Project

Northern Canada Studies

Goal: Human activity zone of influence on barren-land caribou. Assessment and mapping of biomass and Leaf Area Index (LAI). Lichen mapping for caribou habitat.

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Shahab Jozdani
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Illumination variations in non-atmospherically corrected high-resolution satellite (HRS) images acquired at different dates/times/locations pose a major challenge for large-area environmental mapping and monitoring. This problem is exacerbated in cases where a classification model is trained only on one image (and often limited training data) but applied to other scenes without collecting additional samples from these new images. In this research, by focusing on caribou lichen mapping, we evaluated the potential of using conditional Generative Adversarial Networks (cGANs) for the normalization of WorldView-2 (WV2) images of one area to a source WV2 image of another area on which a lichen detector model was trained. In this regard, we considered an extreme case where the classifier was not fine-tuned on the normalized images. We tested two main scenarios to normalize four target WV2 images to a source 50 cm pansharpened WV2 image: (1) normalizing based only on the WV2 panchromatic band, and (2) normalizing based on the WV2 panchromatic band and Sentinel-2 surface reflectance (SR) imagery. Our experiments showed that normalizing even based only on the WV2 panchromatic band led to a significant lichen-detection accuracy improvement compared to the use of original pansharpened target images. However, we found that conditioning the cGAN on both the WV2 panchromatic band and auxiliary information (in this case, Sentinel-2 SR imagery) further improved normalization and the subsequent classification results due to adding a more invariant source of information. Our experiments showed that, using only the panchromatic band, F1-score values ranged from 54% to 88%, while using the fused panchromatic and SR, F1-score values ranged from 75% to 91%.
Liming He
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Sylvain G Leblanc
added a research item
Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily rely on pixel DN values for classification.However, the limited spectral range of ground photos requires additional characteristics to differentiate lichen from spectrally similar objects, such as bright logs. By applying a neural network to tiles of a UAV orthomosaics, additional characteristics, such as surface texture and spatial patterns, can be used for inferences. Our methodology used a neural network (UAV LiCNN) trained on ground photo mosaics to predict lichen in UAV orthomosaic tiles. The UAV LiCNN achieved mean user and producer accuracies of 85.84% and 92.93%, respectively, in the high lichen class across eight different orthomosaics. We compared the known lichen percentages found in 77 vegetation microplots with the predicted lichen percentage calculated from the UAV LiCNN, resulting in a R2 relationship of 0.6910. This research shows that AI models trained on ground photographs effectively classify lichen in UAV orthomosaics. Limiting factors include the misclassification of spectrally similar objects to lichen in the RGB bands and dark shadows cast by vegetation.
Sylvain G Leblanc
added a research item
Arctic temperatures have increased at almost twice the global average rate since the industrial revolution. Some studies also reported a further amplified rate of climate warming at high elevations; namely, the elevation dependency of climate change. This elevation-dependent climate change could have important implications for the fate of glaciers and ecosystems at high elevations under climate change. However, the lack of long-term climate data at high elevations, especially in the Arctic, has hindered the investigation of this question. Because of the linkage between climate warming and plant phenology changes and remote sensing’s ability to detect the latter, remote sensing provides an alternative way for investigating the elevation dependency of climate change over Arctic mountains. This study investigated the elevation-dependent changes to plant phenology using AVHRR (Advanced Very High Resolution Radiometer) time series from 1985 to 2013 over five study areas in Canada’s Arctic. We found that the start of the growing season (SOS) became earlier faster with an increasing elevation over mountainous study areas (i.e., Sirmilik, the Torngat Mountains, and Ivvavik National Parks). Similarly, the changes rates in the end of growing season (EOS) and the growing season length (GSL) were also higher at high elevations. One exception was SOS in the Ivvavik National Park: “no warming trend” with the May-June temperature at a nearby climate station decreased slightly during 1985–2013, and so no elevation-dependent amplification.
Sylvain G Leblanc
added a research item
Mining activities in Canada’s pristine Arctic (e.g., driving on unpacked roads, blasts, rock grinding, diesel combustion, and garbage incineration) could add local sources of airborne fine particulate matter with a diameter of < 2.5 μm (PM2.5) to their surrounding area. The increase in PM2.5 above the background level around a mine represents a potential disturbance to caribou. To quantify the spatial distribution of the elevated PM2.5, we investigated three different sampling schemes to measure PM2.5 concentration using a portable monitor. We found that the best sampling scheme was to use the regional background PM2.5 as the reference and analyze the anomaly of PM2.5 measured at sites around the mine complex from the background level. The regional background PM2.5 values were measured at the Daring Lake Tundra Research Station during 2018 and 2019. Our results indicated that the background PM2.5 was not a low and constant value but varied with rain events, wind direction, and the impacts of forest fire smoke. After excluding periods affected by forest fires smokes, we found the background PM2.5 was close to 0 μg m⁻³ for the first few hours after rain, and then increased logistically with the time after rain (tar) to the maximum of 5 (or 10) μg m⁻³ when the wind came from the north (or south) of the NW-SE axis. The NW-SE axis in western Canada divides the tundra north with few anthropogenic PM2.5 sources from the forested south with many PM2.5 sources from forest fire smokes and human activities. Analyses of PM2.5 anomaly from the background (i.e., PM2.5 measured at a site around the mining complex—the background level at the corresponding tar and wind direction) revealed that the zone of elevated PM2.5 around the mine (Zepm) expanded with tar. In the first few hours after rain, PM2.5 was close to 0 everywhere except within meters of a source (e.g., a truck exhaust) in the downwind direction. During tar = 6 to 96 h, Zepm expanded to 6.3 km in the downwind direction when the wind came from south of the NW-SE axis. A similar result was found in the downwind direction when the wind came from north of the NW-SE axis, with Zepm = 4.4 km. In the upwind direction, the value of Zepm was much smaller, being 0.7 km (or 1.0 km) when the wind came from the north (or south) of the NW-SE axis. For the period of tar between 96 and 192 hours, Zepm further expanded to 21.2 km when the wind from the south of the NW-SE axis. The results from this study indicated that this reference paradigm that uses the regional background PM2.5 as the reference in combination with a portable PM2.5 monitor worked well for quantifying the tempo-spatial patterns of PM2.5 at locations in remote and mostly pristine Arctic. However, their effectiveness for other regions needs further investigation.
Sylvain G Leblanc
added a research item
Lichen is an important food source for caribou in Canada. Lichen mapping using remote sensing (RS) images could be a challenging task, however, as lichens generally appear in unevenly distributed, small patches, and could resemble surficial features. Moreover, collecting lichen labeled data (reference data) is expensive, which restricts the application of many robust supervised classification models that generally demand a large quantity of labeled data. The goal of this study was to investigate the potential of using a very-high-spatial resolution (1-cm) lichen map of a small sample site (e.g., generated based on a single UAV scene and using field data) to train a subsequent classifier to map caribou lichen over a much larger area (~0.04 km2 vs. ~195 km2) and a lower spatial resolution image (in this case, a 50-cm WorldView-2 image). The limited labeled data from the sample site were also partially noisy due to spatial and temporal mismatching issues. For this, we deployed a recently proposed Teacher-Student semi-supervised learning (SSL) approach (based on U-Net and U-Net++ networks) involving unlabeled data to assist with improving the model performance. Our experiments showed that it was possible to scale-up the UAV-derived lichen map to the WorldView-2 scale with reasonable accuracy (overall accuracy of 85.28% and F1-socre of 84.38%) without collecting any samples directly in the WorldView-2 scene. We also found that our noisy labels were partially beneficial to the SSL robustness because they improved the false positive rate compared to the use of a cleaner training set directly collected within the same area in the WorldView-2 image. As a result, this research opens new insights into how current very high-resolution, small-scale caribou lichen maps can be used for generating more accurate large-scale caribou lichen maps from high-resolution satellite imagery.
Sylvain G Leblanc
added an update
A first paper on lichen mapping was publish today by a PhD student (Shahab Jozdani) who is partly financed by our EO for Cumulative Effect project:
 
Sylvain G Leblanc
added an update
2020 was an odd year. With limited field work allowed, we worked mainly on data acquired in 2019. Several manuscripts have been written on our lichen mapping work, from plot photographs automatic classification using AI to scaling up using UAVs.
 
Sylvain G Leblanc
added an update
We collected lots of new data and are currently in the processing phase. Here's a video of one of our site 3D representation from UAV data https://youtu.be/JSiGLsZAYI8 It shows where the UAV (a Mavic Pro 2) was when acquiring the images and the 3D RGB and colour coded height of site B03.
 
Sylvain G Leblanc
added an update
The first of our 2 groups has completed a 2-week field campaign in the Manic-Uapishka-Labrador area. We visited sites with different post-burn conditions (6 to 100+ years), with different level of lichen regeneration and forest cover. We acquired UAV imagery in RGB+Red Edge, lichen biomass, hemispherical photographs and a few spectrometer samples along with cover type. Our colleagues from NL joined us for a couple of days near Churchill Falls.
 
Sylvain G Leblanc
added an update
This video was prepared for the TV interview, but I ended not using it. It shows how we are validation sound propagation on the tundra.
-Sylvain
 
Sylvain G Leblanc
added an update
Using the free ArcticDEM at 5m resolution and GPS value of the road. This video recreate the view from a haul Truck driving south from main camp to misery camp. To simplify the process, the view is actually always south, even when road turns. Colours represent distance from the truck at all time. E.g., Green colours generally representing less than 3km and pure white is at 15 km (maximum distance represented here). This kind of simulation will be use to assess sound propagation.
 
Sylvain G Leblanc
added an update
This is a link to my TV interview on the Ottawa French Rogers TV station. I talked about our caribou work in the NWT.
 
Sylvain G Leblanc
added an update
Title: Comparing the Measurements of Airborne Particulate Matter around a Mine and an Ambient Site within the Bathurst Caribou Summer Range
Authors: Chen, W.J., Leblanc, S.G.White, H.P. Croft, B., Patenaude, A., Clark, K., Pellissey, J.S., Meinert, L., Hum, J., Gunn, A., and Boulanger, J.
 
Sylvain G Leblanc
added an update
In addition to the oral presentation on sound, our group had two posters:
How far can barren ground caribou see mining operations in Canada’s Arctic? (Presenter: Wenjun Chen)
and
Satellite observations for detection of dust from mining activity in a caribou habitat (Presenter H. Peter White)
 
Sylvain G Leblanc
added an update
Presented a talk entitled Noise measurement and propagation to help refine the zone of influence of mining activities on caribou at the 17th north American Caribou Workshop (October 30, 2018):
This study is part of the Northwest Territory Cumulative Impact Monitoring Program (CIMP), and includes scientists and students from Natural Resources Canada, and was a collaboration with the Ekati Diamond mine. Various techniques were used to explore factors affecting the zone of influence of mines on caribou in the Bathurst herd. During three visits at the Ekati Diamond Mine, about 300km northeast of Yellowknife (2015-2017), more than 75 noise spectra were measured with a specialised sound meter (Svantek 977). The noise sources measured were vehicles, airplanes, helicopters and blasts in open pit mines. Using sound propagation theory applied to the caribou hearing spectrum, then estimated the distance at which each sound/noise could be heard by caribou. Our results with simple sound propagation that do not consider environmental effect on the propagation will be presented. Those results indicate that in perfect propagation conditions, with no atmospheric absorption, no natural barriers, and no other sound, mining surface vehicles could not be noticed by caribou past 6-7km, helicopters in flight could potentially be heard as far as 11km, a blast could be heard up to 40km away, and that larger aircraft have the potential to be heard more than 100 km away. We will also present initial results of our propose approach to more accurately estimate these distances using more sophisticated propagation models and experimental measurements that considerer topography, land cover and meteorological conditions.
 
Sylvain G Leblanc
added an update
We spent a week and a half at the Daring Lake Tundra Ecosystem Research Station in the Northwest Territories in August. We used drones to characterize the landscape and two microphones and a noise source to study weather and landscape effects on sound/noise propagation to better understand the physical mechanisms of the zone of influence around mining operations on caribou.
 
Sylvain G Leblanc
added an update
Link to an article about our caribou habitat work:
 
Sylvain G Leblanc
added a research item
Since mid-1980’s, the population of the Bathurst barren ground caribou (Rangifer tarandus) in Canada’s Arctic has declined by 93%. In order to develop and implement an effective recovery plan, it is important to know how various factors have cumulatively impacted the population decline. To contribute to the knowledge, we investigated the following two questions: how have changes in climate-induced habitat conditions impacted the peak calving date of the Bathurst caribou, and what was the implication of the impact on the population? Our results indicate that the peak calving date was impacted by changes in habitat conditions (e.g., the start date of vegetation growing season SOS) in a complex manner. Large inter-annual variations in SOS on the calving ground and summer range of the Bathurst herd were observed during 1985 and 2012, with the largest difference being 29 days. A 1-day delay of SOS in year i − 1 on the calving ground (SOScg(i − 1)) from its normal date could result in a 0.5-day delay in the peak calving date in year i, likely caused by the delay in the conception date in the previous fall. However, advances in SOScg(i − 1) did not alter the peak calving date in year i. Furthermore, a 1-day delay (or advance) in the current year’s SOS on the summer range (SOSsr(i)) might cause a 0.23-day delay (or advance) in the peak calving date in the current year, likely through changing the caribou’s gestation duration. Together SOScg(i − 1) and SOSsr(i) explained 69.1% of the variation in the peak calving date of the Bathurst caribou herd during 1985–2012, indicating the cumulative impacts on the peak calving date by the changing habitat conditions over a period of 2 years and thus the validation of the cumulative habitat impact hypothesis. Finally, our results also show that a 1-day delay in the peak calving date corresponded approximately 2–3% reduction in the birth rate of the Bathurst caribou, and thus might have been partially responsible for the population decline.
Sylvain G Leblanc
added an update
We measured sounds near the Ekati mine last summer: trucks, airplanes, helicopters etc.
 
Sylvain G Leblanc
added a research item
This study explores how dust from the Ekati Diamond Mine potentially affects the availability and quality of forage on the seasonal range of the Bathurst caribou herd. Understanding the effects of dust as a source of disturbance is important because the Bathurst caribou population has declined by 93% since the middle 1980s and there are reports that caribou in general may avoid mining projects. There are several challenges for quantifying dust impacts: 1) Natural variations (e.g., topography, natural disturbance, and soil pH) may also impact forage availability and quality for caribou. To minimize their masking effect, we stratified survey sites into seven land cover classes and selected the most populous class (i.e., the dwarf shrub) for assessing the impact. 2) Within class variation (e.g., the proportion of area covered by rocks where vascular plants and lichen do not grow) can further skew the analysis. We eliminated this problem by examining only the area not covered by rocks. 3) Coarse and fine suspended particulates have different spatial coverages, chemical compositions, and pH values. Consequently, their impacts on caribou forage can be different. To distinguish their impacts, we sampled two areas: transects from the Misery Haul Road that has been in active use vs. those from a rarely used spur road outside the Misery Camp. We sampled percent vegetation cover, soil pH, and dust on leaves along these transects during the summers of 2015 and 2016. Our results indicated that the amount of dust on leaves in a zone of ~1000 m from the Misery Haul Road was 3 - 9 times than that of background sites. The zone of reduced lichen percent cover was also about 1000 m. In contrast, these road dust-induced changes in caribou forage were not observed for the dust-free transect from the spur road.
Sylvain G Leblanc
added an update
Sylvain G Leblanc
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A short article on our work on Caribou, Mining Operations and the “Zone of Influence”:
 
Sylvain G Leblanc
added 9 research items
Leaf area index (LAI) is an important structural vegetation parameter that is commonly derived from remotely sensed data. It has been used as a reliable indicator for vegetation's cover, status, health and productivity. In the past two decades, various Canada-wide LAI maps have been generated by the Canada Centre for Remote Sensing (CCRS). These products have been produced using a variety of very coarse satellite data such as those from SPOT VGT and NOAA AVHRR satellite data. However, in these LAI products, the mapping of the Canadian northern vegetation has not been performed with field LAI measurements due in large part to scarce in situ measurements over northern biomes. The coarse resolution maps have been extensively used in Canada, but finer resolution LAI maps are needed over the northern Canadian ecozones, in particular for studying caribou habitats and feeding grounds.In this study, a new LAI algorithm was developed with particular emphasis over northern Canada using a much finer resolution of remotely sensed data and in situ measurements collected over a wide range of northern arctic vegetation. A statistical relationship was developed between the in situ LAI measurements collected over vegetation plots in northern Canada and their corresponding pixel spectral information from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. Furthermore, all Landsat TM and ETM+ data have been pre-normalized to NOAA AVHRR and SPOT VGT data from the growing season of 2005 to reduce any seasonal or temporal variations. Various spectral vegetation indices developed from the Landsat TM and ETM + data were analysed in this study. The reduced simple ratio index (RSR) was found to be the most robust and an accurate estimator of LAI for northern arctic vegetation. An exponential relationship developed using the Theil–Sen regression technique showed an R of 0.51 between field LAI measurement and the RSR. The developed statistical relationship was applied to a pre-existing Landsat TM 250 m resolution mosaic for northern Canada to produce the final LAI map for northern Canada ecological zones. Furthermore, the 250 m resolution LAI estimates, per ecological zone, were almost generally lower than those of the CCRS Canada-wide VGT LAI maps for the same ecozones. Validation of the map with LAI field data from the 2008 season, not used in the derivation of the algorithm, shows strong agreement between the in situ LAI measurement values and the map-estimated LAI values.
Information on biomass distribution is needed to estimate GHG emissions and removals from land use changes in Canada's north for UNFCCC reporting. This paper reports aboveground biomass measurements along the Dempster Highway transect in 2004, and around Yellowknife and the Lupin Gold Mine in 2005. The measured aboveground biomass ranges are 10–100 t ha−1 for woodlands, 1–100 t ha−1 for shrub sites, and 0.5–10 t ha−1 for grass/herbs sites. The root mean squared error (RMSE) of measurements is 21%, and the median absolute percentage error (MedAPE) is 14%. The combination of JERS backscatter and Landsat TM4/TM5 gives the best biomass equation for the Dempster Highway transect, with r 2 = 0.72 when using a one‐step approach (i.e. using all points) and 0.78 when using a two‐step approach (i.e. stratifying data into three classes: grass, shrub, and woodlands). The two‐step approach reduces the MedAPE from 53% to 33%. The validation against Yellowknife & Lupin data indicates that the equations have good transferability. The improvement of two‐step approach over the one‐step approach, however, is not significant for the validation dataset, suggesting that the one‐step approach is as good as the two‐step approach when applied over areas outside where the equations are developed. The relationships and error analysis of this study, as well as the final estimate of GHG emission/removal over Canada's north have been incorporated into Canada's 2006 UNFCCC report.
Sylvain G Leblanc
added a project goal
Human activity zone of influence on barren-land caribou. Assessment and mapping of biomass and Leaf Area Index (LAI). Lichen mapping for caribou habitat.