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  • 2006 PhD. Earth and Atmospheric Sciences, University of Alberta
  • 2003 MSc. Earth and Atmospheric Sciences, University of Alberta

Dr. Margaret Kalacska

I am an Associate Professor in the Department of Geography at McGill University. My current research contributes to the advancement of remote sensing applications in environmental science.

In my lab we extensively use Remotely Piloted Aircraft Systems (RPAS), and airborne hyperspectral remote sensing from manned aircraft. We also work with satellite imagery (e.g. PlanetScope, Landsat, Sentinel-2), LiDAR and thermal imaging for detailed investigations of terrestrial and aquatic ecosystems and infrastructure. We are a world leader in RPAS hyperspectral imaging.

In collaboration with the National Research Council of Canada's Flight Research Laboratory we developed the second fully operational RPAS-HSI system in the world. This system has been in use for the Canadian Airborne Biodiversity Observatory (CABO) since 2018 to estimate biodiversity and ecosystem functioning.

Through the Fish + Forest project we study aquatic habitats of endemic and endangered ichthyofauna, producing the first aerial and underwater 3D reconstructions of riverscapes in Brazil. Our research also examines large-scale land use change for biodiversity conservation from satellite imagery and contribute to satellite data product validation (Landsat 8 OLI and Sentinel-2) for Canadian peatlands.

I was the first Canadian woman to lead an airborne hyperspectral mission (MAC-13) in Costa Rica in 2013 for forest carbon stock and biodiversity estimation. My interdisciplinary research is carried out in Canada, Brazil, Tanzania, Ghana, Peruvian Amazon, Panama, Madagascar and Costa Rica.

In 2014, I was awarded the Fessenden Prize for Science Innovation by McGill University and in 2018, the Silver Medal from the Canadian Remote Sensing Society, the highest mid-career achievement award recognizing excellence in remote sensing in Canada. I was nominated by the National Research Council Canada for the 2020 Steacie Prize in Natural Sciences.

Current Students and Staff

Gillian Rowan

Gillian Rowan is an MSc student in the Applied Remote Sensing Laboratory in McGill University's Geography department where she studies remote sensing of aquatic ecosystems. After graduating with a Bachelor of Environmental Science in biodiversity and conservation from McGill University, she worked as the Coordinator of Environmental Affairs for Air Canada. In this position she was involved with carbon reporting, waste management, corporate outreach, and community engagement. Gillian's current research examines how remote sensing can be applied to underwater plants, what its limitations are in the aquatic medium, and what information we can reliably use remote sensing to collect. In collecting spectral information about a variety of species of aquatic plants and different water types, she is examining how spectrally separable the plants are under various modelled conditions. Understanding and defining the spectral separability of aquatic plants will allow future researchers and ecosystem managers to better target their monitoring efforts and thus increase the efficiency of conservation efforts in aquatic ecosystems.



Publications

Rowan G.S.L., Kalacska M. 2021. A Review of Remote Sensing of Submerged Aquatic Vegetation for Non-Specialists Remote Sensing 13(4):623

Rowan G.S.L., Kalacska M., Inamdar D., Arroyo-Mora J.P., Soffer R. 2021. Multi-scale spectral separability of submerged aquatic vegetation species in a freshwater ecosystem. Frontiers in Environmental Science - Freshwater Science 9:438

Kathryn Elmer

Kathryn Elmer is currently pursuing her MSc in Geography at McGill University as part of the Applied Remote Sensing Lab (ARSL), and received her BSc in Earth System Sciences from McGill University in 2017. She previously worked for the National Research Council of Canada’s Flight Research Lab (Ottawa, Ontario) and ARSL at McGill University (Montreal, Quebec), where she contributed to research on a variety of topics including the use of unmanned aerial vehicles (UAVs) as remote sensing platforms for ecological monitoring, satellite simulations, spatial accuracy of UAV platforms for 3D landscape reconstructions, and various field work campaigns. Her thesis focuses on using remote sensing technology, specifically hyperspectral imagery (HSI) acquired using airborne and UAV platforms, for identifying and mapping the highly invasive plant species Phragmites australis subs. australis as part of CABO. Her field site is Îles-de-Boucherville National Park and she is working to provide the park management team with a park-wide Phragmites identification map. Her work aims to help establish remote sensing and HSI as an effective tool for the management of invasive species around the world.



Publications

Elmer K, Kalacska M, Arroyo-Mora J.P. 2021 Mapping the extent of invasive Phragmites australis subsp. australis from airborne hyperspectral imagery Frontiers in Environmental Science - Environmental Informatics and Remote Sensing 9:496

Elmer K., Kalacska M. 2021. A High-Accuracy GNSS Dataset of Ground Truth Points Collected within Îles-de-Boucherville National Park, Quebec, Canada Data 6(3):32

Elmer K., Soffer R.J., Arroyo-Mora J.P., Kalacska M. 2020. ASDToolkit: A Novel MATLAB Processing Toolbox for ASD Field Spectroscopy Data Data 5(4):96

Arroyo-Mora J.P., Kalacska M., Inamdar D., Soffer R., Lucanus O., Gorman J., Naprstek T., Schaaf E.S., Ifimov G., Elmer K., Leblanc G. 2018. Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring Drones 3(1):12

Kalacska M., Lucanus O., Arroyo-Mora J.P., Laliberté E., Elmer K., Leblanc G., Groves A. 2020. Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms Drones 4(2):13


Patrick Osei Darko

Patrick Osei Darko is a PhD student in the Applied Remote Sensing Laboratory (ARSL) in the department of Geography, McGill University. He is supervised by Prof. Margaret Kalacska and Dr. Pablo Arroyo-Mora. Patrick's research explores how hyperspectral remote sensing techniques based on airborne and UAV technology can be used for mapping forest traits and species composition in support of global forest conservation efforts and climate change mitigation strategies. Patrick is an experienced mining professional from Ghana who is very passionate about the applications of remote sensing techniques for questions related to environmental sustainability. He was part of a team in the mining industry that implemented a continent-wide information system for land and environmental management which received the Special Achievement (SAG) award in 2018 from ESRI. After his undergraduate degree in Geomatic Engineering (2011), Patrick continued to earn a postgraduate degree in same field (2013-2016) where he evaluated the utility and effectiveness of remote sensing technologies such as Earth observation satellites (e.g. Landsat) and LiDAR for assessing periodic changes in reclaimed tropical forests in Ghana, West Africa.



Publications

Osei Darko P., Kalacska M., Arroyo-Mora J.P., Fagan M.E. 2021. Spectral Complexity of Hyperspectral Images: A New Approach for Mangrove Classification Remote Sensing 13(13):2604

Lamboj A., Lucanus O., Osei Darko P., Arroyo-Mora J.P. 2020. Habitat loss in the restricted range of the endemic Ghanaian cichlid Limbochromis robertsi Biotropica 52(5):896-912

Brendan Cottrell

Brendan Cottrell is a MSc student in the Applied Remote Sensing Laboratory in McGill University's Geography department where he studies the application of remote sensing and drone technology in marine mammal conservation. Brendan graduated from Simon Fraser University with a Bachelor of Science in Applied Physics, later finishing an Advanced Certificate in Geographic Information Systems from the British Columbia Institute of Technology. After graduating from Simon Fraser University, Brendan worked with the British Columbia Marine Mammal Response Network where he was involved in marine mammal rescue, necropsies, and research. Brendan's current research is examining the ability of drones and remote sensing techniques to characterize and catalogue the prevalence and severity of entanglement scarring on large whales such as humpbacks. The collection of baseline data on large whale entanglement rates and impact allows for both fisheries and marine mammal managers to implement more effective solutions in limiting these events.


Deep Inamdar

Deep Inamdar is a PhD candidate at McGill University in Geography in the Applied Remote Sensing Laboratory. He is also a research assistant responsible for processing the hyperspectral imaging data collected for the Canadian Airborne Biodiversity Observatory, an initiative to understand the changes in plant biodiversity on a local, regional, and national scale using spectronomics. Deep completed his undergraduate degree at McMaster University in the Integrated Science program, concentrating in Mathematics and Statistics. During his undergraduate studies, Deep was a research assistant at the National Research Council of Canada in the Flight Research Laboratory, where he developed image processing and analysis tools. Deep is interested in developing tools to study peatland ecosystems with remote sensing technologies. His work aims to model the resilience of peatlands to climate change and the consequences of destabilized ecosystems.



Publications

Inamdar D., Kalacska M., Arroyo-Mora J.P., Leblanc G. 2021. The Directly-Georeferenced Hyperspectral Point Cloud: Preserving the Integrity of Hyperspectral Imaging Data Frontiers in Remote Sensing - Data Fusion 2:9

Inamdar D., Kalacska M., Leblanc G., Arroyo-Mora J.P. 2021. Implementation of the directly-georeferenced hyperspectral point cloud MethodsX 8:101429

Inamdar D., Kalacska M., Leblanc G., Arroyo-Mora J.P. 2020. Characterizing and Mitigating Sensor Generated Spatial Correlations in Airborne Hyperspectral Imaging Data Remote Sensing 12(4):641

Inamdar D., Leblanc G., Soffer R., Kalacska M. 2018. The Correlation Coefficient as a Simple Tool for the Localization of Errors in Spectroscopic Imaging Data Remote Sensing 10(2):231

Arroyo-Mora J.P., Kalacska M., Inamdar D., Soffer R., Lucanos O., Gorman J., Naprstek T., Schaaf E.S., Ifimov G., Elmer K., Leblanc G. 2018. Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring Drones 3(1):12

Kalacska M., Arroyo-Mora J.P., Soffer R.J., Roulet N.T., Moore T.R., Humphreys E., Leblanc G., Lucanus O., Inamdar D. 2018. Estimating Peatland Water Table Depth and Net Ecosystem Exchange: A Comparison between Satellite and Airborne Imagery Remote Sensing 10(5):687

Arroyo-Mora J.P., Kalacska M., Soffer R.J., Moore T.R., Roulet N.T., Juutinen S., Ifimov G., Leblanc G., Inamdar D. 2018. Airborne Hyperspectral Evaluation of Maximum Gross Photosynthesis, Gravimetric Water Content, and CO2 Uptake Efficiency of the Mer Bleue Ombrotrophic Peatland Remote Sensing 10(4):565

Nicolas Cadieux

Digital elevation models (DEMs) were among the first digital geographical information to be readily available and widely used. At the Earth Resources Observation and Science (EROS) Centre of the United States Geological Survey (USGS), DEMs represent the most popular data set distributed with an average of one 1⁰ x 1⁰ tile downloaded every second of every day!

In archaeology, they are frequently employed, with examples dating back to the late 70s and early 80s, because they represent a concrete, directly observable phenomenon that humans can relate to: the surface of the planet.
DEMs allow a vast array of GIS-derived analyses (i.e. slope, shade, aspect, viewshed, path analysis, flood risk analysis, drainage modeling, etc) that all directly relate to how past and current humans, and their prey, experience, perceive, interact and adapt to the landscape and the environment. Topography increases biodiversity, influences soil development, human settlement, and land-use pattens. It is an important element in settlement patterns.

In Canada, Natural Resources Canada (NRCan) has produced the Canadian Digital Elevation Data (CDED) and the Canadian Digital Surface Model (CDSM). The NASA Jet Propulsion Laboratory (JPL), Japan’s Ministry of Economy, Trade and Industry (METI) and the Japan Aerospace Exploration Agency (JAXA) have also released global or near global DEMs (SRTM, ASTER GDEM, AW3D30 respectively). Each has its own qualities, limitations, and level of precision that may, or may not, be adapted to an archaeological research question. Faced with a multitude of DEMs to choose from, even researchers well versed in GIS find themselves lost in this myriad of numerical terrains.

My research goal is to help archaeologists and other researchers to find their way across the various digital landscapes. It focuses mostly on freely available models covering the Canadian landscape that overlap provincial boundaries while maintaining a Canadian perspective on the data as Canada’s northern latitudes present both advantages and unique challenges to model developers.

My PhD project looks at how DEMs are employed by archaeologists. My goal is to help researchers with important concepts that will help them understand the basic characteristics of current, and future elevation models. Using high precision (15 to 30 cm) light detection and ranging (LiDAR) data from 32 LiDAR campaigns flown across Canada (22,150 km2), each model is tested to assess its vertical precision as well as the usefulness of the metadata. This should permit archaeologists and others to carefully select the most appropriate DEM for their research question and will serve to answer Kvamme’s call for archaeologists to be concerned with “the quality of data obtained by computer means”.

Research interests: GIS, Python, DEM, LiDAR, HSI data fusion, Graph-Network analysis



Publications

Cadieux N., Kalacska M., Coomes O.T., Tanaka M., Takasaki Y. 2020 A Python Algorithm for Shortest-Path River Network Distance Calculations Considering River Flow Direction Data 5(1):8

Oliver Lucanus

Oliver Lucanus has been flying drones since the early days of UAS, and maintains and flies the UAS fleet for the Applied Remote Sensing Lab (ARSL) and Canadian Airborne Biodiversity Observatory (CABO). He holds a Transport Canada Advanced Operations Pilot certificate since 2019, a Pix4DMapper Essentials certificate since 2020 and has logged hundreds of flights with many different UAS, including the DJI M600Pro, M300RTK, Inspire 1 and 2, Mavic 2 Enterprise Advanced and others using LiDAR, thermal, photographic and hyperspectral sensors. He is part of the ARSL and National Research Council of Canada team that was the first to integrate the Itres uCASI hyperspectral imager on a UAS. In addition to DJI systems he is also familiar with flight planning and piloting the BFD-X8 with the Hyspex Mjolnir VS-620 hyperspectral imager. He has been an integral part of payload integration, flight planning and piloting for over one hundred missions, including those in controlled airspace. He has coauthored a number of papers using UAS for photogrammetry, thermal imaging, hyperspectral cameras and photography. Currently he is training for BVLOS operations as well as becoming a certified thermographer - to be completed in 2021. Check out his work in freshwater conservation with the Fish+Forest Project


Publications

Recent Alumni (BA/BSc Honor's, MSc, PhD, PDF, Staff)

Sienna Svob, MSc 2014

Publications

Svob S., Arroyo-Mora J.P., Kalacska M. 2014 A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica Carbon Balance and Management 9,9 https://doi.org/10.1186/s13021-014-0009-y

Svob S., Arroyo-Mora J.P., Kalacska M. 2014 The development of a forestry geodatabase for natural forest management plans in Costa Rica Forest Ecology and Management 327(1):240-250

Arroyo-Mora J.P., Svob S., Kalacska M., Chazdon R. 2014 Historical Patterns of Natural Forest Management in Costa Rica: The Good, the Bad and the Ugly Forests 5(7):1777-1797

Thesis: The creation of a forestry relational database and assessment of aboveground biomass variability across Costa Rica using forest management data

Carrie Herzog, MSc 2014

Publications

Kalacska M., Arroyo-Mora J.P., de Gea J., Snirer E., Herzog C., Moore T.R. 2013 Videographic Analysis of Eriophorum vaginatum Spatial Coverage in an Ombotrophic Bog Remote Sensing 5(12):6501-6512

Thesis: A study of the effects of cadaveric decomposition on hyperspectral signatures of soil and vegetation

Erica Skye Schaaf, Research Assistant 2015-2019

Publications

Arroyo-Mora J.P., Kalacska M., Inamdar D., Soffer R., Lucanus O., Gorman J., Narstek T., Schaaf E.S., Ifimov G., Elmer K., Leblanc G. 2019. Implementation of a UAV–Hyperspectral Pushbroom Imager for Ecological Monitoring Drones 3(1),12

Arroyo-Mora J.P., Kalacska M., Soffer R., Ifimov G., Leblanc G., Schaaf E.S., Lucanus O. 2016. Evaluation of phenospectral dynamics with Sentinel-2A using a bottom-up approach in a northern ombrotrophic peatland Remote Sensing of Environment 216:544-560.

Dr. J. Pablo Arroyo-Mora, Postdoctoral Fellow 2009-2012

Senior Research Officer, Flight Research Laboratory, National Research Council Canada

Karling Roberts, Technician 2014-2015
Lilian Fradin, Research Assistant 2017
Rosalie Beauchamp-Rioux (U. de Montréal), MSc 2021
Mark Lalond, MSc 2014

Publications

Kalacska M., Lalonde M., Moore T.R. 2015. Estimation of foliar chlorophyll and nitrogen content in an ombrotrophic bog from hyperspectral data: Scaling from leaf to image Remote Sensing of Environment 169:270-279

Thesis (MSc): The hyperspectral determination of Sphagnum water content in a bog

Thesis (BSc): Using Hyperspectral Remote Sensing to Estimate Foliar Chlorophyll and Nitrogen Concentrations in an Ombrotrophic Peatland

Julie de Gea, MSc 2015

Publications

Leblanc G., Francis C.M., Soffer R., Kalacska M., de Gea J. 2016. Spectral Reflectance of Polar Bear and Other Large Arctic Mammal Pelts; Potential Applications to Remote Sensing Surveys Remote Sensing 8(4), 273

Kalacska M., Arroyo-Mora J.P., de Gea J., Snirer E., Herzog C., Moore T.R. 2013 Videographic Analysis of Eriophorum vaginatum Spatial Coverage in an Ombotrophic Bog Remote Sensing 5(12), 6501-6512

Thesis (MSc): Phenology of vegetation light-use efficiency and reflectance: experiment over two boreal ecosystems

Thesis (BSc): Discriminating between grave sites and non-grave sites using conventional remote sensing methods

Dr. Rachid Hedjam, Postdoctoral Fellow 2013-2017

Assistant Professor, Department of Computer Science, Sultan Qaboos University

Frank Ferber, Technician 2012-2013
Ian Tattersfield, Research Assistant 2016-2017
Tristan Grupp, Research Assistant 2018-2019
Grace Pigeau, Research Assistant 2017
Oliver Schmidt, Research Assistant 2011-2012
Alizée Girard (U. de Montréal), MSc 2019

Publications

Girard A., Schweiger A.K., Carteron A., Kalacska M., Laliberté E. 2020. Foliar Spectra and Traits of Bog Plants across Nitrogen Deposition Gradients Remote Sensing 12(15), 2448

Thesis: Propriétés fonctionnelles et spectrales d’espèces végétales de tourbières ombrotrophes le long d’un gradient de déposition d’azote

Eva Snirer, MSc 2014

Publications

Kalacska M., Arroyo-Mora J.P., de Gea J., Snirer E., Herzog C., Moore T.R. 2013 Videographic Analysis of Eriophorum vaginatum Spatial Coverage in an Ombotrophic Bog Remote Sensing 5(12):6501-6512

Thesis: Hyperspectral remote sensing of individual gravesites - exploring the effects of cadaver decomposition on vegetation and soil spectra

Dr. Benjamin Heumann, Postdoctoral Fellow 2011-2012

Associate Professor, Central Michigan University

Dr. Jin Xing, PhD 2018

Assistant Professor, Newcastle University

Publications

Xing J., Sieber R., Kalacska M. 2014. The challenges of image segmentation in big remotely sensed imagery data Annals of GIS 20(4): 233-244

Thesis: Scale handling for land use/cover change in an era of big data

Google Scholar profile

Jennifer Bracewell, Project Manager 2016-2018
Cameron Roy, Research Assistant 2016
Applied Remote Sensing Lab

Department of Geography
McGill University
805 Sherbrooke West
Burnside Hall 705
Montreal, QC H3A 0B9
Canada

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