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Abstract

The National Terrestrial Ecosystem Monitoring System (NTEMS) was developed by the Canadian Forest Service to provide national-scale baseline information on Canada's forested ecosystems. Based largely on data from the Landsat series of satellites, free and open access to analysis ready data, and utilization of high performance computing, NTEMS enabled the recreation of the history of Canada's forests at a higher level of spatial and categorical detail than ever before. Through NTEMS research, methods have been developed for image compositing, change detection, and change attribution using Landsat time series data. NTEMS outputs have subsequently enabled the characterization of post-disturbance recovery, an annual land cover data cube, and national representations of forest structure.
NTEMS listing of scientific publications 1
2025-01-06
fnNational Terrestrial Ecosystem Mapping System (NTEMS):
Scientific Publications
Version 5
January 6, 2025
Michael A. Wulder (PI), Joanne C. White, Txomin Hermosilla, Geordie W. Hobart Canadian Forest
Service
Nicholas C. Coops University of British Columbia
The National Terrestrial Ecosystem Monitoring System (NTEMS) was developed by the Canadian Forest
Service to provide national-scale baseline information on Canada's forested ecosystems. Based largely on
data from the Landsat series of satellites, free and open access to analysis ready data, and utilization of
high-performance computing, NTEMS enabled the re-creation of the history of Canada’s forests at a
higher level of spatial and categorical detail than ever before. Through NTEMS research, methods have
been developed for image compositing, change detection, and change attribution using Landsat time
series data. NTEMS outputs have subsequently enabled the characterization of post-disturbance recovery,
an annual land cover data cube, and national representations of forest structure.
Contents
Context .......................................................................................................................................................... 2
Key papers ..................................................................................................................................................... 3
Methods development ................................................................................................................................. 4
Forest disturbance ........................................................................................................................................ 5
Post-disturbance forest recovery ................................................................................................................. 6
Forest structure ............................................................................................................................................ 7
Forest age ...................................................................................................................................................... 8
Land cover ..................................................................................................................................................... 8
Tree species .................................................................................................................................................. 9
Forest inventory ............................................................................................................................................ 9
Forest growth ................................................................................................................................................ 9
Landsat program and archive ..................................................................................................................... 10
Carbon accounting applications .................................................................................................................. 11
Virtual constellations .................................................................................................................................. 11
Other applications ....................................................................................................................................... 12
NTEMS listing of scientific publications 2
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Context
Canada is a vast nation. From a total area approaching 1 billion hectares, Canada has about 350 million
hectares of land with trees. These treed areas are found in forested ecosystems, interspersed among
wetlands and lakes, with an area of ~650 million ha, or 65% of the country. Forested ecosystems provide
habitat and timber, protect biodiversity, as well as functioning to filter water and to exchange gasses with
the atmosphere. The depth of Earth Observation (EO) data coverage for Canada, combined with present
data processing capabilities, allow for national-level product generation and scientific analyses to support
forest monitoring information needs.
From a forest monitoring perspective, data from the Landsat series of satellites have many qualities that
make them a data source of choice for national monitoring efforts, the most important of which is a spatial
resolution (30 m) that can capture human impacts over large areas. Processing of 30 m spatial resolution
data allows both national coverage and a high level of regional detail, supporting focused investigations
(such as cumulative impacts) nested within the broader national context. Time series Earth Observation
(EO) data can inform on trends, provide baseline information for monitoring, offer opportunities for
regional investigations, inform on mitigation opportunities and success, and provide transparent data for
compliance and planning, including over remote areas.
As the terrestrial monitoring system developed via NTEMS matures, the introduction of measures from
other sensors, both passive and active, has been integrated to meet the information needs of science,
policy, and management. NTEMS research is ongoing and continues to accelerate the development and
refinement of national information products for terrestrial monitoring in the context of climate change.
Herein is a list of NTEMS peer-reviewed science published to date, organized by theme.
The listed papers are largely open access. If not open access, a ResearchGate link is provided to obtain
access to the publication.
Access to NTEMS open data products (time series disturbance, land cover, etcetera) is available via:
Canada's National Forest Information Systems (NFIS):
https://opendata.nfis.org/mapserver/nfis-change_eng.html
Google Earth Engine Community Catalog: https://gee-community-catalog.org/
**Note: Publications are listed chronologically within themes.
NTEMS listing of scientific publications 3
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Key papers
Rationale and methodology: Information needs and image processing opportunities for mapping
Canada, composites and change.
White, J.C., Wulder, M.A., Hobart, G,W., Luther, J.E., Hermosilla, T., Griffiths, P., Coops, N.C.,
Hall, R.J., Hostert, P., Dyk, A., Guindon. L. 2014. Pixel-based image compositing for large-area
dense time series applications and science. Canadian Journal of Remote Sensing 40(3), 192212.
https://doi.org/10.1080/07038992.2014.945827
Full summary of data, image processing, change detection, change metrics, change labeling, and
Canada-wide project outcomes.
Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Campbell, L.B. 2016. Mass
data processing of time series Landsat imagery: pixels to data products for forest monitoring.
International Journal of Digital Earth 9(11), 1035-1054.
https://doi.org/10.1080/17538947.2016.1187673
National summary of disturbance and recovery trends (1985-2010):
White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual
characterization of 25 years of forest disturbance and recovery for Canada using Landsat time
series, Remote Sensing of Environment 194, 303-321. https://doi.org/10.1016/j.rse.2017.03.035
Frequency and nature of multiple change events (1985-2015):
Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2019. Prevalence of multiple forest
disturbances and impact on vegetation regrowth from interannual Landsat time series (1985-
2015). Remote Sensing of Environment 233, 111403. https://doi.org/10.1016/j.rse.2019.111403
National time series of forest fragmentation (1985-2015):
Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Pickell, P.D., Bolton, D.K. 2019. Impact of
time on interpretations of forest fragmentation: Three-decades of fragmentation dynamics over
Canada. Remote Sensing of Environment 222, 65-77. https://doi.org/10.1016/j.rse.2018.12.027
National leading tree species mapping:
Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence
and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of
Environment 282, 113276. https://doi.org/10.1016/j.rse.2022.113276
National forest age mapping:
Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C. 2023. Estimating and
mapping forest age across Canada’s forested ecosystems. Remote Sensing of Environment 290,
113529. https://doi.org/10.1016/j.rse.2023.113529
Satellite-Based Forest Inventory (SBFI) for Canada:
Wulder, M.A., Hermosilla, T., White, J.C., Bater, C.W., Hobart, G., Bronson, S.C. 2024.
Development and implementation of a stand-level satellite-based forest inventory for Canada.
Forestry: An International Journal of Forest Research 97 (4), 546-563.
https://doi.org/10.1093/forestry/cpad065
NTEMS listing of scientific publications 4
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Methods development
1. White, J.C., Wulder, M.A., Hobart, G,W., Luther, J.E., Hermosilla, T., Griffiths, P., Coops, N.C.,
Hall, R.J., Hostert, P., Dyk, A., Guindon. L. 2014. Pixel-based image compositing for large-area
dense time series applications and science. Canadian Journal of Remote Sensing 40(3), 192212.
https://doi.org/10.1080/07038992.2014.945827
2. Hermosilla, T., Wulder, M.A., White, J. C., Coops, N.C., Hobart, G.W. 2015. An integrated Landsat
time series protocol for change detection and generation of annual gap-free surface reflectance
composites. Remote Sensing of Environment 158, 220234.
https://doi.org/10.1016/j.rse.2014.11.005
https://www.researchgate.net/publication/269113059_An_integrated_Landsat_time_series_pr
otocol_for_change_detection_and_generation_of_annual_gap-
free_surface_reflectance_composites
3. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2015. Regional detection,
characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-
derived time-series metrics. Remote Sensing of Environment 170, 121132.
https://doi.org/10.1016/j.rse.2015.09.004
https://www.researchgate.net/publication/282327786_Regional_detection_characterization_a
nd_attribution_of_annual_forest_change_from_1984_to_2012_using_Landsat-derived_time-
series_metrics?ev=prf_pub
4. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Campbell, L.B. 2016. Mass
data processing of time series Landsat imagery: pixels to data products for forest monitoring.
International Journal of Digital Earth 9(11), 1035-1054.
https://doi.org/10.1080/17538947.2016.1187673
5. Chance, C.M., Hermosilla, T, Coops, N.C., Wulder, M.A., White, J.C. 2016. Effect of topographic
correction on forest change detection using spectral trend analysis of Landsat pixel-based
composites. International Journal of Applied Earth Observation and Geoinformation 44, 186
194. https://doi.org/10.1016/j.jag.2015.09.003
6. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2017. Updating Landsat time
series of surface-reflectance composites and forest change products with new observations.
International Journal of Applied Earth Observation and Geoinformation 63, 104-111.
https://doi.org/10.1016/j.jag.2017.07.013
7. Francini, S., Hermosilla, T., Coops, N.C., Wulder, M.A., White, J.C., Chirici, G. 2023. An
assessment approach for pixel-based image composites. ISPRS Journal of Photogrammetry and
Remote Sensing 202, 1-12. https://doi.org/10.1016/j.isprsjprs.2023.06.002
8. Hermosilla, T., Francini, S., Nicolau, A.P., Wulder, M.A., White, J.C., Coops, N.C., Chirici, G. 2024.
Clouds and Image Compositing. Cloud-Based Remote Sensing with Google Earth Engine, pp. 279-
302. Cham, Switzerland. https://doi.org/10.1007/978-3-031-26588-4_15
NTEMS listing of scientific publications 5
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Forest disturbance
9. Jarron, L.R., Hermosilla, T., Coops, N.C., Wulder, M.A., White, J.C. , Hobart G., Leckie, D.G. 2017.
Differentiation of alternate harvesting practices using annual time series of Landsat data. Forests
8(1), 1-15. https://doi.org/10.3390/f8010015
10. Ahmed, O., M.A. Wulder, J.C. White, T. Hermosilla, N.C. Coops, S.E. Franklin. 2017. Classification
of annual non-stand replacing boreal forest change in Canada using Landsat time series: A case
study in northern Ontario. Remote Sensing Letters 81(1): 2937.
https://doi.org/10.1080/2150704X.2016.1233371
11. Coops, N.C., Hermosilla, T., Wulder, M.A., White, J.C., Bolton, D.K. 2018. A thirty year, fine-scale,
characterization of area burned in Canadian forests shows evidence of regionally increasing
trends in the last decade. PLoS ONE 13(5), e0197218.
https://doi.org/10.1371/journal.pone.0197218
12. Tortini, R., Mayer, A.L., Hermosilla, T., Coops, N.C., Wulder, M.A., 2019. Using annual Landsat
imagery to identify harvesting over a range of intensities for non-industrial family forests.
Landscape and Urban Planning 188, 143-150.
https://doi.org/10.1016/j.landurbplan.2018.04.012
13. Crowley, M.A., Cardille, J.A., White, J.C., Wulder, M.A. 2019. Generating intra-year metrics of
wildfire progression using multiple open-access satellite data streams. Remote Sensing of
Environment 232, 111295. https://doi.org/10.1016/j.rse.2019.111295
14. Bolton, D.K., Coops, N.C., Hermosilla, T., Wulder, M.A., White, J.C., Ferster, C.J. 2019. Uncovering
regional variability in disturbance trends between parks and greater park ecosystems across
Canada (19852015). Scientific Reports 9(1), 1323. https://doi.org/10.1038/s41598-018-37265-4
15. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Pickell, P.D. Bolton, D.K. 2019. Impact of
time on interpretations of forest fragmentation: Three-decades of fragmentation dynamics over
Canada. Remote Sensing of Environment 222, 65-77. https://doi.org/10.1016/j.rse.2018.12.027
16. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2019. Prevalence of multiple forest
disturbances and impact on vegetation regrowth from interannual Landsat time series (1985-
2015). Remote Sensing of Environment 233, 111403. https://doi.org/10.1016/j.rse.2019.111403
17. Coops, N.C., Shang, C., Wulder, M.A., White, J.C., Hermosilla, T. 2020. Change in forest
condition: Characterizing non-stand replacing disturbances using time series satellite imagery.
Forest Ecology and Management 474, 118370. https://doi.org/10.1016/j.foreco.2020.118370
18. Cardille, J.A., Perez, E., Crowley, M.A., Wulder, M.A., White, J.C., Hermosilla, T. 2022. Multi-
sensor change detection for within-year capture and labelling of forest disturbance. Remote
Sensing of Environment 268, 112741. https://doi.org/10.1016/j.rse.2021.112741
19. Pelletier, F., Cardille, J.A., Wulder, M.A., White, J.C., Hermosilla, T. 2024. Inter- and intra-year
forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and
Landsat. Remote Sensing of Environment 301, 113931.
https://doi.org/10.1016/j.rse.2023.113931
20. Pelletier, F., Cardille, J.A., Wulder, M.A., White, J.C., Hermosilla, T. 2024. Revisiting the 2023
wildfire season in Canada. Science of Remote Sensing. 10, 100145.
https://doi.org/10.1016/j.srs.2024.100145
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Forest disturbance (continued)
21. Mulverhill, C., Coops, N. C., Wulder, M. A., White, J. C., Hermosilla, T., Bater, C.W. 2024.
Multidecadal mapping of status and trends in annual burn probability over Canada’s forested
ecosystems. ISPRS Journal of Photogrammetry and Remote Sensing 209, 279-295.
https://doi.org/10.1016/j.isprsjprs.2024.02.006
Post-disturbance forest recovery
22. Bartels, S.F., Chen, H.Y.H., Wulder, M.A., White, J.C. 2016. Trends in post-disturbance recovery
rates of Canada's forests following wildfire and harvest. Forest Ecology and Management 361,
194-207. https://doi.org/10.1016/j.foreco.2015.11.015
23. White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual
characterization of 25 years of forest disturbance and recovery for Canada using Landsat time
series, Remote Sensing of Environment 194, 303-321. https://doi.org/10.1016/j.rse.2017.03.035
24. Bourbonnais, M.L., Nelson, T.A., Stenhouse, G.B., Wulder, M.A. White, J.C., Hobart, G.W.,
Hermosilla, T., Coops, N.C., Nathoo, F., Darimont, C. 2017. Characterizing spatial-temporal
patterns of landscape disturbance and recovery in western Alberta, Canada using a functional
data analysis approach. Ecological Informatics 39, 140150.
https://doi.org/10.1016/j.ecoinf.2017.04.010
25. Frazier, R.J., Coops, N.C., Wulder, M.A., Hermosilla, T., White, J.C. 2018. Analyzing Spatial and
Temporal Variability in Short-Term Rates of Post-Fire Vegetation Return from Landsat Time
Series. Remote Sensing of Environment 205, 32-45. https://doi.org/10.1016/j.rse.2017.11.007
26. White, J.C., Saarinen, N., Kankare, V., Wulder, M.A., Hermosilla, T., Coops, N.C., Pickell, P.D.,
Holopainen, M., Hyyppä, J., Vastaranta, M. 2018. Confirmation of post-harvest spectral recovery
from Landsat time series using measures of forest cover and height derived from airborne laser
scanning data. Remote Sensing of Environment 216, 262-275.
https://doi.org/10.1016/j.rse.2018.07.004
27. White, J.C., Saarinen, N., Wulder, M.A., Kankare, V. Hermosilla, T., Coops, N.C., Holopainen, M.,
Hyyppä, J., Vastaranta, M. 2019. Assessing spectral measures of post-harvest forest recovery
with field plot data. International Journal of Applied Earth Observation and Geoinformation 80,
102114. https://doi.org/10.1016/j.jag.2019.04.010
28. White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C. 2019. Satellite time series can guide forest
restoration. Nature 569(7758), 630. https://doi.org/10.1038/d41586-019-01665-x
29. White, J.C. 2019. Improving capacity for large-area monitoring of forest disturbance and
recovery. Dissertation Forestales 272. 79 p. https://doi.org/10.14214/df.272
30. Kearney, S.P., Coops, N.C., Stenhouse, G.B., Nielsen, S.E., Hermosilla, T., White, J.C., Wulder,
M.A. 2019. Grizzly bear selection of recently harvested forests is dependent on forest recovery
rate and landscape composition. Forest Ecology and Management 449, 117459.
https://doi.org/10.1016/j.foreco.2019.117459
NTEMS listing of scientific publications 7
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Post-disturbance forest recovery (continued)
31. White, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C. 2022. Mapping, validating, and interpreting
spatio-temporal trends in post-disturbance forest recovery. Remote Sensing of Environment 271,
112904. https://doi.org/10.1016/j.rse.2022.112904
32. White, J.C., Hermosilla, T., Wulder, M.A. 2023. Pre-fire measures of boreal forest structure and
composition inform interpretation of post-fire spectral recovery rates. Forest Ecology and
Management 537, 120948. https://doi.org/10.1016/j.foreco.2023.120948
33. White, J.C. 2024. Characterizing forest recovery following stand-replacing disturbances in boreal
forests: contributions of optical time series and airborne laser scanning data. Silva Fennica 58(2),
23076. https://doi.org/10.14214/sf.23076
Forest structure
34. Zald, H., Wulder, M.A., White, J.C., Hilker, T., Hermosilla, T., Hobart, G.W., Coops, N.C. 2016.
Integrating Landsat pixel composites and change metrics with lidar plots to predictively map
forest structure and aboveground biomass in Saskatchewan, Canada. Remote Sensing of
Environment 176, 188201. https://doi.org/10.1016/j.rse.2016.01.015
35. Matasci G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Zald, H.S. 2018.
Large-area mapping of Canadian boreal forest cover, height, biomass and other structural
attributes using Landsat composites and lidar plots. Remote Sensing of Environment 209, 90
106. https://doi.org/10.1016/j.rse.2017.12.020
36. Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K.,
Tompalski, P., Bater, C.W. 2018. Three decades of forest structural dynamics over Canada's
forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment
216, 697-714. https://doi.org/10.1016/j.rse.2018.07.024
37. Bolton, D.K., Tompalski, P., Coops, N.C., White, J.C., Wulder, M.A., Hermosilla, T., Queinnec, M.,
Luther, J.E., van Lier, O.R., Fournier, R.A., Woods, M., Treitz, P. M., van Ewijk, K.Y., Graham, G.,
Quist, L., 2020. Optimizing Landsat time series length for regional mapping of lidar-derived
forest structure. Remote Sensing of Environment 239, 111645.
https://doi.org/10.1016/j.rse.2020.111645
38. Mulverhill, C., Coops, N.C., Hermosilla, T., White, J.C., Wulder, M.A. 2022. Evaluating ICESat-2 for
monitoring, modeling, and update of large area forest canopy height products. Remote Sensing
of Environment 271, 112919. https://doi.org/10.1016/j.rse.2022.112919
39. Neuenschwander, A., Duncanson, L., Montesano, P., Minor, D., Guenther, E., Hancock, S.,
Wulder, M.A., White, J.C., Purslow, M., Thomas, N., Mandel, A., Feng, T., Armston, J., Kellner,
J.R., Andersen, H.E., Boschetti, L., Fekety, P., Hudak, A., Pisek, J., Sánchez-López, N., Stereńczak,
K. 2024. Towards global spaceborne lidar biomass: Developing and applying boreal forest
biomass models for ICESat-2 laser altimetry data. Science of Remote Sensing 10, 100150.
https://doi.org/10.1016/j.srs.2024.100150
NTEMS listing of scientific publications 8
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Forest age
40. Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C. 2023. Estimating and
mapping forest age across Canada’s forested ecosystems. Remote Sensing of Environment 290,
113529. https://doi.org/10.1016/j.rse.2023.113529
Land cover
41. Franklin, S.E., Ahmed, O.S., Wulder, M.A., White, J.C., Hermosilla, T., Coops, N.C. 2015. Large-
area mapping of annual land cover dynamics using multi-temporal change detection and
classification of Landsat time series data. Canadian Journal of Remote Sensing 41(4), 293314.
https://doi.org/10.1080/07038992.2015.1089401
42. Gómez, C., White, J.C., Wulder, M.A. 2016. Optical remotely sensed time series data for land
cover classification: A review. ISPRS Journal of Photogrammetry and Remote Sensing 116, 55-72.
https://doi.org/10.1016/j.isprsjprs.2016.03.008
43. Wulder, M.A., Coops, N.C., Roy, D.P., White, J.C., Hermosilla. T. 2017. Land cover 2.0.
International Journal of Remote Sensing 39(12), 42544284.
https://doi.org/10.1080/01431161.2018.1452075
44. Wulder, M.A., Li, Z., Campbell, E.M., White, J.C., Hobart, G., Hermosilla, T., Coops, N.C. 2018. A
national assessment of wetland status and trends for Canada's forested ecosystems using 33
years of earth observation satellite data. Remote Sensing 10(10): 1623.
https://doi.org/10.3390/rs10101623
45. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2018. Disturbance-informed
annual land cover classification maps of Canada’s forested ecosystems for a 29-year Landsat
time series. Canadian Journal of Remote Sensing 44(1): 6787.
https://doi.org/10.1080/07038992.2018.1437719
46. Wulder, M.A., Hermosilla, T., Stinson, G., Gougeon, F.A., White, J.C., Hill, D.A., Smiley, B.P. 2020.
Satellite-based time series land cover and change information to map forest area consistent
with national and international reporting requirements. Forestry: An International Journal of
Forest Research 93, 331343. https://doi.org/10.1093/forestry/cpaa006
47. Li, Z., Chen, H., White, J.C., Wulder, M.A., Hermosilla, T. 2020. Discriminating treed and non-treed
wetlands in boreal ecosystems using time series Sentinel-1 data. International Journal of Applied
Earth Observation and Geoinformation 85, 102007. https://doi.org/10.1016/j.jag.2019.102007
48. Li, Z., White, J.C., Wulder, M.A., Hermosilla, T., Davidson, A.M., Comber, A.J. 2021. Land cover
harmonization using Latent Dirichlet Allocation. International Journal of Geographical
Information Science 35(2), 348-374. https://doi.org/10.1080/13658816.2020.1796131
49. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2022. Land cover classification in an era of
big and open data: Optimizing localized implementation and training data selection to improve
mapping outcomes. Remote Sensing of Environment 268, 112780.
https://doi.org/10.1016/j.rse.2021.112780
NTEMS listing of scientific publications 9
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Tree species
50. Thompson, S.D., Nelson, T.A., White, J.C., Wulder, M.A. 2015. Mapping dominant tree species
over large forested areas using Landsat best-available-pixel image composites. Canadian Journal
of Remote Sensing 41(3), 203-218. https://doi.org/10.1080/07038992.2015.1065708
51. Strickland, G.E.I., Luther, J.E., White, J.C., Wulder, M.A. 2020. Extending estimates of tree and
tree species presence-absence through space and time using Landsat composites. Canadian
Journal of Remote Sensing 46(5), 567584. https://doi.org/10.1080/07038992.2020.1811083
52. Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A. 2022. Mapping the presence
and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of
Environment 282, 113276. https://doi.org/10.1016/j.rse.2022.113276
53. Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Bater, C.W., Hobart, G.W. 2024.
Characterizing long-term tree species dynamics in Canada's forested ecosystems using annual
time series remote sensing data. Forest Ecology and Management 572, 122313.
https://doi.org/10.1016/j.foreco.2024.122313
Forest inventory
54. Bolton, D.K., White, J.C., Wulder, M.A., Coops, N.C. 2018. Updating stand-level forest inventories
using airborne laser scanning and Landsat time series data. International Journal of Applied
Earth Observation and Geoinformation 66, 174183. https://doi.org/10.1016/j.jag.2017.11.016
55. Shang, C., Coops, N.C., Wulder, M.A., White, J.C., Hermosilla, T. 2020. Update and spatial
extension of strategic forest inventories using time series remote sensing and modeling.
International Journal of Applied Earth Observation and Geoinformation 84, 101956.
https://doi.org/10.1016/j.jag.2019.101956
56. Fassnacht, F.E., White, J.C., Wulder, M.A., Næsset, E. 2024. Remote sensing in forestry: current
challenges, considerations and directions. Forestry: An International Journal of Forest Research
97(1), 1137. https://doi.org/10.1093/forestry/cpad024
57. Wulder, M.A., Hermosilla, T., White, J.C., Bater, C.W., Hobart, G., Bronson, S.C. 2024.
Development and implementation of a stand-level satellite-based forest inventory for Canada.
Forestry: An International Journal of Forest Research. https://doi.org/10.1093/forestry/cpad065
Forest growth
58. Tompalski, P., Wulder, M.A., White, J.C., Hermosilla, T., Riofrío, J., Kurz, W.A. 2024. Developing
aboveground biomass yield curves for dominant boreal tree species from time series remote
sensing data. Forest Ecology and Management 561, 121894.
https://doi.org/10.1016/j.foreco.2024.121894
NTEMS listing of scientific publications 10
2025-01-06
Landsat program and archive
59. Wulder, M.A., White, J.C., Goward, S.N., Masek, J.G., Irons, J.R., Herold, M., Cohen, W.B.,
Loveland, T.R., Woodcock, C.E. 2008. Landsat continuity: Issues and opportunities for land cover
monitoring. Remote Sensing of Environment 112(3), 955-969.
https://www.sciencedirect.com/science/article/pii/S0034425707003331
60. Wulder, M.A., White, J.C., Masek, J.G., Dwyer, J., Roy, D.P. 2011. Continuity of Landsat
observations: Short term considerations. Remote Sensing of Environment 115(2), 747-751.
http://dx.doi.org/10.1016/j.rse.2010.11.002.
61. Wulder, M.A., Masek, J.G., Cohen, W.B., Loveland, T.R., Woodcock, C.E. 2012. Opening the
archive: How free data has enabled the science and monitoring promise of Landsat. Remote
Sensing of Environment 122, 2-10. http://dx.doi.org/10.1016/j.rse.2012.01.010.
62. White, J. C., Wulder, M. A. 2014. The Landsat observation record of Canada: 19722012.
Canadian Journal of Remote Sensing 39(6): 455-467. https://doi.org/10.5589/m13-053
63. Banskota, A., Kayastha, N., Falkowski, M.J., Wulder, M.A., Froese, R.E., White, J.C. 2014. Forest
monitoring using Landsat time-series data: A review. Canadian Journal of Remote Sensing 40(5):
362384. https://doi.org/10.1080/07038992.2014.987376
64. Roy, D.P., Wulder, M.A., Loveland, T.R., Woodcock, C.E., Allen, R.G., Anderson, M.C., Helder, D.,
Irons, J.R., Johnson, D.M., Kennedy, R., Scambos, T.A., Schaaf, C. B., Schott, J.R., Sheng, Y.,
Vermote, E.F., Belward, A.S., Bindschadler, R., Cohen, W.B., Gao, F., Hipple, J.D., Hostert, P.,
Huntington, J., Justice, C.O., Kilic, A., Kovalskyy, V., Lee, Z. P., Lymburner, L., Masek, J.G.,
McCorkel, J., Shuai, Y., Trezza, R., Vogelmann, J., Wynne, R.H., Zhu, Z. 2014. Landsat-8: Science
and product vision for terrestrial global change research. Remote Sensing of Environment 145,
154-172. http://dx.doi.org/10.1016/j.rse.2014.02.001
65. Wulder, M.A, White, J.C., Loveland, T.R., Woodcock, C.E., Belward, A.S., Cohen, W.B. Fosnight,
G., Shaw, J., Masek, J.G., Roy, D.P. 2016. The global Landsat archive: Status, consolidation, and
direction. Remote Sensing of Environment 185, 271-283.
https://doi.org/10.1016/j.rse.2015.11.032
66. Saarinen, N., White, J.C., Wulder, M.A., Kangas, A., Tuominen, S., Kankare, V., Holopainen, M.,
Hyyppä, J., Vastaranta, M. 2018. Landsat archive holdings for Finland: Opportunities for forest
monitoring. Silva Fennica 52(3), 9986, 11p. https://doi.org/10.14214/sf.9986
67. Wulder, M.A., Loveland, T.R., Roy, D.P., Crawford, C.J., Masek, J.G., Woodcock, C.E., Allen, R.G.,
Anderson, M.C., Belward, A.S., Cohen, W.B., Dwyer, J., Erb, A., Gao, F., Griffiths, P., Helder, D.,
Hermosilla, T., Hipple, J.D., Hostert, P., Hughes, M.J., Huntington, J., Johnson, D.M., Kennedy, R.,
Kilic, A., Li, Z., Lymburner, L., McCorkel, J., Pahlevan, N., Scambos, T.A., Schaaf, C., Schott, J.R.,
Sheng, Y., Storey, J., Vermote, E., Vogelmann, J., White, J.C., Wynne, R.H., Zhu, Z. 2019. Current
status of Landsat program, science, and applications. Remote Sensing of Environment, 225, pp.
127-147. https://doi.org/10.1016/j.rse.2019.02.015
68. Zhe, Z., Wulder, M.A., Roy, D.P., Woodcock, C.E., Hansen, M.C., Radeloff, V.C., Healey, S.P.
Schaaf, C., Hostert, P., Strobl, P., Pekel, J-F., Lymburner, L., Pahlevan, N., Scambos, T.A. 2019.
Benefits of the Free and Open Landsat Data Policy. Remote Sensing of Environment 224, 382-
385. https://doi.org/10.1016/j.rse.2019.02.016
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69. Masek, J.G., Wulder, M.A., Markham, B., McCorkel, J., Crawford, C.J., Storey, J. Jenstrom, D.T.
2020. Landsat 9: Empowering Open Science and Applications Through Continuity. Remote
Sensing of Environment 248, 111968. https://doi.org/10.1016/j.rse.2020.111968
70. Loveland, T.R., Anderson, M.C., Huntington, J.L., Irons, J.R., Johnson, D.M., Rocchio, L.E.P.
Rocchio, Woodcock, C.E., Wulder. M.A. 2022. Seeing Our Planet Anew: Fifty Years of Landsat.
Photogrammetric Engineering and Remote Sensing 88(7), 429-436.
https://doi.org/10.14358/PERS.88.7.429
71. Wulder, M.A., Roy, D.P., Radeloff, V.C., Loveland, T.R., Anderson, M.C., Johnson, D.M., Healey,
S., Zhu, Z., Scambos, T.A., Pahlevan, N., Hansen, M., Gorelick, N., Crawford, C.J., Masek, J.G.,
Hermosilla, T., White, J.C., Belward, A.S. Schaaf, C., Woodcock, C., Huntington, J.L., Lymburner,
L., Hostert, P., Gao, F., Lyapustin, A., Pekel, J-F., Strobl, P., Cook, B.C. 2022. Fifty years of Landsat
science and impacts. Remote Sensing of Environment 280, 113195.
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Carbon accounting applications
72. Boisvenue, C., Smiley, B.P., White, J.C., Kurz, W.A., Wulder, M.A. 2016. Integration of Landsat
time series and field plots for forest productivity estimates in decision support models. Forest
Ecology and Management 376, 284297. https://doi.org/10.1016/j.foreco.2016.06.022
73. Boisvenue, C., Smiley, B.P., White, J.C., Kurz, W.A., Wulder, M.A. 2016. Improving carbon
monitoring and reporting in forests using spatially-explicit forest information. Carbon Balance
and Management 11(1), 1-16. https://doi.org/10.1186/s13021-016-0065-6
74. Boisvenue, C., White, J.C. 2019. Information needs of next-generation forest carbon models:
Opportunities for remote sensing science. Remote Sensing 11(4), 463.
https://doi.org/10.3390/rs11040463
75. Wulder, M.A. Hermosilla, T., White, J.C., Coops, N.C. 2020. Biomass status and dynamics over
Canada’s forests: Disentangling disturbed area from associated aboveground biomass
consequences. Environmental Research Letters 15, 094093. https://doi.org/10.1088/1748-
9326/ab8b11
Virtual constellations
76. Wulder, M.A., Hilker, T., White, J.C., Coops, N.C., Masek, J.G., Pflugmacher, D., Crevier, Y. 2015.
Virtual constellations for global terrestrial monitoring. Remote Sensing of Environment 170, 62-
76. https://doi.org/10.1016/j.rse.2015.09.001
77. Wulder, M.A., Hermosilla, T., White, J.C., Hobart, G.H., Masek, J.G. 2021. Augmenting Landsat
time series with Harmonized Landsat Sentinel-2 data products: Assessment of spectral
correspondence. Science of Remote Sensing 4, 100031.
https://doi.org/10.1016/j.srs.2021.100031
78. Radeloff, V.C., Roy, D.P., Wulder, M.A., Anderson, M., Cook, B., Crawford, C.J., Friedl, M., Gao, F.,
Gorelick, N., Hansen, M., Healey, S., Hostert, P., Hulley, G., Huntington, J.L., Johnson, D.M.,
NTEMS listing of scientific publications 12
2025-01-06
Neigh, C., Lyapustin, A., Lymburner, L., Pahlevan, N., Pekel, J.-F., Scambos, T.A., Schaaf, C.,
Strobl, P., Woodcock, C.E., Zhang, H.K., Zhu, Z. 2024. Need and vision for global medium-
resolution Landsat and Sentinel-2 data products. Remote Sensing of Environment 300, 113918.
https://doi.org/10.1016/j.rse.2023.113918
Other applications
79. Rickbeil, G.J.M., Hermosilla, T., Coops, N.C., White, J.C., Wulder, M.A., Lantz, T. 2016. Barren-
ground caribou (Rangifer tarandus groenlandicus) behaviour after recent fire events; integrating
caribou telemetry data with Landsat fire detection techniques. Global Change Biology 23(3),
10361047. https://doi.org/10.1111/gcb.13456
80. Bolton, D.K., Coops, N.C., Hermosilla, T., Wulder, M.A., White, J.C. 2017. Assessing variability in
post-fire structure gradients of productivity in the Canadian boreal using multiresolution remote
sensing. Journal of Biogeography 44(6), 1294-1305. https://doi.org/10.1111/jbi.12947
81. Chowdhury, S., Chao, D., Shipman, T., Wulder, M.A. 2017. Utilization of Landsat data to quantify
land-use and land-cover changes related to oil and gas activities in West-Central Alberta from
2005 to 2013, GIScience and Remote Sensing 54(5), 700-720.
https://doi.org/10.1080/15481603.2017.1317453
82. Rickbeil, G., Hermosilla, T., Coops, N.C., White, J.C., Wulder, M.A. 2017. Estimating changes in
lichen mat volume through time and related effects on barren ground caribou (Rangifer
tarandus groenlandicus) movement. PloS ONE 12(3), e0172669.
https://doi.org/10.1371/journal.pone.0172669
83. Bolton, D.K., White, J.C., Wulder, M.A., Coops, N.C. 2018. Updating stand-level forest inventories
using airborne laser scanning and Landsat time series data. International Journal of Applied
Earth Observation and Geoinformation 66, 174183. https://doi.org/10.1016/j.jag.2017.11.016
84. Rickbeil, G.J.M., T. Hermosilla, N.C. Coops, J.C. White, M.A. Wulder, T.C. Lantz, T.C. 2018.
Changing northern vegetation conditions are influencing barren ground caribou (Rangifer
tarandus groenlandicus) post-calving movement rates. Journal of Biogeography 45(3), 702-712.
https://doi.org/10.1111/jbi.13161
85. Czekajlo, A., Coops, N.C., Wulder, M.A., Hermosilla, T., Lu, Y., White, J.C., van den Bosch, M.
2020. The urban greenness score: A satellite-based metric for multi-decadal characterization of
urban land dynamics. International Journal of Applied Earth Observation and Geoinformation 93,
102210. https://doi.org/10.1016/j.jag.2020.102210
86. Shang, C., Wulder, M.A., Coops, N.C., White, J.C., Hermosilla, T. 2020. Spatially-explicit
prediction of wildfire burn probability using remotely-sensed and ancillary data. Canadian
Journal of Remote Sensing 46(3), 313-329. https://doi.org/10.1080/07038992.2020.1788385
87. Li, Z., Chen, H., White, J.C., Wulder, M.A., Hermosilla, T. 2020. Discriminating treed and non-treed
wetlands in boreal ecosystems using time series Sentinel-1 data. International Journal of Applied
Earth Observation and Geoinformation 85, 102007. https://doi.org/10.1016/j.jag.2019.102007
NTEMS listing of scientific publications 13
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Other applications (continued)
88. Czekajlo, A., Coops, N.C., Wulder, M.A., Hermosilla, T., White, J.C., van den Bosch, M. 2021.
Mapping dynamic peri-urban land use transitions across Canada using Landsat time series:
Spatial and temporal trends and associations with socio-demographic factors. Computers,
Environment and Urban Systems 88, 101653.
https://doi.org/10.1016/j.compenvurbsys.2021.101653
89. Chen, A., Lantz, T., Hermosilla, T., Wulder, M.A. 2021. Biophysical controls of increased tundra
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90. Francini, S., McRoberts, R.E., D’Amico, G., Coops, N.C., Hermosilla, T., White, J.C., Wulder, M.A.,
Marchetti, M., Mugnozza, G.S., Chirici, G. 2022. An open science and open data approach for the
statistically robust estimation of forest disturbance areas. International Journal of Applied Earth
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91. Seider, J.H., Lantz, T.C., Hermosilla, T., Wulder, M.A., Wang, J.A. 2022. Biophysical determinants
of shifting tundra vegetation productivity in the Beaufort Delta region of Canada. Ecosystems 25,
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92. Curasi, S.R., Melton, J.R., Humphreys, E.R., Hermosilla, T., Wulder, M.A. 2024. Implementing a
dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based
land surface model CLASSIC v1.45. Geoscientific Model Development. 17, 26832704.
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93. Travers-Smith, H., N.C. Coops, C. Mulverhill, M.A. Wulder, D. Ignace, Lantz, T.C. 2024. Mapping
vegetation height and identifying the northern forest limit across Canada using ICESat-2 and
Landsat satellite data. Remote Sensing of Environment. 305, 114097.
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