Canada

Stinson, G.; Magnussen, Steen; Boudewyn, Paul; Eichel, F.; Russo, Glenda; Cranny, Morgan; Song, Yu

doi:10.1007/978-3-319-44015-6_12

Cited by 6 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Photo plots are 2 km × 2 km areas located on the nodes of a Canada-wide 20 × 20 km grid within which forest stands polygons are delineated by photo interpretation. For each polygon, estimates had been provided for a standardized suite of forest attributes using a combination of photo interpretation and modelling as part of the National Forest Inventory procedure (Gillis et al 2005;Boudewyn et al 2007;Stinson et al 2016). Beaudoin et al (2014) rasterized the photo plots on the MODIS 250 m × 250 m grid and estimated the value of attributes within each resulting pixel as the spatial average of values found in the underlying polygons.…”

Section: Response Variablesmentioning

confidence: 99%

“…For this purpose, Beaudoin et al (2014) produced the first Canada-wide maps of forest attributes at 250 m resolution. These maps were produced using k nearest neighbors (kNN) interpolation methodology, attribute values from the photo plots of Canada's National Forest Inventory (NFI) (Gillis et al 2005;Stinson et al 2016) as reference data, and 2001 MODIS imagery as the main source of predictive variables.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery

et al. 2018

View full text Add to dashboard Cite

Mapping Canada’s forests is a significant challenge given their extent and the interprovincial differences in forest inventories. We created new sets of nationally consistent forest attribute maps for the years 2001 and 2011 by building upon previously published work with the objective to determine if sequential maps of forest attributes could be used to quantify changes over time. We first refined our previously published methodology of using the k nearest neighbors (kNN) prediction method and MODIS spectral reflectance data as predictive variables. The maps were generated using an improved reference dataset and a new analytical kNN workflow. We then evaluated 2001 to 2011 changes in two key attributes, aboveground biomass and percent tree cover, on pixels identified from published sources as having undergone fire, harvest, or postdisturbance regrowth during that period. For all three change types, average changes in both aboveground biomass and percent tree cover between 2001 and 2011 matched expectations relative to the dynamics of Canadian forests. Our results support the use of sequential national maps of forest attributes for evaluating regionally aggregated disturbance-related changes in forest properties. The new forest attribute maps are available from Beaudoin et al. (2017 ; doi: 10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990) at http://ouvert.canada.ca/data/fr/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 .

show abstract

Section: Response Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The number of sample units without T 2 information is n -n obs . Note that the timing of data collection in Canada's NFI is largely determined by Provincial and Territorial jurisdictions (Stinson et al 2016). Data in support of an estimate of state at T t will have been collected during a multiyear period.…”

Section: Estimation Objectives and Sample Datamentioning

confidence: 99%

“…Canada's National Forest Inventory (NFI) (Gillis et al 2005, Stinson et al 2016) is facing an issue of data imbalance. Options to address the imbalance in photo-interpreted data are needed.…”

Section: Introductionmentioning

confidence: 99%

Updating Canada’s National Forest Inventory with multiple imputations of missing contemporary data

Magnussen

StinsonGraham

BoudewynPaul

2017

The Forestry Chronicle

Self Cite

View full text Add to dashboard Cite

Canada's National Forest Inventory (NFI) is facing an issue of spatial imbalance in photo interpreted data from 400 ha photo-plots available for estimation of state and change. Multiple imputations (MI) of missing data is therefore considered as a means to mitigate a potential bias arising from spatial imbalance, and-to a lesser degree-improve the precision relative to what can be achieved with the subset of plots having current data. In this study we explored MI with data from three study sites located in the provinces of Quebec, Ontario, and Saskatchewan. Specifically, we looked at state at time T 2 and change between T 1 and T 2 in cover-type area proportions and in per unit area stem volume. At each location we found significant T 1 differences in these attributes between plots with and without T 2 data. A MI procedure with 20 replications of stochastic model-based imputations of missing data was therefore effective as a way to mitigate a bias that would arise if T 2 inference was based exclusively on plots with T 2 data. Possible differences between the T 2 and T 1 photointerpretation, paired with no efficient stratification of disturbed and undisturbed plots, largely eliminated expected gains in precision from the MI boosting of the effective T 2 sample size. Despite recognized limitations, we recommend MI as an effective tool to counteract an emerging spatial imbalance in the NFI.Key words: forest cover-types, area proportions, stem volume, disturbance rates, ratio estimators. RÉSUMÉL'inventaire forestier national du Canada (NFI) est confronté à une problématique de déséquilibre dans les données de placettes photographiques de 400 ha disponibles pour évaluer l' état de la forêt et son changement. On envisage donc d'utiliser l'imputation multiple (MI) des données manquantes afin d'amoindrir le biais occasionné par le déséquilibre spatial et, dans une moindre mesure, améliorer la précision par rapport à ce qu'il est possible d'atteindre avec le sous-ensemble de placettes pour lesquelles nous disposons de données à jour. Dans cette étude, nous avons exploré les possibilités de MI avec les données provenant de trois sites d' étude situés dans les provinces de Québec, de l'Ontario et de la Saskatchewan. De façon plus particulière, nous nous sommes intéressés à l' état à temps T 2 et au changement survenu entre T 1 et T 2 dans les proportions des surfaces par type de couvert et le volume par tige par unité de surface. À chaque endroit nous avons observé des différences significatives pour ces paramètres à T 1 selon qu' on utilisait ou non les données de T 2 . Une procé-dure MI avec 20 répétitions d'imputations des données manquantes basées sur un modèle stochastique s' est avérée efficace pour atténuer le biais qui résulterait si l'inférence à T 2 reposait uniquement sur les placettes disposant des données à T 2 . Toutefois, les différences dans la technique de photo-interprétation à T 1 et à T 2 combinées à l'absence de stratification des placettes perturbées et intactes a masqué la majeure partie du g...

show abstract

Remote sensing in forestry: current challenges, considerations and directions

Fassnacht

White

Wulder

et al. 2023

Forestry: An International Journal of Forest Research

View full text Add to dashboard Cite

Remote sensing has developed into an omnipresent technology in the scientific field of forestry and is also increasingly used in an operational fashion. However, the pace and level of uptake of remote sensing technologies into operational forest inventory and monitoring programs varies notably by geographic region. Herein, we highlight some key challenges that remote sensing research can address in the near future to further increase the acceptance, suitability and integration of remotely sensed data into operational forest inventory and monitoring programs. We particularly emphasize three recurrent themes: (1) user uptake, (2) technical challenges of remote sensing related to forest inventories and (3) challenges related to map validation. Our key recommendations concerning these three thematic areas include (1) a need to communicate and learn from success stories in those geographic regions where user uptake was successful due to multi-disciplinary collaborations supported by administrative incentives, (2) a shift from regional case studies towards studies addressing ‘real world’ problems focusing on forest attributes that match the spatial scales and thematic information needs of end users and (3) an increased effort to develop, communicate, and apply best-practices for map and model validation including an effort to inform current and future remote sensing scientists regarding the need for and the functionalities of these best practices. Finally, we present information regarding the use of remote sensing for forest inventory and monitoring, combined with recommendations where possible, and highlighting areas of opportunity for additional investigation.

show abstract

Canada

Cited by 6 publications

References 18 publications

Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery

Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery

Updating Canada’s National Forest Inventory with multiple imputations of missing contemporary data

Remote sensing in forestry: current challenges, considerations and directions

Contact Info

Product

Resources

About