Assessing spatial distribution and quantification of native trees in Saskatchewan’s prairie landscape using remote sensing techniques DOI Creative Commons
Elham Shafeian, Bryan J. Mood,

Kenneth W. Belcher

et al.

European Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 58(1)

Published: Dec. 11, 2024

The importance of trees in non-forest landscapes has been the focus only a few studies. However, these provide many important ecosystem services. In this study, we mapped and quantified using Sentinel-2 (S2) very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed Random Forest (RF) classification to map spatial distribution native different scenarios. optimal model showed an overall accuracy kappa 0.99 0.98, respectively. 40,500 km2 tree cover, including cover (approximately 29,565 ≈10.5%), excluding plantations, regional provincial parks, water bodies Canadian prairie region Saskatchewan. According our results, highest numbers were found eastern northwestern parts study area – cluster "BLK_1" "Black" soil zone, with total 5,388 13,233 km2, lowest southwest side "BRN_6" "Brown" 2.38 979.5 This research is as detecting quantifying integral part studies on carbon sequestration, economics, effective management strategies.

Language: Английский

Stand Age Affects Biomass Allocation and Allometric Models for Biomass Estimation: A Case Study of Two Eucalypts Hybrids DOI Open Access

Runxia Huang,

Wankuan Zhu,

Apeng Du

et al.

Forests, Journal Year: 2025, Volume and Issue: 16(2), P. 193 - 193

Published: Jan. 21, 2025

We studied the effects of stand age on allocation biomass and allometric relationships among component in five stands ages (1, 3, 5, 7, 8 years old) two eucalypts hybrids, including Eucalyptus urophylla × E. grandis tereticornis, Leizhou Peninsula, China. The stem, bark, branch, leaf, root from 60 destructively harvested trees were quantified. Allometric models applied to examine relationship between tree predictor variable (diameter at breast height, D, H). Stand was introduced into explore effect estimation. results showed following: (1) significantly affected distribution each component. proportion stem total increased with age, proportions leaf decreased first then age. (2) There close (i.e., components biomass, aboveground per tree) diameter height (D), (H), product (DH), square (D2H). measurement parameters (D, H, DH, D2H) could be assessment plantation. (3) equations that included as a complementary improved fit enhanced accuracy estimates. optimal independent for prediction model varied according organ. These indicate has an important influence allocation. considering improve carbon sequestration estimates plantations.

Language: Английский

Citations

0
Enhanced forest inventories in Canada: implementation, status, and research needs DOI
Joanne C. White, Piotr Tompalski, Christopher W. Bater

et al.

Canadian Journal of Forest Research, Journal Year: 2025, Volume and Issue: 55, P. 1 - 37

Published: Jan. 1, 2025

Forest inventory practices in Canada have evolved over time with changes forest management priorities, advances technology, fluctuations the marketplace, societal expectations, and generational shifts workforce. Provincial territorial governments are vested responsibilities each jurisdiction has adopted approaches that reflect jurisdictional information needs contexts. Typically, these inventories strategic nature spatially explicit, providing stand-level attribute derived from a two-phase approach involving manual air photo interpretation stratified ground plot sampling. Airborne laser scanning (ALS; also known as light detection ranging or lidar) emerged transformative data source for is now considered operational, resulting outputs commonly referred to enhanced (EFI). Herein we review synthesize how EFIs influencing practice Canada. We characterize spatial coverage characteristics of ALS acquired purposes, summarize current status EFI implementation within Canada’s provinces territories, identify emerging trends associated EFIs, consider broader global context. highlight common research gaps towards development nationally globally relevant agenda support greater integration remotely sensed into programs beyond.

Language: Английский

Citations

0
Forest aboveground biomass estimation using deep learning data fusion of ALS, multispectral, and topographic data DOI
Harry Seely, Nicholas C. Coops, Joanne C. White

et al.

International Journal of Remote Sensing, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 39

Published: April 22, 2025

Language: Английский

Citations

0
Characterizing long-term tree species dynamics in Canada’s forested ecosystems using annual time series remote sensing data DOI Creative Commons
Txomin Hermosilla, Michael A. Wulder, Joanne C. White

et al.

Forest Ecology and Management, Journal Year: 2024, Volume and Issue: 572, P. 122313 - 122313

Published: Oct. 5, 2024

Language: Английский

Citations

2
Forest Biomass Estimation Using Deep Learning Data Fusion of Lidar, Multispectral, and Topographic Data Remote Sensing of Environment DOI
Harry Seely, Nicholas C. Coops, Joanne C. White

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

0
Assessing spatial distribution and quantification of native trees in Saskatchewan’s prairie landscape using remote sensing techniques DOI Creative Commons
Elham Shafeian, Bryan J. Mood,

Kenneth W. Belcher

et al.

European Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 58(1)

Published: Dec. 11, 2024

The importance of trees in non-forest landscapes has been the focus only a few studies. However, these provide many important ecosystem services. In this study, we mapped and quantified using Sentinel-2 (S2) very high-resolution (VHR) Google satellite imagery without any field campaigns. We performed Random Forest (RF) classification to map spatial distribution native different scenarios. optimal model showed an overall accuracy kappa 0.99 0.98, respectively. 40,500 km2 tree cover, including cover (approximately 29,565 ≈10.5%), excluding plantations, regional provincial parks, water bodies Canadian prairie region Saskatchewan. According our results, highest numbers were found eastern northwestern parts study area – cluster "BLK_1" "Black" soil zone, with total 5,388 13,233 km2, lowest southwest side "BRN_6" "Brown" 2.38 979.5 This research is as detecting quantifying integral part studies on carbon sequestration, economics, effective management strategies.

Language: Английский

Citations

0