National Scale Satellite Climate Data records of Canada's Landmass and Ecosystems

Activity Rationale

Systematic long-term observations of the Earth system are required to improve our understanding of climate and climate change impacts on Canada’s landmass. Satellite observations are a key source of data that provide a wealth of information about environmental conditions and ecosystem dynamics. This activity develops methods to transform satellite observations into useable terrestrial products and analyses long-term time series to determine climate trends and impacts of climate changes on Canada’s lands.

Leader: Alexander Trichtchenko

The Topic

Recent advances in space technology have given the scientific community a much better opportunity to characterize the impact of climate variability and change. In the last decade a number of new and continuing missions with improved technical characteristics were launched. Among these missions, the MODerate Resolution Imaging Spectroradiometer (MODIS) is the most advanced sensor available for large-scale terrestrial applications. Two MODIS instruments are currently functioning onboard NASA’s TERRA and AQUA satellites. Each MODIS instrument provides global coverage every 1-2 days and observes 36 spectral bands ranging from visible to infrared wavelengths. Seven spectral bands (B1 to B7) are specifically designed for land applications. Two of the bands (B1 and B2) acquire imagery at 250-meter spatial resolution (downward angle), five (B3 to B7) at 500-meter resolution, and the remaining 29 at 1 km resolution.

Scientists from the Canada Centre for Remote Sensing (CCRS) have produced unique MODIS image enhancement technology that allows imagery of the entire country to be generated for all seven land bands (B1-B7) at 250m spatial resolution. This technology uses special image fusion and normalization techniques. An example of MODIS imagery at 250m spatial resolution over Canada for various seasons is shown to the right.

The longest satellite time series are available from the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA (National Oceanic and Atmospheric Administration) satellites. The AVHRR sensors observe the Earth in five spectral bands (two optical and three thermal) at 1-km spatial resolution.  Time series with complete coverage of Canada from AVHRR/NOAA are available from 1985. The figure to the right shows an example of Canada-wide clear-sky composites for July 1-10 for 20 years. It also shows trends in Hudson Bay sea ice cover indicating that in recent years, ice has started to clear out earlier in the summer.

To quantify environmental change for impact assessments, this activity develops methodology and technology for generating thematic climate data records (TCDRs). While coverage of Canada by these sensors is available on a daily basis, the images have to be processed according to international standards specified by the Global Climate Observing System and Committee on Earth Observing Satellites in order to be useful as environmental or climate data records and to be comparable with products from other countries.

The primary focus of the research is on surface reflectance and albedo, land cover, vegetation property mapping, and sea and lake ice phenology, parameters that characterize the potential climate change impacts on Canada's landscapes and ecosystems.

Results

The following section describes some of the achievements this activity has attained so far and provides information about produced datasets. For more detailed information and results, please contact Alexander Trichtchenko or visit the Canada Centre for Remote Sensing (CCRS) website. For explanations of technical terms and concepts, please visit the Outreach Materials available from CCRS.

Some datasets are available on FTP servers (ftp://), which is a network protocol used to exchange files over networks. To view the FTP sites in Windows Explorer, click Page (top right-hand side of web browser), and then click Open FTP Site in Windows Explorer.

Surface Reflectance and Albedo

Reflectance is a key remote sensing measurement that captures details about how radiation (such as light) bounces off a surface. Features on the Earth’s surface reflect radiation in different ways. Information about how the reflection happens, how much radiation is reflected, and how the radiation changes provides details about the target that caused the reflection.

As a contribution to the Canadian International Polar Year (IPY) Program and with support from the Canadian Space Agency through the Government Related Initiatives Program (GRIP), this activity generated the first-ever satellite circumpolar clear-sky mosaics from MODIS/TERRA data at 250m-spatial resolution. The examples for late summer for 2000-2008 are shown below. Note the dramatic reduction in the area of sea ice in 2007 and 2008 compared to other years. Data can be accessed at ftp://ftp.ccrs.nrcan.gc.ca/ad/CircumpolarMap.

MODIS/Terra clear-sky composites over the Arctic circumpolar region in late summer (2000-2008) at 250-m saptial resolution. (Trishchenko, Luo, Khlopenkov, Park, and Wang, 2009)

Clear-sky composites of MODIS land bands at 250-m spatial resolution over Canada and Arctic circumpolar regions have also been produced for March 2000 to December 2008 with improved data processing technology (Luo, Trishchenko, Khlopenkov, 2008). Due to the large volume of data, new MODIS mosaics over Canada and Arctic region are not placed in the public domain, but can be made available upon request from Alexander Trichtchenko. The previous version can be accessed at http://geogratis.cgdi.gc.ca/geogratis/en/collection/detail.do?id=32545.
Canada-wide Bidirectional Reflectance Distribution Functions (BRDF) based on MODIS observations from March 2000 to March 2006 can be accessed at http://geogratis.cgdi.gc.ca/geogratis/en/collection/detail.do?id=25509.

Since the early 1980’s satellite observations of Canada’s lands have been obtained from the AVHRR sensor. New advances in data processing have provided an opportunity to gain more information from historical records. A fifth generation AVHRR processing system is being developed and used to re-process the AVHRR 1km Canadian archive with improved accuracy of pixel geolocation and radiometric calibration. This new system is called CAPS – Canadian AVHRR Processing System (Kjhlopenkov, Trishchenko, Luo, Komarov, 2009). Due to the large volume of data, the AVHRR datasets are not placed in public domain, but can be made available upon request from Alexander Trichtchenko

The state of ice coverage over the Northwest Passage in the beginning of September from combined AVHRR-MODIS time series. The images indicate less ice and more open water in the Northwest Passage during recent years.

Albedo refers to the fraction of incident solar radiation that is reflected by the Earth's surface, which is an important concept in climate studies. Albedo determines the amount of energy that is absorbed by the ground, and therefore the amount of energy that is available to evaporate water and to heat the ground and the lower atmosphere. Comparison of 17 Global Climate Model (GCM) results from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report data archive and satellite albedo trends showed that satellite observations point to significant negative albedo trends in summer months while most GCM show neutral trends. Negative albedo trends lead to increased warming in the Arctic because more radiation is absorbed by the Earth’s surface. The estimated total radiative forcing is ~3-5 W/m-2 during 15 years, which exceeds the total forcing due to greenhouse gases GHG build-up (2.5 W/m-2) over last 150 yrs. This effect may potentially be increasing due to positive feedback. None of current GCM models captured this albedo darkening effect. (Wang, Trishchenko, Khlopenkov, Davidson, JGR, 2006).

Comparison of trends in summer surface albedo over Canada derived from satellite observations and climate models. Unlike the model results, satellite observations show significant darkening trend which can likely be attributed to the impact of a warmer climate on vegetation and cryosphere (Wang, Trishchenko, Khlopenkov, and Davidson, 2006).

Land Cover

Stakeholders in sectors such as forestry, agriculture, and landscape management are interested in land cover mapping to quantify existing resources and facilitate good decision-making for the sustainable use of Canada’s resources. In collaboration with the Earth Science Sector (ESS) program “Understanding Canada’s Landmass and Coasts from Space”, advances in land cover mapping include the following:

• Land cover products for 1985-2005 have been developed for five-year intervals using satellite data from AVHRR and SPOT VEGETATION sensors. Products can be accessed at ftp://ftp.ccrs.nrcan.gc.ca/ad/NLCCLandCover/LandcoverCanada1985_2005_1KM   

Examples of Canada’s land cover time series for 1985-2000 are shown below.

Examples of Canada's land cover time series for 1985-2000.

• A land cover map of North America was developed with the United States Geological Survey (USGS) at 1km resolution, which contributed to the Global Land Cover 2000 project led by the Joint Research Centre of the European Commission. Products can be accessed at ftp://ftp.ccrs.nrcan.gc.ca/ad/EMS/Landcover2000/.

Land cover of North and Central America for 2000 produced as part of the Global Land Cover 2000 Project led by the Joint Research Centre of the European Commission. Larger image

Vegetation Property Mapping

Fraction of Absorbed Photosynthetically Active Radiation (fAPAR) measures photosynthetic activity in plants and provides information about the presence and productivity of vegetation. By mapping fAPAR, information can be gained about the strength and location of carbon sinks on land, which is important for evaluating Canada’s net carbon emissions. fAPAR cannot be directly measured by satellite sensors, so the EALCO model (Ecological Assimilation of Land and Climate Observations), a model that simulates interactions among ecosystem and climate processes, (see Developing Earth Observation-based Ecosystem Modelling Tools for the Assessment of Climate Change Impacts) is integrated with satellite observations to obtain this product.

fAPAR products have been improved by enhancing the data quality of satellite observations and the EALCO model. This product is being produced from satellite observations as far back as 1985, and is being validated with field measurements.

Leaf Area Index (LAI) is an important biological parameter because it represents the land-based surface responsible for absorbing carbon and provides a remote sensing signal by interacting with solar radiation. New approaches have been developed to retrieve LAI from satellites and to monitor LAI in the field by non-destructive methods using digital hemispheric cameras and hand-held radiometers. The LAI mapping is conducted in collaboration with the ESS program “Understanding Canada’s Landmass and Coasts from Space”.

LAI data for 1998-2004 derived from the SPOT/VGT sensor can be accessed at http://geogratis.cgdi.gc.ca/download/EO_Data/SPOTVGT_LAI/

Lake ice phenology

An example of the trend of ice break-up timing for four Canadian lakes, spatially distributed from south to north, is shown to the right. The results were produced using AVHRR data processed at the Canada Centre for Remote Sensing (CCRS). The results indicate generally negative trends in ice cover, with earlier ice melt dates and shorter ice cover period.

Trend of ice break-up timing for four Canadian lakes, spatially distributed from south to north. (Latifovic, Pouliot, 2007).

Snow Cover

As part of Canada’s contributions to the International Polar Year (IPY), CCRS scientists are working on producing historical daily snow cover information from satellite AVHRR observations to gain knowledge about how snow cover has changed over time. Daily snow cover maps have been produced over the Arctic region of northern hemisphere for 1982-2004 at 5km resolution from the AVHRR composites generated by the NOAA/NASA Polar Pathfinder Program. Snow mapping is being conducted over the North-western Hemisphere (1983-2005) at 1km resolution.

Daily estimates of snow cover over land for the Northern Hemisphere from 1982-2004 derived from NOAA AVHRR Polar Pathfinder Satellite Imagery are available at ftp://ftp.ccrs.nrcan.gc.ca/ad/IPY/snowapp. An example is shown to the right.

Study Data

Links to available datasets are provided in the text above and in the ERCC Data portal. To access more geospatial data from the Earth Science Sector (ESS), please visit the GeoGratis data portal.

Publications

Please note that subscriptions may be required to access some articles. To request a copy of publications, or for any more information, please contact Alexander Trichtchenko.

• Check for more recent publications in GEOSCAN, the publications database of the Geological Survey of Canada and the Canada Centre for Remote Sensing.

Abuelgasim, A.A.; R.Fernandes, S.G.Leblanc, 2006. Evaluation of national and global LAI products derived from optical remote sensing instruments over Canada. IEEE Transactions Geoscience and Remote Sensing, 44, 1872-1884.

Alcaraz-Segura, D., E.Chuvieco, H.E.Epstein, E.S.Kasischke, A.P.Trishchenko, 2009. The remotely-sensed greening versus browning of the North American boreal forest. Global Change Biology. In press (as of April 2009).

Baret, F., J.T.Morissette, R.Fernandes, J.L.Champeaux, R.B.Myneni, J.Chen, S.Plummer, M.Weiss, C.Bacour, S.Garrigues, J.E.Nickeson, 2006. Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: proposition of the CEOS-BELMANIP. IEEE Transactions Geoscience and Remote Sensing, 44 , 1794-1803.

Chuvieco, E., P. Englefield, A. P. Trishchenko, Y. Luo, 2008. Generation of long time series of burn area maps of the Boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, 112 (5), pp. 2381-2396.

Fernandes, R., V.Korolevych, S. Wang, 2007. Trends in land evapotranspiration over Canada for the period 1960-2000 based on in situ climate observations and a land surface model. Journal of Hydrometeorology, 8 (5), pp. 1016-1030.

Fontana, F.M.A. A.P.Trishchenko, K.V.Khlopenkov, Y.Luo, S.Wunderle, 2009. Impact of orthorectification on maximum NDVI composite data. Remote Sensing of Environment, Submitted (as of April 2009).

Garrigues, S., R. Lacaze, F. Baret, J. T. Morisette, M. Weiss, J. E. Nickeson, R. Fernandes, S. Plummer, N. V. Shabanov, R. B. Myneni, Y. Knyazikhin, and W. Yang, 2008. Validation and intercomparison of global Leaf Area Index products derived from remote sensing data. Journal of Geophysical Research, 113, G02028, doi:10.1029/2007JG000635

Guo, S., H.G. Leighton, J. Feng, A.P.Trishchenko, 2007: Wildfire aerosol and cloud radiative forcing in the Mackenzie River basin from satellite observations. Book chapter 21 in "Cold Region Atmospheric and Hydrological Studies: The Mackenzie GEWEX Experience".Vol.1; Atmospheric Dynamics. Springer-Verlag. pp.365-381.

Khlopenkov, K.V., A.P.Trishchenko, Luo, Y., A.Komarov, 2009. Image matching technique to achieve sub-pixel georeferencing accuracy in Canadian AVHRR processing system (CAPS). IEEE Transactions Geoscience and Remote Sensing. To be submitted (as of April 2009).

Khlopenkov K.V., A.P.Trishchenko, 2008. Implementation and evaluation of concurrent gradient search method for reprojection of MODIS level 1B imagery. IEEE Transactions Geoscience and Remote Sensing. 46 (7), art. no. 4538199, pp. 2016-2027.

Khlopenkov, K, A.P.Trishchenko: 2007: SPARC: The new cloud, clear-sky, snow/ice and shadow detection algorithm for historical AVHHR 1-km observations. Journal of Atmospheric and Oceanic Technology. Vol. 24, No. 3, pages 322-343

Latifovic, R., D.Pouliot, 2007: Analysis of climate change impacts on lake ice phenology in Canada using the historical satellite data record. Remote Sensing of Environment, 106 (4), pp. 492-507

Luo, Y., A. P. Trishchenko, K.V.Khlopenkov, 2008: Developing clear-sky, cloud and cloud shadow mask for producing clear-sky composites at 250-meter spatial resolution for the seven MODIS land bands over Canada and North America. Remote Sensing of Environment. 112 (12), pp. 4167-4185.

Morisette, J.T., F.Baret, J.LPrivette, R.B.Myneni, J.E.Nickeson, S.Garrigues, N.V.Shabanov, M.Weiss, R.Fernandes, S.G.Leblanc, M.Kalacska, G.A.Sanchez-Azofeifa, M.Chubey, B.Rivard, P.Stenberg, M.Rautiainen, P.Voipio, T.Manninen, A.N.Pilant, T.E. Lewis, J.S.Iiames, R.Colombo, M.Meroni, L.Busetto, W.B.Cohen, D.P. Turner, E.D. Warner, G.W.Petersen, G.Seufert, R.Cook, 2006.  Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup. IEEE Transactions Geoscience and Remote Sensing, 44, 1804-1817.

Pouliot, D., R.Latifovic, I.Olthof, I.  2008: Trends in vegetation NDVI from 1 km AVHRR data over Canada for the period 1985-2006. International Journal of Remote Sensing, 30 (1), pp. 149-168.

Radkevich, A.V., A.P.Trishchenko, 2008: An approach for aerosol retrievals over Canada’s landmass from historical AVHRR 1-km observations. Proceedings of IGARSS 2008. Boston. MA, 4pp

Trishchenko, A.P., Y.Luo, K. Khlopenkov, W.M.Park, S.Wang, 2009. Arctic circumpolar mosaic at 250m spatial resolution for IPY by fusion of MODIS/TERRA land bands B1-B7. International Journal of Remote Sensing, 30 (6), pp. 1635-1641.

Trishchenko, A.P., 2008. Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors: Extension to AVHRR NOAA-17, 18 and METOP-A. Remote Sensing of Environment. 113, pp. 335-341. 10.1016/j.rse.2008.10.002

Trishchenko, A.P., Y.Luo, K. Khlopenkov, S.Wang, 2008. A method to derive the multi-spectral surface albedo consistent with MODIS from historical AVHRR and VGT satellite data. Journal of Applied Meteorology and Climatology, 47(4), 1199-1221.

Trishchenko, A.P., K.V. Khlopenkov, C.Ungureanu, R.Latifovic, Y.Luo, W.B.Park. 2007. Mapping of surface albedo over Mackenzie River basin from satellite observations. Book chapter 19: in "Cold Region Atmospheric and Hydrological Studies: The Mackenzie GEWEX Experience". Vol.1; Atmospheric Dynamics. Springer-Verlag. pp.327-341.

Trishchenko, A.P., 2006. Solar irradiance and brightness temperatures of AVHRR and GOES SW channels. Journal of Atmospheric and Oceanic Technology, 23, pp.198-210.

Trishchenko, A.P., Y.Luo, K.V.Khlopenkov, 2006: A method for downscaling MODIS land channels to 250 m spatial resolution using adaptive regression and normalization, SPIE, paper No:6366-07, 8pp.

Wang, S. A. P. Trishchenko, X.Sun, 2007: Simulation of canopy radiation transfer and surface albedo in the EALCO model. Climate Dynamics. 29, 29, pp.615-632. DOI 10:1007/s00382-007-0252-y.

Wang, S., and Davidson, A., 2007. Impact of climate variations on surface albedo of a temperate grassland. Agricultural and Forest Meteorology 142, 133-142, doi:10.1016/j.agrformet.2006.03.027
Wang, S., A. P. Trishchenko, K. V. Khlopenkov, and A. Davidson, 2006. Comparison of International Panel on Climate Change Fourth Assessment Report climate model simulations of surface albedo with satellite products over northern latitudes. Journal of Geophysical Research, 111, D21108, doi:10.1029/2005JD006728.

Zhao, H. and Fernandes, R., 2008.  Daily snow cover estimation from AVHRR Polar Pathfinder Data over Northern Hemisphere land surfaces during 1982-2004. Journal of Geophysical Research, 114, D05113, doi:10.1029/2008JD011272.

Additional Materials and Information

CEOS, 2006: Satellite Observation of the Climate System: The Committee on Earth Observation Satellites (CEOS) Response to the Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC. 54pp. Available at www.ceos.org/CEOS%20Response%20to%20the%20GCOS%20IP.pdf.

GCOS, 2006: Systematic observation requirements for satellite-based products for climate. Supplemental details to the satellite-based component of the Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC. GCOS-107, September 2006. Available at http://www.wmo.int/pages/prog/gcos/Publications/gcos-107.pdf

Goodrum, G., Kidwell, K.B., Winston, W. (Eds), 2000: NOAA KLM User’s Guide. Revised. US Department of Commerce, NESDIS, NOAA, National Climatic Data Center, Satellite Data Services Division, Washington, DC, USA. Available at http://www2.ncdc.noaa.gov/docs/klm/index.htm