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Assessing Fractional Cover in the Alpine Treeline Ecotone Using the WSL Monoplotting Tool and Airborne Lidar


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As forest cover in mountain areas impacts headwater properties like habitat extent and downstream water resources, it is important to assess and understand the changes that occur across forest transition zones like the alpine treeline ecotone (ATE). Such changes occur slowly and manifest at decadal to century time scales; however, the present benchmark spatial resolution for land cover analysis from oblique repeat photographs, 100 m, is insufficient to analyze anticipated changes in ATE over a century-scale. In this research note, fractional cover classification of the ATE is achieved through oblique photography analysis with the WSL Monoplotting Tool. Seven oblique photographs of the West Castle Watershed (Alberta, Canada), collected by the Mountain Legacy Project, were gridded to a 20-m resolution and assigned canopy cover classes by manual interpretation. Four canopy cover classes (i.e., no cover, low vegetation, partial canopy, full canopy) were compared to lidar-derived fractional cover. The extraction of canopy cover information from oblique photography at a resolution of 20 m introduces the ability to assess and quantify changes in the ATE using century-scale oblique photographic records. 2017
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Canadian Journal of Remote Sensing
Journal canadien de télédétection
ISSN: 0703-8992 (Print) 1712-7971 (Online) Journal homepage:
Assessing Fractional Cover in the Alpine Treeline
Ecotone Using the WSL Monoplotting Tool and
Airborne Lidar
David R. McCaffrey & Chris Hopkinson
To cite this article: David R. McCaffrey & Chris Hopkinson (2017) Assessing Fractional Cover
in the Alpine Treeline Ecotone Using the WSL Monoplotting Tool and Airborne Lidar, Canadian
Journal of Remote Sensing, 43:5, 504-512, DOI: 10.1080/07038992.2017.1384309
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Published online: 09 Oct 2017.
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, VOL. , NO. , –./..
Assessing Fractional Cover in the Alpine Treeline Ecotone Using the WSL
Monoplotting Tool and Airborne Lidar
David R. McCarey and Chris Hopkinson
Department of Geography, University of Lethbridge, Alberta Water & Environmental Science Building,  University Drive, Lethbridge, AB TK
M, Canada
Received  January 
Accepted  September 
As forest cover in mountain areas impacts headwater properties like habitat extent and downstream
water resources, it is important to assess and understand the changes that occur across forest
transition zones like the alpine treeline ecotone (ATE). Such changes occur slowly and manifest at
decadal to century time scales; however, the present benchmark spatial resolution for land cover
analysis from oblique repeat photographs, 100 m, is insucient to analyze anticipated changes in ATE
over a century-scale. In this research note, fractional cover classication of the ATE is achieved through
oblique photography analysis with the WSL Monoplotting Tool. Seven oblique photographs of the
West Castle Watershed (Alberta, Canada), collected by the Mountain Legacy Project, were gridded
to a 20-m resolution and assigned canopy cover classes by manual interpretation. Four canopy cover
classes (i.e., no cover, low vegetation, partial canopy, full canopy) were compared to lidar-derived
fractional cover. The extraction of canopy cover information from oblique photography at a resolution
of 20 m introduces the ability to assess and quantify changes in the ATE using century-scale oblique
photographic records.
La couverture forestière dans les régions montagneuses a un impact sur les propriétés des têtes
de bassin versant, telles que l’étendue des habitats et les ressources hydriques en aval. Il est donc
important d’évaluer et de comprendre les changements qui surviennent dans les zones de transition
forestières telles que l’écotone forestier alpin (EFA). Ces changements se produisent lentement et se
manifestent sur une échelle de temps décennale ou centennale. Cependant, le point de référence
actuelle en matière de résolution spatiale pour l’analyse de couverture terrestre avec photographies
obliques à répétition, 100 m, est insusant pour mesurer les changements anticipés dans les EFA à
l’échelle centennale. Cet article présente une classication de couverture terrestre fractionnaire pro-
duite par l’analyse de photographies obliques avec le WLS Monoplotting Tool. Sept photographies
obliques du bassin versant West Castle (Alberta, Canada), acquises par le Mountain Legacy Project,
ont été maillées à une résolution de 20 m et assignées à une classe de couverture forestière suivant
une interprétation manuelle. Quatre classes de couverture forestière (aucune couverture, végétation
basse, canopée partielle, pleine canopée) ont été comparées à une classication fractionnaire dérivée
du lidar. L’extraction d’informationsur la couverture forestière de photographies obliques à une résolu-
tion de 20 m rend l’évaluation et la quantication des changements dans les EFA à l’échelle centennale
Alpine treeline ecotone (ATE), the transition zone
between alpine tundra and closed canopy, is character-
ized by distinct patterns in forest structure; decreases
in mature tree height, stand density, and fractional
cover correlate with increases in elevation (Körner 2012;
Tranquill i ni 1979). Environmental factors inuencing
these forest structure patterns are varied (Case and Dun-
can 2014; Holtmeier and Broll 2005; Weiss et al. 2015),
and understanding the degree to which multi-scale inter-
actions between anthropogenic, orographic, and climatic
CONTACT David R. McCaffrey
factors aect shifts in ATE has relied on observation
methods, such as repeated plot measurements (Weiss
et al. 2015), dendrochronology (Liang et al. 2014), remote
sensing (Coops et al. 2013),andhistoricrecords(e.g.,
oblique photography; Hagedorn et al. 2014).
ATE observation methods are limited in the temporal
and spatial extents at which they can resolve change
(Danby 2011). For example, forest structure parameters
that characterize ATE, such as fractional cover, can be
observed at a high spatial resolution (1m)usingair-
borne lidar, but few extended lidar records presently exist
Copyright © CA SI
Downloaded by [David McCaffrey] at 09:22 01 November 2017
for periods longer than 20 years. Conversely, oblique
photograph records of ATE exist for periods exceeding
100 years (e.g., Trant et al. 2015), but quantitative analysis
of century-scale land cover change using oblique pho-
tographs has been restricted to low spatial resolutions
(100 m; Stockdale et al. 2015). In the Rocky Mountains,
where advance of ATE species, such as subalpine r (Abies
lasiocarpa), has been observed at 0.28 m yr1–0.62 m
yr1(Bekker 2005; Luckman and Kavanagh 2000), the
tography will depend on increasing the spatial resolution
of analysis above 100 m; for example, if ATE has advanced
on the order of 50 m in a century, in order to detect
change using a century scale photographic record, the
spatial resolution of analysis must be higher than 100 m.
This research note introduces a methodology that
assesses fractional cover in oblique photography, which
increases both the temporal period and spatial scale
of ATE observation when applied to historic repeat
photographs. Using a technique pioneered by Stockdale
et al. (2015), land cover in an oblique photograph can be
rasterized, enabling direct comparison between repeat
photographs. The present research is, in part, a replica-
tion of Stockdale et al. (2015), but distinguishes itself by
adding analysis, which is critical for the application of
the method to observations of ATE: (i)wedemonstrate
that the rasterization method can be executed at a spatial
scaleof20m;(ii) we intentionally selected oblique pho-
tographs with overlapping view elds to test correspon-
dence between images; (iii) we improve upon a general
linear model of spatial error in a manner which allows
selection of the image with lowest error in cases of multi-
pleobservation;and(iv) we validate manual classication
of canopy fractional cover from oblique photographs
against fractional cover measured by airborne lidar.
Quantitative area analysis of oblique photographs
Prior limitations of quantitative oblique photogra-
phy analysis have been overcome with the advent of
software like the WSL Monoplotting Tool (WSL-MT;
note: WSL is the German acronym for “Eidgenössische
Forschungsanstalt für Wald, Schnee und Landschaft,
the Swiss Federal Institute for Forest, Snow and Land-
scape Research), which produces georeferenced vector
data from oblique photographs using tie points between
oblique and aerial photographs, and high resolution
topographic data (Bozzini et al. 2012). Previous analyses
of oblique photographs to assess areas of change in the
ATE were mostly qualitative, relying on descriptions
of land cover change and estimations of spatial extent
(Butler and DeChano 2001;KlasnerandFagre2002;
Kullman and Öberg 2009;MoiseevandShiyatov2003;
Roush et al. 2007). Stockdale et al. (2015)introduced
a method of quantifying land cover change using the
WSL-MT and repeat photography from the Mountain
Legacy Project (MLP), a collection of over 120,000 his-
(1888–1958; Trant et al. 2015). The study compared esti-
mated coordinates of tie points used in WSL-MT camera
calibration with the coordinates of points that had been
projected from oblique to orthogonal perspective using
the software; the mean error between points (error vec-
tor length) was 14.7 m, while mean displacement error
(i.e., dierence between the centroid of the set of all test
points in a given image) was 2.9 m (Stockdale et al. 2015).
The high spatial resolution of airborne lidar makes it a
promising candidate for validation of oblique photograph
analysis, but at the time of writing, only a single study is
known to have validated land cover data generated from
the WSL-MT using vegetation measurements from air-
borne lidar (Kolecka et al. 2015). In that study, lidar-
derived estimates of vegetation height and canopy cover
were compared to areas of forest succession mapped from
oblique photographs, with an overall accuracy of 95%.
Oblique photographs
Research was conducted over the West Castle Watershed
(WCW), Alberta, Canada. WCW is located in the head-
waters of the Oldman River on the eastern slopes of the
Rocky Mountains, with an area of 103 km2(watershed
dened as upstream of the University of Lethbridge West
Castle Field Station, located at 49.35°N, 114.41°W),
and an elevation range of 1400–2600 m above sea
level. Aside from a small ski resort and village near the
and trail network in the valley bottoms, the forested
slopes demonstrate minimal anthropogenic disturbance,
infestation. Consequently, the WCW is an ideal study
area for assessing recent natural shifts in the treeline
ecotone in this part of the Canadian Rockies. Seven high-
resolution oblique photographs of WCW were selected
the spatial coverage of the valley while also providing
photographs were collected in August 2006, and geoloca-
tions for photograph origins were provided by the MLP
(Table 1 ).
Rasterized canopy cover data were generated from
oblique photographs using WSL-MT, following the
Downloaded by [David McCaffrey] at 09:22 01 November 2017
Tab le . Oblique photograph summary.
Photograph Number Elevation (m) Latitude Longitude Photograph Date
, °. °. July , 
, °. °. July , 
, °. °. July , 
, °. °. July , 
, °. °. July , 
, °. °. July , 
, °. °. July , 
method of Stockdale et al. (2015): (i) co-registered aerial
imagery (1.5 m, SPOT 6, acquired July 31, 2014, © 2014
CNES, licensed by BlackBridge Geomatics; purchased by
Planet Labs Inc., 2015) and topographic data (1 m DEM,
lidar collection described below) were used to calibrate
camera parameters for each of the 7 images; (ii)foreach
image, an iterative process of control point selection was
used to reduce 21 potential control points to 6 control
points with the least angle error—discarded control point
became ‘test points’ used in error analysis; (iii)thecamera
parameters were exported to ArcGIS 10.3 (Esri 2014),
where the 1 m DEM was used to create a viewshed for
the image (Figure 1b); (iv) a 20-m shnet (i.e., 400 m2
grid cells) was overlaid and clipped to the viewshed,
with any grid cells having less than 75% coverage (i.e.,
<300 m2)beingomitted(Figure 1c); (v)theWo r l d to
Pixel function of the WSL software was used to project
shnet grid cells from UTM coordinates to pixel coor-
dinates, so that the 20 m ×20 m grid cells were draped
over the oblique image (Figure 1d). Once in an oblique
projection, grid cells were manually assigned into 1 of 4
canopy cover classes based on observed canopy openness
and texture (Figure 1e). The 4 canopy cover classes were:
(i)No Cover—grid cells devoid of vegetation; (ii)Low
Veget a t i on—grid cells appear vegetated, but context and
texture suggest shrubs or krummholz, not upright trees
>2m;(iii)Partial Canopy—trees are present, but ground
is visible in >50% of the grid cell; (iv)Full Canopy—trees
cover >50% of a grid cell. Finally, classied oblique
images were converted back to orthogonal view for
comparative analysis (Figure 1f).
Visual estimates of canopy cover were completed by
a single trained interpreter. While it is well known that
manual photograph interpretation is subject to error
introduced by misregistration and interpreter bias, which
precludes single interpreter analysis, recent studies of
fractional cover assessment from aerial imagery have
established a multi-interpreter agreement using a second
interpreter, working on a subset (5%–10%) of the data
(Nowak and Greeneld 2012;Ucaretal.2016). We ran-
domly selected 5% of the observed grid cells, and used
a second interpreter to classify canopy cover using the
same 4-class criteria.
Error analysis
Error vector length and displacement errors were cal-
culated for each of the 7 photographs in the 2006 MLP
dataset, using the discarded test points from the camera
calibrations. Error vector length is the 3-D distance
between each test point and its projected counterpart,
and displacement error is the 3-D distance between the
centroid of the set of test points and the set of projected
points. Additionally, landscape level measurements of
error vector length and displacement were calculated
using all available test points (n=64), without stratifying
by image.
Using the Alberta Vegetation Inventory (Alberta
Environment and Parks 2012), vector data for known
areas of disturbance (e.g., former cut blocks, oil well pads,
roads, ski resort, and a small burn area) were aggregated
into a single layer, and any grid cells intersecting with this
disturbance layer were omitted. Grid cells that extended
above ridgelines or the horizon were omitted from analy-
sis, leaving a nal observation area of 38.5 km2, or 37.7%
of WCW.
To understand factors that contribute to error vector
length, Stockdale et al. (2015) modeled vector error
length as a function of distance from the camera origin,
and angle of viewing incidence. Angle of viewing inci-
dence is dened as the angle between a ray connecting
the camera origin to the control point, and a 10-m line
segment xed to the ground along the sight line of the
ray, with the control point as a midpoint. A general linear
model was executed in SPSS 24 (IBM 2016), using the
Error Vector Length (m)
=Intercept +βI+βD+βA,[1]
where Iis image number (used as a random factor),
Dis distance to camera, Ais the angle of viewing
incidence, and βis the model coecient for each
Additionally, an ‘observation-parameter routine’ was
constructed, which calculates the distance to the camera
and viewing incidence for any set of points on the DEM,
in ArcGIS 10.3 (ESRI 2014), allowing the modeled error
Downloaded by [David McCaffrey] at 09:22 01 November 2017
Figure . The oblique photograph to raster workflow, as described by Stockdale et al. (): (a) an oblique image of Mount Haig, in the
West Castle Watershed, copyright Mountain Legacy Project (); (b) orthogonal view shed of oblique Mount Haig image, using camera
calibration from WSL Monoplotting Tool; (c) a -m fishnet applied to the Mount Haig view shed; (d) fish net grid projected back to
oblique view using WSL World to Pixel function; (e) oblique image with canopy cover classification; and (f) orthogonal image with canopy
cover classification.
vector length to be applied at any observation grid cell in
the watershed.
MLP photographs with overlapping extents were
intentionally selected to test correspondence between
separate observations. Of the total observed area,
10.5 km2(27.2%) had multiple observations, which
enabled an assessment of the manual classication con-
sistency from dierent vantage points (Figure 2a,Ta b le 2).
Accuracy of canopy cover classications was assessed by
determining whether the minimum and maximum clas-
sication values for each grid cell agreed or disagreed. In
cases of disagreement between observations, the canopy
cover classication from the image with the lowest error
vector length, as modeled by the observation-parameter
routine, were selected.
Airborne lidar
An airborne lidar survey of WCW was own on Octo-
ber 18, 2014 with a Leica ALS70 and a minimal point
2at nominal altitude (1,300 m above
the mean ground surface elevation). Lidar point cloud
Downloaded by [David McCaffrey] at 09:22 01 November 2017
Figure . Multiple observations: (a) observation areas were viewed by either , , or  different oblique images and (b) areas with multiple
observation either agreed in all  or  observations, or disagreed.
processing and fractional cover analysis followed the
canopy-to-total returns method described in Hopkinson
and Chasmer (2009).Datawereclassiedintogroundand
non-ground using Ter ra s can (Terrasolid, Finland) and a
1-m DEM was interpolated from the ground-classied
points and aggregated using mean values to match the
20-m canopy cover classication grid cells. Fractional
cover was calculated using the LAStools suite (Isenburg
2013); data were height normalized, and lascanopy was
applied with a height threshold of 2.0 m and a step of
20 m, again matching canopy cover classication grid
(Figure 3d).
Fractional cover, as a metric, treats canopy cover as
the agreement between factional cover and manually
classied canopy cover, which has discrete, ordinal
classes, we needed to discretize the measurements of
fractional cover into 4 classes. No logical break points
existed a priori, so we used 3 common, unsupervised
discretization methods: equal frequency, equal range,
and k-means. We tested agreement between 4-class
manual interpretation and ordinal, binned classes of
fractional cover using Cohens K, weighted linearly
(Cohen 1968).
Tab le . Agreement of multiple observations.
Number of Observations Area (km) Percent of Observed Area
. .
Multiple Observations
Agree . .
Disagree . .
As the results may have been inuenced by expected
areas of homogenous full canopy cover at lower elevations
and no cover at higher elevations, each analysis was run
twice; once on all observed areas, and once restricted
to elevations between 1800 m–2300 m, where ATE is
Overall correspondence between the primary interpreter
and the secondary interpreter was 88.4%, and weighted
Cohen’s K showed substantial agreement between inter-
pretations (K =0.79, p<0.001). When elevations were
restricted to the more variable ATE region, correspon-
dence dropped to 74.1%, with weighted K again showing
substantial agreement (K =0.73, p<0.001).
Mean error vector length between test points ranged
from 2.0 m to 63.8 m per image, with a mean of 23.9 m
among the 7 images (Tab l e 3). Displacement ranged
from 0.8 m to 39.5 m, with a mean of 14.4 among the 7
images. In the landscape level analysis of 64 aggregated
points, mean error vector length was 21.7 m and mean
displacement was 7.0 m.
A general linear model of error vector length was
(i) 2 outlier points were identied and removed—these
outliers had error vector length values of 177.7 m and
192.1 m (the next highest value was 78.0 m), and occurred
in dierent images (photos 6 and 3, respectively); (ii)a
Shapiro-Wilk test demonstrated the data were not nor-
mally distributed (W=541, p<0.001)—the truncated
sample of 62 values responded to a common log trans-
formation, and a repeat of the Shaprio-Wilk test failed to
reject normality (W=9.65, p=0.076). We proceeded
Downloaded by [David McCaffrey] at 09:22 01 November 2017
Figure . West Castle Watershed area of interest: (a) minimum error vector length, as modeled by the GLM; (b) number of photograph
with lowest modeled error, used for canopy cover classification; (c) four classes of manual canopy cover classification; and (d) lidar-derived
fractional cover.
Tab le . Error analysis for WSL-MT camera calibration, error vector length, and modeled error.
No. of
Mean Angle
Error (°)
No. of Test
Mean Error Vector
Length (±SE)
Error (m)
Mean Distance From Camera
(m) (range)
Mean Angle of Viewing
Incidence (°)(range)
. . (.) . ,. (,.–,.) . (.–.)
.  . (.) . ,. (,.–,.) . (.–.)
. . (.) . ,. (,.–,.) . (.–.)
. . (.) . ,. (,.–,.) . (.–.)
. . (.) . ,. (,.–,.) . (.–.)
. . (.) . ,. (,.–,.) . (.–.)
.  . (.) . ,. (,.–,.) . (.–.)
Mean . . . (.) . ,. .
Landscape  . (.) .
 . (.) .
Model Error Vector Length , . (<.) .–.
Downloaded by [David McCaffrey] at 09:22 01 November 2017
Figure . Lidar-derived fractional cover values were discretized into four ordinal groups using three methods (i.e., equal frequency, equal
range, and k-means); the boxplot depicts the IQR for each of these three groups (in blue shades) and compares their fractional cover
distributions against those generated from manual classifications (in red).
Tab le . Agreement between manual classifications and discretized fractional cover.
% C.I.
% C.I. P Value
% C.I.
% C.I. P Value
Equal frequency . . . . . <. . . . . . <.
Equal range . . . . . <. . . . . . <.
K-means . . . . . <. . . . . . <.
Manual breaks . . . . . <. . . . . . <.
with the general linear model, which yielded the following
log Error Vector Length (m)
=0.992 +βI+0.000077D+0.009A.[2]
All factors were signicant at α=0.05, except for
distance to camera (D;f=1.278, p=0.263). The
observation-parameter routine was used to measure the
distance to camera and angle of viewing incidence for
each grid cell in the analysis produced a surface map
of the modeled error vector length (Figure 3a). Mean
error vector length for the model was 14.6 m, and ranged
between0.9mand75.7m(Ta b le 3); these values were
develop the model.
no area in the watershed was observed in more than 3
dierent images (Figure 2a). Comparison of multiple
observation areas showed that 78.4% of the grid cells
agreed between observations, while at least 1 classi-
cation value disagreed in 21.6% of cases (Figure 2b,
Table 2 ). Agreement between manual cover classica-
tions and fractional cover classes was generally consistent
across discretization methods (Figure 4); 4-class accu-
racy ranged from 43.3%–47.0%, and weighted K values
showing moderate agreement (K =0.42–0.43, p<0.001;
Table 4 ). In the ATE, 4-class accuracy was only slightly
reduced from the full watershed analysis, ranging from
39.4%–46.0%, with weighted K values showing fair
agreement (K =0.35–0.36, p<0.001; Tab le 4).
Discussion and conclusion
The analyses indicated that fractional cover across the
ATE can be discriminated from oblique imagery at a res-
placement error were both substantially higher than error
values calculated in Stockdale et al. (2015); our study cal-
culated a mean error vector length of 23.9 m and a land-
scape level displacement error of 7.0 m, while Stockdale
et al. (2015)found14.4mand2.9merrors,respectively.
length and displacement error were more comparable to
the previous study, at 16.5 m and 5.9 m. Several possi-
bilities exist for the larger error observed in the present
study. Stockdale had a larger sample size of test points
Downloaded by [David McCaffrey] at 09:22 01 November 2017
(n=121), which resulted from fewer omissions in test
point projection from WSL-MT. It should be noted that
these omissions may reect higher error vector lengths
than those seen in processed test points, thus making
actual error vector length in the present study higher than
what is reported. Another potential cause of the discrep-
ancy between error estimates is that aerial imagery used
for control point selection in the previous study was at a
resolution of 0.5 m, 3 ×greater resolution than the 1.5 m
SPOT 6 data used in the present study. Higher resolution
aerial imagery could have improved control point place-
ment, reduced angle error, and contributed to a lower
mean error vector length. Regardless of the discrepancy,
in the present study mean error vector length was com-
parable to canopy cover grid cell resolution and mean
displacement error remained substantially below this res-
olution, demonstrating that fractional cover can be ras-
terized from oblique photographs at a resolution of 20 m.
This spatial resolution is an important threshold to reach
for the application of the method to ATE observations, as
it corresponds to the area of most forest mensuration plots
(400 m2), and permits cataloguing of changes in the ATE
given the expected rate of advance over the century scale
observation period permitted by repeat photography.
Comparison of grid cells with multiple observations
showed that canopy cover classication disagreed in
21.6% of cases. Disagreement cases were resolved using
modeled error vector length, which produced values
comparable to those in the observed error vector length;
observed mean error vector length for the 62 test points
used for model development was 16.5 m, with a range
of 1.9 m–78.0 m, while modeled values had a mean
of 14.6 m and a range of 0.9 m–75.7 m (Table 3 ). The
previous study found that image number (I), distance
to camera (D), and angle of viewing incidence (A)all
contributed signicantly to the model (i.e., p<0.05), but
not signicant. These results demonstrate that models
of error vector length can be useful in resolving cases of
disagreement in oblique photograph classication, and
primary factor aecting displacement error.
Manual classications of fractional cover from the
oblique photographs were, in part, validated using lidar-
derived fractional cover. Fractional cover distributions
from manual classications had increasing median val-
ues with each ordinal class, in both the full watershed
and ATE restricted analyses. While accuracy between
the discretized fractional cover classes and the manual
classes was generally low, peaking at 47.0%, it is worth
considering this may have resulted from the fact that the
discretization methods used were theoretical, and did
not necessarily reect real-world bins of fractional cover.
For example, if we arrange lidar-derived fractional cover
values in order, and partition them into bins with equal
frequency ratios as those seen in the manual classica-
tions, we reach accuracy upwards of 64.7% (see Table 4 ,
Manual breaks). While this method is not a defensible
validation, as it assumes that the manual classications
analysis rely on partition points that are in some ways
With an abundance of repeat oblique photography
in the Canadian Rocky Mountains (Trant et al. 2015),
future research, which combines quantitative analysis of
oblique photography with lidar-derived forest structure
data, can increase the spatial resolution and temporal
extent of ATE monitoring. This is important as we con-
tinue to explore the impacts of climatic change, natural
and anthropogenic disturbances on forested mountain
ecosystems, and downstream water resources.
their helpful comments. We also wish to thank Dr. Eric Higgs
for providing oblique photographs, and Dr. Claudio Bozzini
for instruction on the WSL monoplotting tool. Additionally,
we gratefully acknowledge Josh Montgomery for acting as the
second photograph interpreter.
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... The availability of the WSL monoplotting tool from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) [21,22] has already led to several studies that have been able to quantify environmental longterm changes in alpine areas using individual historical terrestrial oblique photographs. Research has included land-cover/vegetation change [21][22][23][24][25][26][27][28], natural hazards [29,30], LIA glacier extents [31] and rock glacier movement [32]. However, no studies have shown the long-term mapping of surface changes of LIA lateral moraines until the second half of the 20th century using historical terrestrial photos. ...
... The accuracy and precision of the digital monoplotting results are influenced by several factors [21][22][23][24][25][26][28][29][30][31][32] including the distribution and number of the GCPs, the accuracy and precision of the DTM, the accuracy of the estimated camera parameters (interior and exterior orientation of the camera) and the angle of incidence between the image ray and the DTM. Furthermore, the quality of the historical terrestrial photos is not comparable to modern photos (e.g., lens distortion), further reduced by the way they were stored in the archives (e.g., stains, scratches), influencing the potentially achievable accuracy. ...
... Studies using photos from the Mountain Legacy Project [23,25] show clearly higher error values, but these studies used photos that cover larger and wider areas in high mountain regions (Rocky Mountains, Canada). Therefore, they are prone to higher error values (similar to the photos from the SEHAG project used in this study), as the accuracy decreases with increasing distance from the camera, due to the uncertainties in the orientation (angle). ...
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Aerial photographs of the European Alps usually only reach back to the middle of the 20th century, which limits the time span of corresponding studies that quantitatively analyse long-term surface changes of proglacial areas using georeferenced orthophotos. To the end of the Little Ice Age, this leads to a gap of about 100 years. Using digital monoplotting and several historical terrestrial photographs, we show the quantification of surface changes of a Little Ice Age lateral moraine section until the late second half of the 19th century, reaching a total study period of 130 years (1890–2020). The (initial) gully system expands (almost) continuously over the entire study period from 1890 to 2020. Until 1953, the vegetation-covered areas also expanded (mainly scree communities, alpine grasslands and dwarf shrub communities), before decreasing again, especially between 1990 and 2003, due to large-scale erosion within the gully system. Furthermore, our results show that the land-cover development was impacted by temperature and precipitation changes. With the 130-year study period, we contribute to a substantial improvement in the understanding of the processes in the proglacial by analysing the early phase and thus the immediate response of the lateral moraine to the ice exposure.
... Researchers from the Swiss Federal Research Institute WSL have developed the WSL Monoplotting Tool (WSL-MPT) which allows to process single landscape photographs in a very user-friendly way (Bozzini et al. 2012). So far, the WSL-MPT has been used for the quantitative analysis of natural hazards (Bozzini et al. 2012, Conedara et al. 2018, glacial processes (Wiesmann et al. 2012, Scapozza et al. 2014) and land cover changes (Stockdale et al. 2015, 2019, McCaffrey and Hopkinson 2017, 2020, Gabellieri and Watkins 2019. ...
... In such cases, the extraction of precise vectorized geodata is preferable over a raster-based approach. With respect to vector data, only the spatial accuracy of points (Stockdale et al. 2015, McCaffrey andHopkinson 2017) and line features (Wiesmann et al. 2012) has been tested so far, while the reliability of polygon area has not been assessed. ...
... Former studies have performed the georectification based on six control points (e.g. Stockdale et al. 2015, McCaffrey andHopkinson 2017). In the present study, 12 GCPs per image were chosen as this gave a more even distribution of points across the entire image. ...
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... These experiments were conducted on photo pairs from the Mountain Legacy Project, a collection of over 120,000 historic survey images of the Canadian Rockies (1888-1958), of which over 6000 have 21 st -century repeat photographs available under creative commons license [48]. Previous research, validated using airborne lidar, established that fractional cover classes could be assessed from oblique imagery at a spatial resolution of 20 m, using the WSL-MT [49]. ...
... We used a technique to assess fractional cover from oblique photographs, described in [49], to observe postfire vegetative change in repeat photographs of a watershed in the Canadian Rockies. We sought to determine: (1) if there were observable differences in canopy cover change between fire-exposed and non-fire-exposed regions of the watershed, (2) if changes in canopy cover correlate to topographic patterns that are consistent with expected edaphic controls on regrowth in the region (e.g., less regrowth on south-facing aspects), and (3) if it was possible to detect the rate of ATE advance in non-fire-exposed areas, where ATE position is regulated by climate. ...
... Photograph pairs were selected to maximize the spatial coverage of the observed area of WCW. Using the same set of photographs, it was determined that 38.5 km 2 (37.7%) of the watershed was observable in these images [49] (Figure 2). Remote Sens. 2020, 12, x FOR PEER REVIEW 4 of 22 ...
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Alpine Treeline Ecotone (ATE), the typically gradual transition zone between closed canopy forest and alpine tundra vegetation in mountain regions, displays an elevational range that is generally constrained by thermal deficits. At landscape scales, precipitation and moisture regimes can suppress ATE elevation below thermal limits, causing variability in ATE position. Recent studies have investigated the relative effects of hydroclimatic variables on ATE position at multiple scales, but less attention has been given to interactions between hydroclimatic variables and disturbance agents, such as fire. Advances in monoplotting have enabled the extraction of canopy cover information from oblique photography. Using airborne lidar, and repeat photography from the Mountain Legacy Project, we observed canopy cover change in West Castle Watershed (Alberta, Canada;~103 km 2 ; 49.3 • N, 114.4 • W) over a 92-year period (1914-2006). Two wildfires, occurring 1934 and 1936, provided an opportunity to compare topographic patterns of mortality and succession in the ATE, while factoring by exposure to fire. Aspect was a strong predictor of mortality and succession. Fire-exposed areas accounted for 83.6% of all mortality, with 72.1% of mortality occurring on south-and east-facing slope aspects. Succession was balanced between fire-exposed and unburned areas, with 62.0% of all succession occurring on north-and east-facing slope aspects. The mean elevation increase in closed canopy forest (i.e., the lower boundary of ATE) on north-and east-facing undisturbed slopes was estimated to be 0.44 m per year, or~44 m per century. The observed retardation of treeline advance on south-facing slopes is likely due to moisture limitation.
... Recognizing the great value of monoplotting, handy software and codes have been created for the geoscience community, including the OP-XFORM project (Aschenward, Leichter, Tasser, & Tappeiner, 2001), the JUKE method (Corripio, 2004), Georeferencing oblique terrestrial photography (Mitishita, Machado, Habib, & Gonçalves, 2004), the 3D Monoplotter (Fluehler, Niederoest, & Akca, 2005), and the DiMoTeP (Conedera, 2018). Recently, the WSL Monoplotting Tool (WSL-MPT) developed by the Swiss Federal Research Institute (WSL) is gaining popularity and has been applied to the quantitative analysis of natural hazards (Scapozza, Lambiel, Bozzini, Mari, & Conedera, 2014;Triglav-Čekada, Radovan, Gabrovec, & Kosmatin-Fras, 2011), glacial processes (Stockdale, Bozzini, Macdonald, & Higgs, 2015), and land cover changes (Gabellieri & Watkins, 2019;McCaffrey & Hopkinson, 2017;Stockdale, Bozzini, Macdonald, & Higgs, 2015). A similar tool called Pic2map, leveraging the convenience of the Geographic Information System (GIS) software QGIS, shows a strong rising trend (McCaffrey & Hopkinson, 2020). ...
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Urban flooding is becoming a common and devastating hazard, which causes life loss and economic damage. Monitoring and understanding urban flooding in a highly localized scale is a challenging task due to the complicated urban landscape, intricate hydraulic process, and the lack of high-quality and resolution data. The emerging smart city technology such as monitoring cameras provides an unprecedented opportunity to address the data issue. However, estimating water ponding extents on land surfaces based on monitoring footage is unreliable using the traditional segmentation technique because the boundary of the water ponding, under the influence of varying weather, background, and illumination, is usually too fuzzy to identify, and the oblique angle and image distortion in the video monitoring data prevents geor-eferencing and object-based measurements. This paper presents a novel semi-supervised segmentation scheme for surface water extent recognition from the footage of an oblique monitoring camera. The semi-supervised segmentation algorithm was found suitable to determine the water boundary and the monoplotting method was successfully applied to georeference the pixels of the monitoring video for the virtual quantification of the local drainage process. The correlation and mechanism-based analysis demonstrate the value of the proposed method in advancing the understanding of local drainage hydraulics. The workflow and created methods in this study have a great potential to study other street-level and earth surface processes.
... A limitation of repeat photography is that oblique imagery is difficult to analyze quantitatively, as spatial scale varies with perspective in the image (Roush et al. 2007); pixels in the foreground cover a smaller area than pixels in the background, and oblique photographs cannot be orthorectified. However, this issue has been resolved using a fishnet monoplotting technique (McCaffrey and Hopkinson 2017;Stockdale et al. 2015), and software courtesy of the WSL (Bozzini et al. 2012) (Note: WSL is the German acronym for "Eidgen€ ossische Forschungsanstalt f€ ur Wald, Schnee und Landschaft," the Swiss Federal Institute for Forest, Snow and Landscape Research). Using the WSL software, common tie points are identified between oblique imagery and high-resolution orthogonal imagery. ...
Historic changes in Alpine Treeline Ecotone were modeled using 21 topographic, climatic, geologic, and disturbance variables in a random forest model. Airborne LiDAR and oblique historic repeat photography were used to identify changes in canopy cover in the West Castle Watershed (WCW), Alberta, Canada (49.3 N, 114.4 W). A Random Forest model was trained on $30% of the watershed which was observable in oblique imagery, then used for a spatial extension to predict change classes in the unobserved regions of the watershed. Overall accuracy of the model was 77.3% and kappa showed moderate agreement at 0.56. The relative strength of each prediction variable was compared using permutation importance. Fire exposure, annual temperature, and annual solar radiation were the highest-ranking variables; canopy cover decreases on warm, fire-exposed aspects at high elevations, and increases on cool, non-fire-exposed aspects.
... We found that, as compared to the results from the orthophotos, classification of oblique photos overestimated closed canopy forest; 13% of the landscape that was called "CF" in the oblique images was called WD in the ortho view. Another source of disagreement was due to increased displacement of some grid cells as the angle of viewing becomes more oblique (Stockdale et al. 2015;McCaffrey and Hopkinson 2017). This resulted in different locations on the landscape being compared because, while the grid cell might be located on a patch of trees in the oblique image, this same grid cell might be placed in the adjacent clearing in an ortho image. ...
... Higher elevation areas experienced significant conversion of meadows and grasslands to forest, and this is consistent with other studies showing treeline advancement throughout the Rocky Mountains in the twentieth century (Luckman and Kavanagh 2000, Klasner and Fagre 2002, Shaw 2009, Elliott 2011, McCaffrey and Hopkinson 2017. We also saw much of the lowest elevation areas (agricultural zone) transitioned to earlier seral stages. ...
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We used repeat oblique photography to quantify and determine the drivers of vegetation change, particularly forest closure and encroachment, in the Rocky Mountains of southern Alberta, Canada from the beginning of the 20 th century to the present. We classified the landscape into seven distinct vegetation types (closed canopy conifer-, broadleaf deciduous-, or mixedwood-forest, open canopy woodlands, shrublands, grasslands and meadows, non-vegetated), and assessed vegetation change between the two time periods. We found that closed canopy coniferous-, broadleaf deciduous-, and mixedwood-forests increased on an area basis by 35%, 45% and 80%, respectively over this time period; concomitantly, grasslands and open canopy woodlands declined by 25% and 39%, respectively.
... Similar achievement potential and limitations of the MPT_2.0 in terms of usefulness and achievable precision have been reported in independent scientific studies in the field of historical landscape reconstructions [36] and treeline ecotone dynamics [37]. ...
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Urban flooding is becoming a common and devastating hazard to cause life loss and economic damage. Monitoring and understanding urban flooding in the local scale is a challenging task due to the complicated urban landscape, intricate hydraulic process, and the lack of high-quality and resolution data. The emerging smart city technology such as monitoring cameras provides an unprecedented opportunity to address the data issue. However, estimating the water accumulation on the land surface based on the monitoring footage is unreliable using the traditional segmentation technique because the boundary of the water accumulation, under the influence of varying weather, background, and illumination, is usually too fuzzy to identify, and the oblique angle and image distortion in the video monitoring data prevents georeferencing and object-based measurements. This paper presents a novel semi-supervised segmentation scheme for surface water extent recognition from the footage of an oblique monitoring camera. The semi-supervised segmentation algorithm was found suitable to determine the water boundary and the monoplotting method was successfully applied to georeference the pixels of the monitoring video for the virtual quantification of the local drainage process. The correlation and mechanism-based analysis demonstrates the value of the proposed method in advancing the understanding of local drainage hydraulics. The workflow and created methods in this study has a great potential to study other street-level and earth surface processes.
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While aerial photography and satellite imagery are the usual data sources used in remote sensing, land based oblique photographs can also be used to measure ecological change. By using such historical photographs, the time frame for change detection can be extended into the late 1800s and early 1900s, predating the era of aerial imagery by decades. Recent advancements in computing power have enabled the development of techniques for georeferencing oblique angle photographs. The WSL Monoplotting Tool is a new piece of software that opens the door to analyzing such photographs by allowing for extraction of spatially referenced vector data from oblique photographs. A very large repeat photography collection based on the world's largest systematic collection of historical mountain topographic survey images, the Mountain Legacy Project, contains >6000 high resolution oblique image pairs showing landscape changes in the Rocky Mountains of Alberta between ca. 1900 – today. We used a subset of photographs from this collection to assess the accuracy and utility of the WSL Monoplotting Tool for georeferencing oblique photographs and measuring landscape change. We determined that the tool georeferenced objects to within less than 15 m of their real world 3D spatial location, and the displacement of the geographic center of over 121 control points was less than 3 m from the real world spatial location. Most of the error in individual object placement was due to the angle of viewing incidence with the ground (i.e., low angle/highly oblique angles resulted in greater horizontal error). Simple rules of control point selection are proposed to reduce georeferencing errors. We further demonstrate a method by which raster data can be rapidly extracted from an image pair to measure changes in vegetation cover over time. This new process permits the rapid evaluation of a large number of images to facilitate landscape scale analysis of oblique imagery.
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Secondary forest succession on abandoned agricultural land has played a significant role in land cover changes in Europe over the past several decades. However, it is difficult to quantify over large areas. In this paper, we present a conceptual framework for mapping forest succession patterns using vegetation structure information derived from LiDAR data supported by national topographic vector data. This work was performed in the Szczawnica commune in the Polish Carpathians. Using object-based image analysis segments of no vegetation, and sparse/dense low/medium/high vegetation were distinguished and subsequently compared to the national topographic dataset to delineate agricultural land that is covered by vegetation, which indicates secondary succession on abandoned fields. The results showed that 18.7% of the arable land and 40.4% of grasslands, that is 31.0% of the agricultural land in the Szczawnica commune, may currently be experiencing secondary forest succession. The overall accuracy of the approach was assessed using georeferenced terrestrial photographs and was found to be 95.0%. The results of this study indicate that the proposed methodology can potentially be applied in large-scale mapping of secondary forest succession patterns on abandoned land in mountain areas.
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This paper presents examples of environmental changes in the Canadian Rockies in the context of a 1.5 degreesC increase in mean annual temperatures over the last 100 years. During this period increases in winter temperatures have been more than twice as large as those during spring and summer. Glacier cover has decreased by at least 25% during the 20th century and glacier fronts have receded to positions last occupied ca. 3000 years ago. These two lines of evidence suggest that the climate of the late 20th century is exceptional in the context of the last 1000 to 3000 years. Detailed studies in three closely located upper treeline sites document variable responses of vegetation to climate change that reflect species differences as well as local differences in microclimate and site conditions. Treeline has advanced upslope in response to climate warming, but site and species differences control the rate and nature of the advance. Human impacts on the environment compound the changes due to climate warming. Historic photographs indicate significant changes in the type and density of forest cover due to the absence of significant forest fires within these National Parks during the last 70-80 years. The visual impact of these changes, which partially reflects a policy of fire suppression, is far greater than the impact of changes associated with more direct tourist-related impacts. It is therefore important that monitoring programs examine vegetation changes over the entire landscape rather than focussing exclusively on supposedly climate-sensitive sites.
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Since its invention in the first half of the nineteenth century, photography has assumed a leading role as a means for documenting the real world. With the improvement of technology, photography developed into photogrammetry, enabling the mapping and georeferencing of landscape elements beginning with stereo photographs. With the introduction of aerial photography, terrestrial oblique photography became obsolete for cartographic purposes and was nearly forgotten by most specialists in photogrammetry. In recent times, the improvement of computing power and the production of high resolution Digital Elevation Models has made the spatial georeferincing of single oblique pictures (monoplotting) more approachable. In this paper, we focus on a new monoplotting tool developed by our research group and we illustrate the basic concept, the solutions implemented and options as well as the results of a case study on land-use and vegetation evolution over a 100-year period. The tool has been conceived to georeference ordinary individual photographs in order to orthorectify the visible landscape or to produce and export map layers (e.g. georeferenced vector data) by drawing them directly on these pictures. The basic requirements of the system are the digital version of the historical picture, the DEM of the depicted landscape, the real-world coordinates of a suitable number of control points unambiguously 501 A New Monoplotting Tool to Extract Georeferenced Vector Data and Orthorectified Raster Data from Oblique Non-Metric Photographs recognizable on the picture, and – suitable but not mandatory-the real-world coordinates of the precise shooting point and of the centre of the picture.
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Birch (Betula) trees and forests are found across much of the temperate and boreal zones of the Northern Hemisphere. Yet, despite being an ecologically significant genus, it is not well studied compared to other genera like Pinus, Picea, Larix, Juniperus, Quercus, or Fagus. In the Himalayas, Himalayan birch (Betula utilis) is a widespread broadleaf timberline species that survives in mountain rain shadows via access to water from snowmelt. Because precipitation in the Nepalese Himalayas decreases with increasing elevation, we hypothesized that the growth of birch at the upper timberlines between 3,900 and 4,150 m a.s.l. is primarily limited by moisture availability rather than by low temperature. Toverify this assumption, a total of 292 increment cores from 211 birch trees at nine timberline sites were taken for dendroecological analysis. The synchronous occurrence of narrow rings and the high inter series correlations within and among sites evidenced a reliable cross-dating and a common climatic signal in the tree-ring width variations. From March-May, all nine tree-ring width site chronologies showed a strong positive response to total precipitation and a less strong negative response to temperature. During the instrumental meteorological record (from 1960 to the present), years with a high percentage of locally missing rings coincided with dry and warm pre-monsoon seasons. Moreover, periods of below-average growth are in phase with well-known drought events all over monsoon Asia, showing additional evidence that Himalayan birch growth at the upper timberlines is persistently limited by moisture availability. Our study describes the rare case of a drought-induced alpine timberline that is comprised of a broadleaf tree species.
Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1,000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a 1.83 m square grid of points embedded within 0.04 ha circular plots. The imagery products included aerial photography from the U.S. Department of Agriculture National Agricultural Imagery Program (viewed within ArcGIS), and Google Earth imagery. For Tallahassee, Florida, the estimate of tree canopy cover was 48.6 to 49.1% using Google Earth imagery and 44.5 to 45.1% using NAIP imagery within ArcGIS. Statistical tests suggested that the two sampling approaches produced significantly different estimates using the two different imagery sources. For Tacoma, Washington, the estimated tree canopy cover was about 19.2 to 20.0% using Google Earth imagery and 17.3 to 18.1% when using NAIP imagery in ArcGIS. Here, there seemed to be no significant difference between the random point-based sampling efforts when used with the two different image sources, while the opposite was true when using the plot/grid sampling approach. However, our findings showed some similarities between the two sampling approaches; hence, the random point-based sampling approach might be preferred due to the time and effort required, and because fewer opportunities for classification problems might arise. Continuous review of urban canopy cover estimation procedures suggested by organizations such as the Climate Action Reserve and others can provide society with information on the accuracy and effectiveness resource assessment methods employed for making wise decisions about climate change and carbon management.
Alpine treelines mark the low-temperature limit of tree growth and occur in mountains world-wide. Presenting a companion to his book Alpine Plant Life, Christian Körner provides a global synthesis of the treeline phenomenon from sub-arctic to equatorial latitudes and a functional explanation based on the biology of trees. The comprehensive text approaches the subject in a multi-disciplinary way by exploring forest patterns at the edge of tree life, tree morphology, anatomy, climatology and, based on this, modelling treeline position, describing reproduction and population processes, development, phenology, evolutionary aspects, as well as summarizing evidence on the physiology of carbon, water and nutrient relations, and stress physiology. It closes with an account on treelines in the past (palaeo-ecology) and a section on global change effects on treelines, now and in the future. With more than 100 illustrations, many of them in colour, the book shows alpine treelines from around the globe and offers a wealth of scientific information in the form of diagrams and tables.
Multiple environmental factors contribute to the spatial and compositional character and elevational patterns of alpine treeline ecotones (ATEs), and the relative influence of these factors is scale dependent and spatially variable. Frameworks detailing the hierarchical structure of the ATE have been developed to characterize scale dependencies of the pattern and controls of treeline, but this topic has not been studied across a broad range of scales (e.g., from the hillslope to the region). This research directly examines scaling by comparing relationships among treeline elevations and a set of possible controls as geographic extent is varied. The data set used for this research consists of elevational data at the ATE and a set of hypothesized controls for 1,006 sites in twenty-six mountain ranges across the Western United States. The response and predictor variables are quantified from digital data sets using geographic information systems and remote sensing methodologies and then analyzed using a Mantel test framework. Results generally support, and add empirically derived detail to, existing theoretical frameworks, with climatic controls (i.e., variables characterizing temperature and precipitation) having higher correlations with ATE elevation at coarser scales and topographic variables having higher correlations at finer scales. These scale relations support the conceptual hierarchical frameworks that have been proposed, and they are useful guides of covariate selection for future ATE modeling endeavors.
Using sequential aerial photography, we identified changes in the spatial distribution of subalpine fir (Abies lasiocarpa) habitat at the alpine treeline ecotone. Six 40-ha study sites in the McDonald Creek drainage of Glacier National Park contained subalpine fir forests that graded into alpine tundra. Over a 46-yr period, altitudinal changes in the location of alpine treeline ecotone were not observed. However, over this 46-yr period the area of krummholz, patch-forest, and continuous canopy forest increased by 3.4%, and tree density increased within existing patches of krummholz and patch-forest. Change in subalpine fir vegetation patterns within 100 m of trails was also compared to areas without trails. Within 100 m of trails, the number of small, discrete krummholz stands increased compared to areas without trails, but there was no significant change in total krummholz area. We used historical terrestrial photography to expand the period (to 70 yr) considered. This photography supported the conclusions that a more abrupt ecotone transition developed from forest to tundra at alpine treeline, that tree density within forested areas increased, and that krummholz became fragmented along trails. This local assessment of fine-grained change in the alpine treeline ecotone provides a comparative base for looking at ecotone change in other mountain regions throughout the world.