Canada-wide maps of dominant tree species from remotely sensed and

ground data

G. PAVLIC{{, W. CHEN*{, R. FERNANDES{, J. CIHLAR{, D. T. PRICEx,R. LATIFOVIC{, R. FRASER{ and S. G. LEBLANC{

{Applications Division, Canada Centre for Remote Sensing, Canada

{Under contract to the Canada Centre for Remote Sensing,

Natural Resources, Canada

xNorthern Forestry Centre, Canadian Forestry Service, Canada

(Received February 2005; in final form February 2006)

Information on the spatial distribution of dominant tree species is important asinput or validation data in large scale ecological studies, such as carbon budgetestimation, biodiversity assessment, and vegetation dynamic modelling. We used

a 1-km resolution land cover map of Canada produced from 1998 SPOT VGTsatellite data as the base map. Fractions of coniferous needleleaf or deciduousbroadleaf forests within each 1-km pixel were then estimated by developing

relationships with climate using land-cover maps from Landsat images selected asa representative sample. The fraction of coniferous/deciduous forest within each1-km pixel was further divided into dominant species fractions using speciescomposition information at the sub-ecoregion level, derived from statistics in the

Canadian Forest Inventory (CanFI 1991/94 version), from narrative descriptionsof ecoregions, and from topographical data. A total of 17 Canada-wide maps ofdominant tree species groups at 1 km-resolution were produced. The estimates of

this study agree well with CanFI data at the ecoregion level where available, andshow good correspondence with published range maps of Canadian tree species.

Keywords: Dominant tree species; Maps; Canada; Remote sensing; CanFI;

Narrative description of ecoregion; DEM

1. Introduction

Forests provide wood products as well as important ecological services, such ascleaning air and water, sequestering carbon, and maintaining biodiversity. Foreststands of different species composition, however, often differ substantially in theirability to provide these goods and services. Therefore, information on forest speciesdistribution is essential to better quantify the ability of forests to provideeconomically or environmentally important goods and services. For example,country-wide datasets of dominant tree species distribution are needed as inputs tocarbon budget modelling (e.g. McGuire et al. 2001, Chen et al. 2000, Chen et al.2003) and biodiversity assessments (Kerr and Cihlar 2004). They can also be used to

*Corresponding author. Email: wenjun.chen@ccrs.nrcan.gc.ca

Geocarto InternationalVol. 22, No. 3, September 2007, 185–204

Geocarto InternationalISSN 1010-6049 print/ISSN 1752-0762 online ª 2007 Taylor & Francis

http://www.tandf.co.uk/journalsDOI: 10.1080/10106040701201798

validate results of vegetation dynamics models (El Maayar et al. 2001), or to providea basis for projecting vegetation changes into the future.The Canadian Forest Inventory (CanFI) contains tree species information, but

only statistics of species composition over a large area are publicly available (Grayand Power 1997, http://nfi.cfs.nrcan.gc.ca/canfi). By integrating forest inventory andremote sensing information, Koble et al. (2001) created a database of forest speciesdistribution for the forests within the 15 member states of the European Union(EU15). In the present study, we aimed to develop Canada-wide maps of dominantforest species groups using a similar approach. The 17 dominant species groups wereadopted from the CanFI91/94 (Gray and Power 1997, table 1).

2. Data sources and treatments

The data used in the study are listed below, along with brief descriptions of datasources and preprocessing methods. All data were re-projected to the GRS 1980(NAD83) earth ellipsoid version of the Lambert Conformal Conic (LCC) mapprojection using a 1-km grid.

2.1 Land cover map of Canada in 1998 at 1-km resolution

186 G. Pavlic et al.

A land cover map with a pixel size of 1 km was produced from a temporal compositeof SPOT-VEGETATION (VGT) satellite data, acquired during July and August1998 (Cihlar et al. 2002). The land cover map consisted of 12 classes derived from 51underlying labelled spectral clusters.

Table 1. An example of using the Canadian ecoregion narrative descriptions to estimate thecomposition of dominant tree species for coniferous and deciduous forests. The dominantspecies groups are adopted from the Canadian Forest Inventory (CanFI91/94).

Topographical featuresElevation All AllAspect All AllDrainage Other sites Dry sites

Dominant coniferous tree species groupsBlack or red spruce (BS) 33%Other spruce (OS) 33%White pine (WP)Jack, lodgepole or shore pine (JP) 33% 100%Other pine (OP)Balsam, amabilis, grand, or subalpine fir (BF)Hemlock (HK)Douglas fir (DF)Larch (LA)Cedar or other coniferous (OC)

Dominant deciduous tree species groupsTrembling aspen (AS) 100%Other poplar (PO)Yellow birch (YB)Other birch (OB)Sugar or black maple (SM)Other maple (OM)Other broadleaf species (OH)

2.2 Landsat TM/ETMþ land cover samples across Canada

A total of 33 Landsat TM/ETMþ scenes were selected using an objective procedureto capture the statistical distribution of land cover across Canada (figure 1) (Cihlaret al. 2003, Latifovic and Olthof 2004). These Landsat scenes were classified usingan Enhancement Classification Method (Beaubien et al. 1999). The classificationemployed a legend with 33 land cover types based on a modified National VegetationClassification Standard (NCVS) as defined by the US Federal Geographic DataCommittee (FGDC) (Grossman et al. 1998).

2.3 Water body fraction coverage of Canada

This dataset represents the fraction of liquid surface water within each 1-km grid cellacross Canada (Pavlic et al. 2002), as mapped within the National Topographic DataBase (NTDB) v3.1 (Anonymous 1996). Water covered areas are defined as all waterbody entities reported in the NTDB 1:50000 mapping scale (or 1:250000 scale if theformer was unavailable).

Figure 1. Distribution of Landsat TM/ETMþ scenes (path/row) used in this study, acrossvarious ecozones (numbered) in Canada. Ecozones 1 to 15 are, respectively, Arctic Cordillera,Northern Arctic, Southern Arctic, Taiga Plains, Taiga Shield, Boreal Shield, AtlanticMaritime, Mixedwood Plains, Boreal Plains, Prairies, Taiga Cordillera, Boreal Cordillera,Pacific Maritime, Montane Cordillera, and Hudson Plains.

Maps of dominant tree species from remotely sensed and ground data 187

2.4 Climate data

A global monthly climate data set for the 20th century (New et al. 2000) was used.We extracted mean monthly temperature and precipitation over Canada’s landmass.The original 0.5-degree data were further interpolated (bilinear interpolation) intothe base map projection at 1-km resolution to be spatially consistent with theremotely sensed data.

2.5 Narrative descriptions of terrestrial ecoregions of Canada

Narrative descriptions provide qualitative information about the geographicdistribution of dominant tree species across Canada’s landmass. The smallestecological unit for which narrative descriptions are available is the ecoregion(Wiken et al. 1993). In total, Canada’s landmass is divided into 194 ecoregionswith a mean area of 41 058 km2. The information contained in the narrativedescriptions of an ecoregion typically allows the fractions of dominant forestspecies to be estimated at the sub-ecoregion level, on the basis of drainage classesand topographical positions.

2.6 Canadian Forest Inventory dataset

The CanFI dataset was first compiled by the Canadian Forest Service for the year1981, and it has since been updated three times (1986, 1991 and 2001). On eachoccasion, provincial and territorial forest management inventories and reconnais-sance level information were used as inputs to the national roll-up (Gray and Power1997). These management agencies have developed their own measurementstandards and they are continually updating their forest inventories as resourcespermit, so the quality and age of the data used in CanFI is quite variable, both intime and across the country. It also generally lacks information on non-timberattributes and is of unknown precision (http://nfi.cfs.nrcan.gc.ca/overview_e.html).However, CanFI reports of forest species composition within the inventoried areasare considered quite accurate, because species distributions are unlikely to havechanged greatly during the last decades.Due to the above limitations in the CanFI dataset, in this study we used only

species composition data at the ecoregion level, in combination with the informationderived from the narrative descriptions of ecoregions.

2.7 Drainage layer

The polygon coverage of Soil Landscapes of Canada (SLC-V2.2) containsinformation of soil drainage classes (Canadian Soil Information System (CanSIS)1996). These polygons were gridded at 1-km and re-projected into the base mapprojection to produce a site drainage layer of Canada.

2.8 Topographical data

The narrative descriptions of ecoregions include relationships between tree speciesand terrain elevations and/or aspects. Therefore, data layers of elevation and aspectswere extracted from the USGS 1 km Digital Elevation Model (DEM) for North

188 G. Pavlic et al.

America (http://edcdaac.usgs.gov/gtopo30/hydro), and re-projected onto the basemap.

3. Methodology

The methodology to map dominant tree species over Canada was largely determinedby data availability. Figure 2 shows the 3-steps approach taken to derive the spatialdistribution of fractional dominant tree species. Step 1, shown on the right side offigure 2, yields the fraction of coniferous or deciduous forests within each of a 1-kmresolution pixel from the 1-km resolution land cover map of Canada. Step 2, on theleft side of figure 2, provides information that is used to further divide the coniferousforests and deciduous forests fractions into dominant tree species groups. Thisinformation was given at the sub-ecoregion level if drainage classes and topographywarranted a further stratification within an ecoregion (see further details aboutthe stratification of ecoregions in section 3.2). In cases where no stratification wasrequired, the information would be presented at the ecoregion level. In the final step,the fractions of coniferous forests or deciduous forests within each 1-km pixel weredivided into fractions of dominant tree species. Details of these steps are describedbelow.

3.1 Quantifying fractions of coniferous and deciduous forest at 1-km resolution

The starting point for quantifying fractions of coniferous and deciduous forest overCanada was the 1-km resolution land cover map for 1998. Among its 12 land cover

Figure 2. Flowchart showing the procedure for estimating fractions of dominant tree speciesgroups over Canada.

Maps of dominant tree species from remotely sensed and ground data 189

classes, five are forest types: coniferous forest with closed canopy, deciduous forestwith closed canopy, mixed coniferous-deciduous forest with closed canopy,coniferous forest with open canopy, and mixed coniferous-deciduous forest withopen canopy.A 1-km pixel classified as coniferous (or deciduous) forest with closed canopy

could contain a substantial amount of deciduous (or coniferous) trees (Cihlar et al.2002, Latifovic and Olthof 2004). Directly labelling these forest classes into onedominant tree species could thus result in significant errors. A desirableimprovement would be to further divide each 1-km pixel of forest class intofractions of coniferous forest, deciduous forest, and other classes that might bepresent (e.g. water, bare soil, rock). Only the coniferous (or deciduous) componentwould then be labelled as coniferous (or deciduous) tree species within each 1-kmpixel.The fractions of coniferous forest, deciduous forest, and other land classes within a

1-km pixel can be estimated using higher spatial resolution land cover maps, such asthose available from 30-m resolution Landsat TM/ETMþ data. Such a data set wasavailable to this study. A total of 33 Landsat TM/ETMþ scenes were selected usingan objective procedure (Cihlar et al. 2000a,b) to represent the statistical distributionof land cover classes across Canada (figure 1) (Cihlar et al. 2003, Latifovic andOltholf 2004). By using a cross-tabulation of spatially coincident 1-km pixel SPOTVGT and 30-m pixel Landsat TM/ETMþ land cover data, the percentages ofconiferous and deciduous forest were extracted for every 1-km pixel within theseLandsat TM/ETMþ scenes. The extraction method was described by Cihlar et al.(2003) and Latifovic and Olthof (2004). Since the 33 Landsat TM/ETMþ scenescovered only a small portion of Canada’s forested land, it was necessary todevelop a method for scaling up the sub-1-km-pixel fraction information fromthese Landsat TM/ETMþ scenes to the entire country. Mapping land cover atthe Landsat level for Canada is presently underway in large scale projects, andbefore the completion of this work, there are three possible options for scalingup. The first is to assume that fractions of coniferous and deciduous forests areidentical everywhere in the country for a given forest class. Consequently, themean fractions of coniferous and deciduous forests derived from these LandsatTM/ETMþ scenes for a certain forest class would be applied to this forest classeverywhere in Canada. The second option is to geographically stratify (e.g. at theecozone level) the fractional information of coniferous or deciduous forests withina forest class. In this case, the mean fractions of coniferous and deciduous forestsderived from the 33 TM/ETMþ derived land cover maps for a given forest classwithin an ecozone would be applied to this forest class everywhere in the ecozone.A third option is to relate the fractions of coniferous or deciduous forests withina forest class to climate as it is well established that at large area scale vegetationspatial distribution corresponds to climate (e.g. Odum 1983). To implement thisoption, a number of statistical relationships (further discussed in section 4.1) wereestablished between the fractions of coniferous and deciduous forests within aforest class and key climate indices (e.g. average growing season air temperaturefrom May to September, annual precipitation). These relationships were thenapplied to the whole country.Results obtained using each of the three options were compared and the best

method selected (discussed in section 4.1) for production of maps of the Canada-wide fractional coverage of coniferous or deciduous forest.

190 G. Pavlic et al.

3.2 Estimating dominant tree species fractions at the ecoregion or sub-ecoregion level

The narrative descriptions at the ecoregion level contain information on dominantforest species, and their association with drainage classes and topographicalpositions (Wiken et al. 1993). When combined with drainage class and topographicinformation, the fractions of dominant forest species may thus be estimated at thesub-ecoregion level.The narrative descriptions were transformed into numerical values, as follows. For

abundance, predominant was interpreted as 100%; dominant 80%; secondary 20%,and occasional 10%. If the text lists the main species as an equal mixture, then allspecies were assigned with the same fraction. The three drainage classes are welldrained; moderately drained, and poorly drained. For elevation, the descriptionsusually give the range of elevations where the species occur. At the Rocky Mountainssites, montane was interpreted as 1200–1800 m, sub-alpine 1800–2100 m, and alpineabove 2100 m (Protected Areas Programme, UNEP World Conservation Monitor-ing Centre, http://www.wcmc.org.uk:80/protected_ areas/data/wh/rockies.html). Wenoticed that the appropriate elevation ranges for each ecoregion varied with latitude,but a lack of details in the narrative descriptions prevented us from carrying outfurther stratification. The aspect in the description corresponds to eight DEM aspectclasses, defined as eight 458 sectors centered on the cardinal bearings.Table 1 shows an example of how the narrative descriptions were used. For

ecoregion 181 (Liard Basin), the descriptions state that ‘‘the ecoregion ischaracterized by extensive stands of boreal forest composed of lodgepole pine,white and black spruce, and aspen. Dry sites support lodgepole pine.’’ We assumedthat the dry sites (well drained) in the ecoregion would be close to 100% lodgepolepine, which is grouped with jack pine and shore pine into a species group, accordingto CanFI91/94 and denoted as ‘JP’. The deciduous component would be close to100% aspen (denoted ‘AS’). For the remaining sites in this ecoregion, the coniferouscomponent was assumed to be composed of black spruce (grouped with red spruce,as ‘BS’) at 33%, other spruce species group (denoted ‘OS’) at 33%, and JP at 33%.The integration of estimates from the ecoregion narrative description and CanFI

was based on an algorithmic process (table 2). The ecoregion narrative descriptionsand CanFI are compilations of information generated at different times and withdifferent standards, but the CanFI database was based on extensive inventories withstricter data quality control. Therefore, the CanFI species composition estimates atecoregion level should be more accurate than those derived from the narrativedescriptions. Hence, (1) where CanFI species information was available it was used(table 2, case a); (2) where CanFI species information was available but did not coverthe entire ecoregion, the CanFI estimate was distributed to the entire ecoregion usinga weighted sub-ecoregion area fraction (table 2, case b); (3) where CanFI coveragewas not available (e.g. sparse forest in the North) the estimates from the ecoregionnarrative descriptions were retained and weighted by sub-ecoregion area fraction(table 2, case c); (4) a correction was applied to force the fractions of all species to100% at the sub-ecoregion level.

3.3 Estimating fractions of dominant tree species group at 1-km resolution

The final step in estimating dominant tree species fractions at 1-km resolution was toapply the dominant tree species composition statistics at sub-ecoregion or ecoregion

Maps of dominant tree species from remotely sensed and ground data 191

level from section 3.2 to the 1-km resolution fractions of coniferous or deciduousforest from section 3.1. The species fractions were forced to equal the sum of thefractions of coniferous and deciduous forest within every forest class pixel. Figure 3shows an example of the final step, where coniferous and deciduous fractionsobtained from SPOT VGT and Landsat data indicated that 60% of the pixel wascovered by coniferous forest, 20% by deciduous forest, and 20% by other land covertypes. The statistics of dominant tree species fractions at the ecoregion/sub-ecoregion level indicate that 40% of the coniferous forest belongs to the black spruceand red spruce group (BS), 40% is other spruce (OS), and 20% is hemlock (HK); ofthe deciduous forest, 80% is trembling aspen (AS), and 20% is yellow birch (YB).The final result for this 1-km resolution pixel is thus estimated as 24% BS, 24% OS,12% HK, 16% AS, and 4% YB.

4. Results and discussion

4.1 Fractions of coniferous and deciduous forest at 1-km resolution

Figure 4 shows the relationship between coniferous/deciduous fractions and theMay–September mean air temperature averaged over 1901–1998 for the closed-canopy coniferous forest class as reported in the 1998 Canada land cover map. Eachpoint represents the mean fractional value of coniferous or deciduous forestaveraged over half of the Landsat scene. The partitioning of a Landsat scene wasbased on the May–September mean air temperature. There are two reasons forchoosing half of the Landsat scene to establish the climate-coniferous/deciduousfractions relationship. First, such relationships can be expected to emerge only atlarge area spatial scales, without being obscured by topographic, hydrologic or otherlocal factors. Secondly, we found significant changes in temperature within aLandsat scene in some cases. For instance, for a scene in Rocky Mountains region,the temperature of the two half scenes are 88C and 108C, with correspondingdeciduous fractions being 22% and 14%, respectively. As shown in figure 4,substantial changes in the coniferous and deciduous fractions for the closed-canopy

Table 2. An example of integrating the Canadian ecoregion narrative description andCanadian Forest Inventory (CanFI91/94) species composition data to estimate dominant treespecies fraction at the sub-ecoregion level. See text for explanation of the different cases (a, b,c) and integration steps. BS, black or red spruce; OS, other spruce; JP, jack, lodgepole or shorepine; OP, other pine; BF, balsam, amabilis, grand, or subalpine fir; LA, larch.

% of coniferous or deciduousforests at the ecoregion or

sub-ecoregion level

Spatial scale% of forests

at the ecoregionBS(a)

OS(a)

JP(a)

OP(b)

BF(c)

LA(a)

CanFI Ecoregion 100 10 40 30 10 – 10Text

DescriptionsSub-ecoregion 1 30 60 – – – – 40Sub-ecoregion 2 70 – 50 40 – 10 –

Integrationstep 1–3

Sub-ecoregion 1 30 10 – – 3 – 10Sub-ecoregion 2 70 – 40 30 7 7 –

Integrationstep 4

Sub-ecoregion 1 30 43 – – 13 – 43Sub-ecoregion 2 70 – 48 36 8 8 –

192 G. Pavlic et al.

3

coniferous class were found along the mean air temperature gradient. Similarrelationships were also found for other forest classes (table 3). A multiple regressionprocedure of subset selection (Miller 2002) was used to relate the May–Septembermean air temperature and annual precipitation averaged for the period 1901–1998,to the coniferous/deciduous fractions within each forest class. In most cases, thefractions are significantly related to both temperature and precipitation. Significantdifferences were also found between humid and dry areas. The aridity index (AI) wasused to differentiate between humid and dry regions. AI was computed as the ratioof mean annual precipitation to potential evapotranspiration for the period 1961–90,following the procedure described by Sauchyn et al. (2002). Figure 5 shows thedistribution of humid (AI4 1) and dry (AI� 1) areas in Canada. In humid regions,air temperature is the most important factor, and it explained well the variations infractions of coniferous and deciduous forests. For drier areas, both air temperatureand precipitation were found to be important factors. The relative stand estimationerrors, calculated as stand estimation error divided by the mean value, were less then20%. The main reason is that fractions of deciduous forest in both closed-canopyand open-canopy coniferous forest classes are low, so the relative standard errorswere correspondingly higher, 39% and 34%, respectively.The significant relationships between coniferous/deciduous fractions and climate

variables suggest that the up-scaling approach in Option 1 (assuming the fractions ofconiferous/deciduous forest are the same everywhere in the country for a forest class)could result in substantial errors. Option 2 of stratifying the fractional informationat the ecozone level would do better than Option 1, but could not account for withinecozone variations. Furthermore, Option 2 could introduce artificial variations in

Figure 3. Example showing the final step for quantifying the dominant tree species fractionsat 1-km resolution.

Maps of dominant tree species from remotely sensed and ground data 193

coniferous and deciduous fractions along a boundary between ecozones. Therefore,Option 3, which relies on climate-coniferous/deciduous fractions relationships, is thebest choice. Using the relationships given in table 3, coniferous and deciduousfractions for Canada (figure 6, upper panel) were estimated. The final fraction valueswere corrected using the water body fraction coverage (Pavlic et al. 2002) to accountfor the portion of each pixel covered by water. Where the sum of water body,needleleaf, and broadleaf area fractions exceeded 100%, a reduction factor wasapplied proportionately to all three fractions. Overall, coniferous forests were foundto contribute a much higher proportion across Canada than deciduous forests. InPacific coastal regions, the coniferous fraction may exceed 80%. A relatively highfraction (up to 70%) of coniferous forests was also found in the western mountainranges and along the Atlantic coast. The extensive boreal forest zone typicallycontains 30–60% coniferous species. The highest fractions of deciduous forests occuralong the St. Lawrence River, and to a lesser extent, at the southern edge of thewestern boreal forest zone, typically in the range 40–60%. For the remainder ofCanada’s forestland deciduous forests typically contribute less than 15% of theland cover.As the coniferous and deciduous fractions were estimated using relationships with

climate variables at a scale comparable to a half-Landsat scene, they represent anapproximation of the broad scale average, instead of providing spatial detail at1-km resolution. In reality, distribution may be patchier. For example, the deciduous

Figure 4. Relationship between coniferous/deciduous fractions and the May–Septembermean air temperature averaged over 1901–98, for the closed-canopy coniferous forest class inthe 1998 Canada land cover map.

194 G. Pavlic et al.

Table3.

Relationshipsbetweenconiferous/deciduousfractionsandclim

ate

variables(M

ay–September

meanairtemperature

T,andannualprecipitation

Paveraged

from

1901–98).Theregressionsweredoneseparately

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(AI)4

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areaswithAI�1.Erroris

calculatedasthestandard

estimationerrordivided

byitsmeanvalue,

andN

isthenumber

ofsamples.

Landcover

class

Relationships

r2Error(%

)N

Closed-canopy

coniferousforest

%C¼�0:0131T2þ0:2666T�0:6832;

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0.39

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%C¼�0:0035T2þ0:0575Tþ0:1995;

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�0.70

0.15

28

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11:9198969�0:10859T�6:08112�10�5P;

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�0.73

0.16

Closed-canopy

mixed

forest

%C¼�0:0046T2þ0:0811Tþ0:2278;

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�0.55

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%D¼

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0.17

Open-canopy

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%C¼�0:0025T2þ0:0352Tþ0:3835;

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�0.49

0.15

Maps of dominant tree species from remotely sensed and ground data 195

forest fraction along the St. Lawrence River can easily reach 80–90% at one locationand close to zero at a nearby site, instead of being consistently 40–60% everywhere.Therefore, a significant improvement, especially with regard to spatial precision,could be achieved by directly quantifying the fractions of coniferous and deciduousforests at 1-km resolution using Landsat TM/ETMþ land cover classification. ACanada-wide forest cover classification is currently being carried out by theCanadian Forest Service using Landsat data (http://www.pfc.forestry.ca/eosd), andupon its completion could be used to improve the fractional coverage estimatesreported here.

4.2 Fractions of dominant tree species groups

Using the species composition information derived using a) CanFI, b) the narrativedescription of ecoregions, c) the national digital elevation model (DEM), d) drainageclass data from SLC 2.2, and e) water body distribution database, we further dividedthe fractions of coniferous and deciduous forests into dominant tree species groups.A total of 17 Canada-wide maps of dominant tree species fractions were produced,corresponding to the dominant tree species groups identified in CanFI (1991/94version). The lower panels of figure 6 show examples of these species maps for two

Figure 5. Distribution of humid (Aridity Index4 1) and dry (Aridity Index41) areas inCanada.

196 G. Pavlic et al.

widely distributed species groups: black and red spruce group (BS) and tremblingaspen group (AS), and two localized species groups: white pine (WP) and yellowbirch (YB).

Figure 6. Maps of coniferous/deciduous fractions over Canada (upper panels), and examplesof dominant tree species fraction maps for two widely distributed species groups: black andred spruces (BS) and trembling aspen (AS), and two localized species groups: white pine (WP)and yellow birch (YB) (lower panels). Also range maps are included (Farrar 1995). Availablein colour online.

Maps of dominant tree species from remotely sensed and ground data 197

The BS group covers the largest forest area among the 17 dominant tree speciesgroups, about 57 million hectares (table 4). Its fractions reach 30–50% in theeastern boreal shield of Ontario, Quebec, and Newfoundland (includingLabrador). The western boreal shield and taiga plains ecozones, extendingfrom Manitoba to the Yukon, contain significant fractions of BS, accountingfor 10–30% of the forested area. Trembling aspen (AS) is the most widelydistributed deciduous species, covering *22 million hectares, with the greatestabundance found in the boreal plains of the prairie provinces and in the MontaneCordillera ecozone in central and northern British Columbia. White pine (WP)occurs in British Columbia and in the east from Manitoba to Newfoundland,with a total area of *1.4 million hectares. Yellow birch is present in the mixedwood plains from Ontario to the Maritime Provinces, and is most abundant inQuebec.As for the coniferous/deciduous fractions these species fraction maps reflect large

spatial patterns, and should be most useful for large area scale studies. Improvedspatial details in dominant tree species fractions could be obtained from moredetailed coniferous/deciduous fractions, and through more spatially detailed speciescomposition information, e.g. from detailed forest inventory.

4.3 Comparison with other data sets

Total areas of coniferous and deciduous fractions were compared with CanFI atthe ecoregion level (figure 7). Note that the estimates of total coniferous anddeciduous areas obtained in this study were derived using remotely senseddata, thus being independent of CanFI. Overall, the correlations were high, withr2 of 0.87 and 0.78 for coniferous and deciduous fractions, respectively. Theestimates obtained in this study, were generally higher than those given by CanFIbecause the ‘unclassified’ category of CanFI was in this study assigned to eitherconiferous or deciduous fraction. Forested regions outside of the CanFI91/94inventoried area were not included in this comparison. At the dominant treespecies level, existing data from other studies enable two comparisons. First,Farrar’s (1995) species range maps, show the observed natural distribution ofindividual tree species. The exact boundary of a species’ range is often uncertain,as noted by Farrar (1995). Within the range, the abundance of a species variesconsiderably, and a few individuals may survive at sites beyond the rangeboundary depending on local soil and climate conditions. The range maps wereincluded in figure 6 for the four dominant tree species groups. Overall, goodcorrespondence was found between the distributions of dominant tree species andthose reported by the range maps. The total area of a dominant tree species groupestimated in this study was determined through remote sensing with the CanFIdataset being used only for estimating the fractions of dominant tree speciesgroups within coniferous/deciduous at the ecoregion level. Therefore, it is ofinterest to compare the total areas of dominant tree species groups at the ecoregionlevel as reported by CanFI to those estimated in this study. Figure 8 shows 1:1comparisons for the four species group included in figure 6. Overall, theagreements were very good, with r2 values of 0.91 for BS, 0.63 for AS, 0.91 forWP, and 0.79 for YB (table 5). Again, these 1:1 comparisons included onlyecoregions located within the CanFI inventoried region. Table 6 shows the totalareas of dominant tree species groups, including regions outside the CanFI 1991/94

198 G. Pavlic et al.

Table

4.

Abundance

ofdominanttree

speciesgroupswithin

CanadianProvincesandTerritories

(in1000ha).

British

Columbia

Alberta

Saskatchew

an

Manitoba

Ontario

Quebec

New

Brunsw

ick

Prince

Edward

Island

New

foundland

andLabrador

Nova

Scotia

Yukon

Northwest

Territories

Nunavut

Canada

BS

1150

1557

3101

5614

16791

17808

869

16

6602

916

844

2079

67

57420

OS

6671

6065

1564

2056

2494

2780

217

18

530

239

3794

4833

61

31327

WP

1094

10

97

6657

3996

561

13

596

1264

00

01428

JP11409

5543

3562

3295

5141

2377

59

11

12

1416

957

11

33791

OP

413

50

010

434

167

27

00

19

00

01124

BF

2540

691

188

265

2398

2267

907

19

2935

589

782

147

118736

HK

4575

00

0208

183

29

10

43

00

05042

DF

4129

308

12

00

00

00

00

04442

LA

204

311

220

729

1764

1783

47

1319

42

167

637

48

6279

OC

2009

10

09

680

433

147

10

30

00

3296

AS

2959

5669

2619

2721

3298

1446

178

4310

46

1003

2131

43

22405

PO

527

718

420

1283

3517

1560

59

012

1214

215

11

8544

YB

00

00

168

609

351

2226

156

00

01514

OB

517

462

567

936

3003

6034

77

02150

62

143

367

414328

SM

00

020

1182

1221

499

60

200

00

03132

OM

54

025

59

306

623

500

25

78

596

00

02270

OH

764

18

68

267

4178

2662

309

1153

113

00

08538

All

38037

21403

12343

17281

46235

47360

4338

100

13380

3170

8368

11370

221

223616

Maps of dominant tree species from remotely sensed and ground data 199

boundaries—mostly in the north—which were classified as forest in the 1998SPOT-VGT land cover map (Cihlar et al. 2002) and also described in the ecoregionnarrative descriptions. The total areas occupied by tree species that dominate in thenorth, such as black spruce and tamarack, are therefore significantly larger thanthose determined directly from CanFI. Conversely, for those tree species that occurpredominantly within the CanFI91/94 boundaries excellent agreement wasobtained (table 5).

4.4 Uncertainties in input data and their impacts on the accuracy of the final maps

The final forest species maps are derived on the basis of a number of independentdata sets: land cover maps at 30 m and 1-km resolutions, CanFI data, narrativedescriptions of terrestrial ecoregions, water fraction map, Digital Elevation Model,soil drainage coverage, and climate. While the uncertainties in all these inputs couldhave an impact on the accuracy of the final dominant species maps, we simply do notknow these uncertainties, with the exception of land cover maps, and so have no wayto examine their impacts.For land cover maps, spatial and thematic resolutions are interdependent, and

low spatial resolution and high thematic resolution unavoidably lead to lowaccuracy (Smith et al. 2003). For example, Cihlar et al. (2003) and Latifovic andOlthof (2004) reported that accuracy of land cover products for Canada derivedfrom 1-km resolution data is accurate at 91% at the level of two classes (forest/non-forest), and at *80% using the 6-class IPCC (Intergovernmental Panel onClimate Change) legend since the classes do not intermix at the pixel level. When9–16 forested classes were classified, the accuracy was reduced to *47%. Theselow accuracies in the 1-km ‘hard classification’ are mainly caused by the fact that

Figure 7. Comparison of total coniferous/deciduous forest areas at the ecoregion levelbetween CanFI91/94 and this study for areas covered by CanFI91/94.

200 G. Pavlic et al.

forest stands are usually a mixture of deciduous and coniferous species, so thatlabelling a stand as either deciduous or coniferous results in a large error. Thiserror can be reduced if we instead estimate the fractions of deciduous andconiferous within a 1-km pixel using 30-m resolution Landsat data. High accuracyof land cover maps from 30-m resolution Landsat TM/ETMþ, using theEnhancement Classification Method (ECM) (which is also the method used inthis study), was reported by Beaubien et al. (2001): e.g. coniferous 90%, deciduous96.9%, mixed 80.0%, disturbed/other 95.9%, with an overall accuracy of 90.7%.Relationships between the coniferous/deciduous fractions and climate data weredeveloped using results from 33 Landsat scenes and applied to all 1-km pixels. Therelative errors in derived coniferous/deciduous fractions are estimated to rangefrom 9–39% (table 3).We note that CanFI and the narrative descriptions data can provide forest species

information at ecoregional/sub-ecoregional level. Therefore, we can only assess the

Figure 8. 1:1 comparison for total black and red spruce (BS), trembling aspen (AS), whitepine (WP), and yellow birch (YB) areas at the ecoregion level between CanFI91/94 and thisstudy, for areas covered by CanFI91/94.

Maps of dominant tree species from remotely sensed and ground data 201

accuracy of the final dominant species maps at this level, as described in section 4.3.Clearly, there is a need to further validate these products at a higher spatialresolution, and this need should guide our future work.

Table 6. Total areas of dominant tree species groups estimated by this study and as reportedin CanFI91/94. Areas reported by this study include forested regions not included in CanFI91/94 but which were classified as forests on the SPOT-VGT land cover map of Cihlar et al.(2002).

Dominant tree species groups This study (Mha) CanFI (Mha)

Black and red spruce 57.4 39.7Other spruce 31.2 19.9White pine 1.4 1.0Jack lodgepole and shore pine 33.7 34.4Other pine 1.1 1.4Balsam amabilis grand subalpine fir 18.7 14.8Hemlock 5.0 4.5Douglas fir 4.4 4.4Larch 6.2 0.8Cedar and other coniferous 3.2 3.3Unspecified needleleaf 0.0 13.7All needleleaf 162.8 138.3

Trembling aspen 22.4 14.3Other poplar 8.5 3.4Yellow birch 1.5 1.4Other birch 14.3 7.3Sugar and black maple 3.1 3.7Other maple 2.2 2.2Other broadleaved species 8.5 9.6Unspecified broadleaf 0.0 11.5All broadleaf 60.7 53.7

Unclassified 0.0 26.4

All species 223.6 218.5

Table 5. Dominant tree species fraction estimates compared between this study andCanFI91/94 at the ecoregion level.

Dominant tree species group Regression slope r2 N

Black spruce and red spruce (BS) 0.89 0.91 148Other spruce (OS) 0.85 0.83 170White pine (WP) 0.75 0.91 63Jack lodgepole and shore pine (JP) 1.04 0.78 125Other pine (OP) 1.07 0.79 76Balsam amabilis grand and sub-alpine fir (BF) 0.81 0.80 142Hemlock (HK) 0.96 0.82 61Douglas fir (DF) 0.97 0.96 31Larch (LA) 0.37 0.48 142Cedar and other coniferous (OC) 0.99 0.86 55Trembling aspen (AS) 0.78 0.63 153Other poplar (OP) 0.53 0.63 146Yellow birch (YB) 0.97 0.79 38Other birch (OB) 0.64 0.60 154Sugar maple and black maple (SM) 1.03 0.85 35Other maple (OM) 1.02 0.63 39Other broadleaf species (OH) 1.07 0.96 77

202 G. Pavlic et al.

5. Concluding remarks

By integrating remote sensing observations, ground species composition informa-tion, and topographic data, 17 Canada-wide maps of dominant tree species groupswere developed. These results fill a data gap of Canada-wide species maps requiredby national studies of forest ecosystem services.Comparisons of total areas of coniferous/deciduous forests and dominant tree

species groups between this study and CanFI, as well as with species range maps ofFarrar (1995), showed good agreement at the ecoregion level. However, estimates ofdominant tree species fractions are not expected to be precise at a single pixel level.This is because they reflect dominant species composition at sub-ecoregion level, andtherefore should be most useful for studies concerned with the entire landmass ofCanada or large regions. Improvements in the spatial detail of dominant tree speciesfractions could be obtained both by using coniferous/deciduous fractions obtaineddirectly from Canada-wide Landsat TM/ETMþ land cover classification, and byusing more spatially detailed species composition information, such as collected instand-level forest inventories where these are carried out.

Acknowledgements

This study received financial support from the Programme for Energy Research andDevelopment (PERD) of Natural Resources Canada and the Government ResearchInitiative Programme (GRIP) of the Canadian Space Agency. The constructivecomments by anonymous reviewers greatly strengthen the manuscript. Dr. YuZhang and Darren Pouliot internally reviewed the manuscript.

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