{"id":25555,"date":"2019-08-14T13:54:58","date_gmt":"2019-08-14T17:54:58","guid":{"rendered":"https:\/\/carleton.ca\/geography\/?post_type=cu_people&#038;p=25555"},"modified":"2026-03-20T14:52:05","modified_gmt":"2026-03-20T18:52:05","slug":"koreen-millard","status":"publish","type":"cu_people","link":"https:\/\/carleton.ca\/geography\/people\/koreen-millard\/","title":{"rendered":"Associate Professor Koreen Millard"},"content":{"rendered":"<header class=\"mb-6 cu-pageheader cu-component-updated md:mb-12\">\n    <h1 class=\"cu-prose-first-last font-semibold !mt-2 mb-4 md:mb-6 text-3xl md:text-4xl lg:text-5xl lg:leading-[3.5rem] relative after:absolute after:h-px after:bottom-0 pb-5 after:w-10 after:bg-cu-red after:left-px\">\n                    \n             \n                \n            <\/h1>\n\n    \n    <\/header>\n\n\n\n\n\n<h4 id=\"biography\" class=\"wp-block-heading\">Biography<\/h4>\n\n\n\n<p>My research sits at a crossroads between geomatics, physical geography and big data science.&nbsp;I focus on ecosystem monitoring and extraction of biophysical parameters from remotely sensed imagery, but I also critically assess how bias and uncertainty can affect the use of these tools in a variety of landscapes.&nbsp;&nbsp;By coupling remote sensing with extensive monitoring in the field, my research helps detangle hydrological, vegetation and climate interactions so that we can better predict the responses of wetlands and northern ecosystems to change. Recently, much of my research has been related to peatland wildfires, including assessing time series analysis techniques of SAR and multispectral imagery to understand the conditions under which peatlands burn.<\/p>\n\n\n\n<h4 id=\"selected-publications\" class=\"wp-block-heading x_MsoNormal\"><span data-ogsc=\"rgb(25, 25, 25)\">Selected Publications:<\/span><\/h4>\n\n\n\n<p>Richardson, E., <strong class=\"myprefix-text-bold\">Millard, K.<\/strong>, van Proosdij, D. (2026).\u00a0On the use of post-classification change analysis for monitoring salt marsh extent in support of carbon inventory reporting.\u00a0 Remote Sensing Applications: Society and Environment.\u00a0<a href=\"https:\/\/doi.org\/10.1016\/j.rsase.2025.101862\">https:\/\/doi.org\/10.1016\/j.rsase.2025.101862<\/a><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><u><span data-ogsc=\"black\">Pontone, N.<\/span><\/u><span data-ogsc=\"black\">,&nbsp;<b>Millard, K.,&nbsp;<\/b>Guindon, L., Thompson, D., Beaudoin, A., (2024). A hierarchical, multi-sensor framework for peatland sub-class and vegetation mapping throughout the Canadian Boreal Forest. Remote Sensing In Ecology and Conservation.&nbsp;<a href=\"https:\/\/doi.org\/10.1002\/rse2.384\" data-auth=\"NotApplicable\" data-linkindex=\"0\" data-ogsc=\"\">https:\/\/doi.org\/10.1002\/rse2.384<\/a><\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><u><span data-ogsc=\"black\">Pelletier, N.<\/span><\/u><span data-ogsc=\"black\">,&nbsp;<b>Millard, K.,<\/b>&nbsp;<u>Darling, S.<\/u>, (2023). Wildfire probability estimation in Canadian treed peatlands based on remote-sensing time-series of surface conditions. Remote Sensing of Environment.&nbsp;296,&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.rse.2023.113747\" data-auth=\"NotApplicable\" data-linkindex=\"1\" data-ogsc=\"\">https:\/\/doi.org\/10.1016\/j.rse.2023.113747<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><u><span data-ogsc=\"black\">Schultz, S.<\/span><\/u><span data-ogsc=\"black\">,&nbsp;<b>Millard, K.,<\/b>&nbsp;<u>Darling, S.<\/u>, Chenier, R., (2023). \u201cInvestigating the Use of Sentinel-1 for Improved Mapping of Small Peatland Water Bodies: Towards Wildfire Susceptibility Monitoring in Canada\u2019s Boreal Forest\u201d. Hydrology, 10(5), 102,&nbsp;<\/span><a href=\"https:\/\/doi.org\/10.3390\/hydrology10050102\" data-auth=\"NotApplicable\" data-linkindex=\"2\" data-ogsc=\"\"><span data-ogsc=\"black\">https:\/\/doi.org\/10.3390\/hydrology10050102<\/span><\/a><span data-ogsc=\"black\">.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><b><span data-ogsc=\"black\">Millard, K.,<\/span><\/b><span data-ogsc=\"black\">&nbsp;<u>Darling, S., Pelletier, N., Schultz., S.,<\/u>&nbsp;(2022). Seasonally-decomposed Sentinel-1 backscatter time-series are useful indicators of peatland wildfire vulnerability. Remote Sensing of Environment. 283(15),&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.rse.2022.113329\" data-auth=\"NotApplicable\" data-linkindex=\"3\" data-ogsc=\"\">https:\/\/doi.org\/10.1016\/j.rse.2022.113329<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><u><span data-ogsc=\"black\">Antropova, Y.<\/span><\/u><span data-ogsc=\"black\">, Komarov, A., Richardson, M.,<b>&nbsp;Millard, K.<\/b>, Smith, K., (2022).&nbsp; Detection of wet snow in the Arctic tundra from time-series fully-polarimetric RADARSAT-2 images.&nbsp; Remote Sensing of Environment,&nbsp;&nbsp;<a href=\"https:\/\/doi.org\/10.1016\/j.rse.2022.113305\" data-auth=\"NotApplicable\" data-linkindex=\"4\" data-ogsc=\"\">https:\/\/doi.org\/10.1016\/j.rse.2022.113305<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><span data-ogsc=\"black\">Riva, F., Martin, C.,&nbsp;<b>Millard, K<\/b>., Fahrig, L., (2022).&nbsp; Loss of the world\u2019s smallest forests.&nbsp; Global Change Biology,&nbsp;<a href=\"https:\/\/doi.org\/10.1111\/gcb.16449\" data-auth=\"NotApplicable\" data-linkindex=\"5\" data-ogsc=\"\">https:\/\/doi.org\/10.1111\/gcb.16449<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><u><span data-ogsc=\"black\">Fuller, A.,<\/span><\/u><span data-ogsc=\"black\">&nbsp;<b>Millard, K.<\/b>, Green, J., (2022), SatViT: Pre-training Transformers for Earth Observation. IEEE Geoscience and Remote Sensing Letters, 19,&nbsp;<a href=\"https:\/\/doi.org\/10.1109\/LGRS.2022.3201489\" data-auth=\"NotApplicable\" data-linkindex=\"6\" data-ogsc=\"\">https:\/\/doi.org\/10.1109\/LGRS.2022.3201489<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><span data-ogsc=\"black\">Melton, J., Chan, E.,&nbsp;<b>Millard, K.<\/b>, Fortier, M., R. Winton, S., Mart\u00edn-L\u00f3pez, J., Cadillo-Quiroz, H., Kidd, D., and Verchot, L., (2022), A map of global peatland extent created using machine learning (Peat-ML). Geoscientific Modelling and Development, 15, 4709\u20134738,&nbsp;<\/span><a href=\"https:\/\/doi.org\/10.5194\/gmd-15-4709-2022\" data-auth=\"NotApplicable\" data-linkindex=\"7\" data-ogsc=\"\"><span data-ogsc=\"black\">https:\/\/doi.org\/10.5194\/gmd-15-4709-2022<\/span><\/a><span data-ogsc=\"black\">.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><b><span data-ogsc=\"black\">Millard, K.<\/span><\/b><span data-ogsc=\"black\">, Brown, N., Stiff, D., Pietroniro, A., (2020).&nbsp; Automated surface water detection from space: a Canada-wide, open-source, automated, near-real time solution.&nbsp; Canadian Journal of Water Resources. 45(5), 304-323.&nbsp;&nbsp;<\/span><a href=\"https:\/\/doi.org\/10.1080\/07011784.2020.1816499\" data-auth=\"NotApplicable\" data-linkindex=\"8\" data-ogsc=\"\"><span data-ogsc=\"black\">https:\/\/doi.org\/10.1080\/07011784.2020.1816499<\/span><\/a><span data-ogsc=\"black\">&nbsp;<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><b><span data-ogsc=\"black\">Millard, K.,<\/span><\/b><span data-ogsc=\"black\">&nbsp;Kirby, P., Nandall, S., Benhamian, A., Banks, S., Pacini, F., (2020).&nbsp; Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series.&nbsp; Remote Sensing, 12(15), 2465,&nbsp;<a href=\"https:\/\/doi.org\/10.3390\/rs12152465\" data-auth=\"NotApplicable\" data-linkindex=\"9\" data-ogsc=\"\">https:\/\/doi.org\/10.3390\/rs12152465<\/a>.<\/span><\/p>\n\n\n\n<p class=\"x_MsoNormal\"><span data-ogsc=\"rgb(25, 25, 25)\">For the most up-to list of my research publications, please visit my google scholar profile<\/span>&nbsp;<a title=\"Original URL: https:\/\/scholar.google.com\/citations?user=UkrB8a4AAAAJ&amp;hl=en. Click or tap if you trust this link.\" href=\"https:\/\/can01.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fscholar.google.com%2Fcitations%3Fuser%3DUkrB8a4AAAAJ%26hl%3Den&amp;data=05%7C02%7CNIKALINSEMAN%40CUNET.CARLETON.CA%7Cf47538e3b72a450a85c808dc7363826f%7C6ad91895de06485ebc51fce126cc8530%7C0%7C0%7C638512118434556377%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&amp;sdata=kr25JiNbAeg7gMt96frU8MlGH4YRgWxeJB4ia2Xt2yY%3D&amp;reserved=0\" data-auth=\"Verified\" data-linkindex=\"10\" data-ogsc=\"blue\">here<\/a><\/p>\n","protected":false},"author":2,"featured_media":25556,"template":"","meta":{"_acf_changed":false,"cu_people_first_name":"Associate Professor Koreen","cu_people_last_name":"Millard","cu_people_initials":"","footnotes":"","_links_to":"","_links_to_target":""},"cu_people_type":[20],"cu_people_expertise":[],"class_list":["post-25555","cu_people","type-cu_people","status-publish","has-post-thumbnail","hentry","cu_people_type-professors"],"acf":{"cu_people_job_title":"Multi-sensor data fusion for improved understanding of hydrology\/vegetation change and interactions; Modelling spatial and temporal biophysical variables with time-series remote sensing and field-measurements; Machine learning image classification for mapping environmental change","cu_people_degree":"B.A. (Bishop's University), M.Sc. 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