRR)
instrument on board the National Oceanic and Atmospheric Administration (NOAA)
11 and 14 satellites were used in the AVHRR ... Geocoding and Compositing (GeoComp)
system. This system operating at the Manitoba Remote Sensing Centre (MRSC) in
Winnipeg, Manitoba generated Canada-wide 10-day composite images at 1-km
spatial resolution. The composite images cover the growing season from April 11
to October 31 for 1993 to 1999 (20 composite maps per year or 140 in total). In
GeoComp, the maximum value of the Normalized Difference Vegetation Index (NDVI)
computed from the top-of-atmosphere (TOA) radiance data was used to composite
images with reduced radiometric artifacts. The GeoComp 10-day composite data
were then reprocessed using the Atmospheric, Bidirectional and cloud
Contamination Corrections of CCRS version 2 (ABC3v2) software system at CCRS to
apply a refined sensor calibration and other radiometric product improvements.
The resulting data set are as free of residual errors as possible, from effects
not representing the surface under uniform illumination and viewing conditions.
Consequentialy, they approximate nadir-viewed composite images obtained under
cloud-free conditions during the growing season.
The resulting 1-km resolution composite maps include: a contaminated pixel
mask; the smoothed surface reflectance in AVHRR bands 1, 2 and 3 corrected for
bidirectional reflectance function (BRDF); the smoothed Normalized Difference
Vegetation Index (NDVI) computed from surface reflectance; the relative azimuth
angle; the relative date; the satellite zenith angle; the sun zenith angle; and
the smoothed surface temperature corrected for emissivity effects. The data
layers and the underlying data processing are described in detail in the data
set description document ABC3v2.txt (ASCII text) or ABC3v2.doc (MS Word
document) available from CCRS. The data layers, originally generated in Lambert
Conic Conformal projection have been reprojected into geographic
(latitude/longitude) coordinate system. Both projections use the NAD83 datum.
The ABC3v2 output products are used for various land cover, environmental
monitoring and climate change studies. Specialized products such as detailed
land cover and Leaf Area Index (LAI) maps are required for land cover studies.
Albedo maps based on ABC3 data are used as input to the solar radiation budget
in global climate change studies.
The ABC3v2 reprocessing of GeoComp 10-day composite data (elaborated in the
following paragraphs) included: recalibration of channel 1 and 2 data;
atmospheric corrections of channel 1 and 2 data; creation of a contaminated
pixel mask; computation of surface temperature from channel 4 and 5 brightness
temperature; computation of channel 3 surface reflectance; BRDF correction of
channel 1, 2 and 3 data; and seasonal interpolation of data to replace missing
or contaminated pixels.
As part of the recalibration, an updated radiometric calibration for AVHRR
channels 1 and 2 was applied in ABC3v2 to replace the calibration applied in
GeoComp based on pre-launch or earlier calibration coefficients. The
calibration gain and offset coefficients were computed using Piece Wise Linear
(PWL) calibration coefficients to describe the temporal post launch radiometric
degradation of the sensor as part of a definitive calibration update for NOAA
14 by CCRS (URL
http://registry.gsdi.org/viewrecord.php?rec=746). The NOAA 11
PWL calibration coefficients were defined in the publication by Cihlar and
Teillet (Cihlar, J. and P.M. Teillet. 1995. Forward piecewise linear
calibration model for quasi-real time processing of AVHRR data. Canadian
Journal of Remote Sensing. Volume 21, pages: 22-27).
An atmospheric correction using the Simplified Method for Atmospheric
Correction (SMAC) (Rahman, H., and G. Dedieu. 1994. SMAC: a simplified method
for the atmospheric correction of satellite measurements in the solar spectrum.
International Journal for Remote Sensing, Volume 15, pages: 123-143) was
applied to the top-of-atmosphere radiance data in channels 1 and 2 to generate
surface reflectance. In addition to nominal values of atmospheric parameters
used in SMAC, ancillary data sets (image maps) generated by CCRS of monthly
mean ozone, ten-day composite water vapour and seasonal average barometric
pressure were used. The solar zenith angle corrected for local topography was
used to compute the diffuse solar illumination. The recommended aerosol optical
depth at 550 nm of 0.06 for clear days was used based on the AEROsols of CANada
(AEROCAN) sunphotometer network data (Fedosejevs, G., N.T. O'Neill, A. Royer,
P.M. Teillet, A.I. Bokoye and B. McArthur. 2000. Aerosol Optical Depth for
Atmospheric Correction of AVHRR Composite Data. Canadian Journal for Remote
Sensing, Volume 26, Number 4, pages: 273-284).
The contaminated pixel mask was produced with the Cloud Elimination from
Composites using Albedo and NDVI Trend (CECANT) procedure by (Cihlar, J., 1996.
Identification of contaminated pixels in AVHRR composite images for studies of
land biosphere. Remote Sensing of Environment. Volume 56, pages: 149-163).
CECANT was developed to identify the contaminated pixels where the surface
vegetation, bare soil, rock or open water is obscured by clouds, partial
(sub-pixel) clouds, cloud shadows, smoke or other heavy aerosols, snow or ice.
The semi-empirical method by Coll et al. was employed in ABC3v2 to determine
the surface temperature from the brightness temperature in AVHRR channels 4 and
5 using the split window method and a separate accounting for atmospheric
attenuation and soil emissivity (Coll, C., V. Caselles, J.A. Sobrino, and E.
Valor. 1994. On the atmospheric dependence of the split-window equation for
land surface temperature. International Journal for Remote Sensing. Volume 15,
Number 1, pages: 105-122).
Channel 3 radiance contains a thermal emissive component and a solar reflective
component during the day. While channel 3 contains noisy data, CCRS has
developed a method to retrieve the solar reflective component. The surface
reflectance in channel 3 is computed from TOA radiance in channel 3 and channel
5 brightness temperature using an empirical fit.
For the BRDF correction, the Roujean model was modified to characterize the
seasonal BRDF effect for each land cover type. The Canada Land Cover Map was
developed at CCRS from a classification of 1995 AVHRR data (Cihlar, J., and J.
Beaubien.1998. Land Cover of Canada 1995 Version 1.1. Digital data set
documentation, Natural Resources Canada, Ottawa, Ontario). This map and user
document are available on the CCRS ftp site
ftp2.ccrs.nrcan.gc.ca/ftp/ad/EMS/landcover95. A further modification of
Roujean's BRDF model introduced NDVI and the hot spot effect (Latifovic, R., J.
Cihlar, and J. Chen. 2002. A comparison of BRDF models for the normalisation of
satellite optical data to a standard sun-target-sensor geometry. IEEE
Transactions on Geoscience and Remote Sensing). The BRDF correction models
generated for AVHRR channels 1, 2 and 3 were used to normalize all the surface
reflectances to a sun zenith angle of 45 degrees and nadir viewing angle.
Pixels denoted as bad for various reasons in the contaminated pixel mask were
interpolated seasonally for the BRDF-corrected channels 1, 2, 3, NDVI and
surface temperature composite map image layers (provided that at least three
uncontaminated composite period values were available within one year). A
polynomial fit was used to extrapolate the end points for all image layers
except surface temperature. An additional temporal smoothing for NDVI seasonal
curve is based on a sliding filter on the interpolated NDVI from 5 consecutive
composite periods centered on the date of interest where the highest and lowest
values are dropped and the remaining three are averaged.
Each of the 35 (final and intermediate) product data layers created by the
ABC3v2 software has an associated metadata file (according to GeoComp-n
standards) in ASCII readable format. The full data set with metadata files can
be acquired by contacting CCRS.
***Note: If you use Winzip to unzip the data, please try the following:
Since the data sets are packaged using UNIX tools, they are best served for
UNIX platforms. If you use windows zip to unzip them, you need to set your
winzip's properties to make them work. You may try the following: Launch
Winzip, select Options menu, select Configuration, and click Miscellaneous tab.
In the other category, if the check box (second one) for TAR file smart CR/LF
conversion is checked, uncheck it.The ABC3 Canada-wide 1-km resolution AVHRR
composite maps (Version 2) were produced as part of the CCRS Northern Biosphere
Observation and Modelling Experiment (NBIOME). NBIOME co-ordinated the
participation of a Canadian research team in the international Earth Observing
System (EOS) to develop methods for post-processing of AVHRR seasonal composite
maps to produce derived products with national coverage. The ABC3v2 output
product layers are used at CCRS in land cover and climate change studies; and
are used to generate various non-remote sensing products such as Leaf Area
Index (LAI) and Net Primary Productivity (NPP). These data layers can be used
directly by resource managers to study large scale changes in land cover types
and land use practices. Natural disturbances such as forest fires can alter the
land cover. Anthropogenic changes caused by clear cutting of forests or
industrial and residential development are significant in the long-term. The
composite products can be used to evaluate seasonal behaviours of land cover
types. These data layers and derived products can be used in radiation budget
and climate studies.
Data Set Citation
Dataset Originator/Creator: Government of Canada, Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing
Dataset Title: Canada-wide 1-km AVHRR Composite Maps based on GEOCOMP Data enhanced with ABC3v2 Software
Dataset Release Date: 20000804
Dataset Release Place: Ottawa, Ontario, Canada
Dataset Publisher: Government of Canada, Natural Resources Canada, Earth Sciences Sector, Canada Centre for Remote Sensing
Start Date: 1993-04-11Stop Date: 1999-10-31
ISO Topic Category
Access Constraints none
Use Constraints Copyright Canada Centre for Remote Sensing, Natural Resources Canada in papers,
posters or presentation material
Data Set Progress
Role: TECHNICAL CONTACT
Email: josef.cihlar at ccrs.nrcan.gc.ca
588 Booth Street, Room 423
Province or State: Ontario
Postal Code: K1A 0Y7
Creation and Review Dates
DIF Creation Date: 2002-08-21
Last DIF Revision Date: 2009-03-16
Future DIF Review Date: 2006-06-18