Assessing spatial distribution and quantification of native trees in Saskatchewan’s prairie landscape using remote sensing techniques

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

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Publication Details

Journal
European Journal of Remote Sensing
Published
2024-12-11
DOI
https://doi.org/10.1080/22797254.2024.2438638
Citations
3
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.38

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article

Assessing spatial distribution and quantification of native trees in Saskatchewan’s prairie landscape using remote sensing techniques

Bryan J. Mood, Colin P. Laroque, Elham Shafeian, Kenneth W. Belcher
3 citations
European Journal of Remote Sensing
Remote Sensing in Agriculture
1.38
article

Assessing spatial distribution and quantification of native trees in Saskatchewan’s prairie landscape using remote sensing techniques

Bryan J. Mood, Colin P. Laroque, Elham Shafeian, Kenneth W. Belcher
article en
3 citations

Abstract

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

European Journal of Remote SensingVol. 58(1)
University of Saskatchewan (CA)
Environment and Climate Change Canada
Openalex Percentile: Top 17%
Remote Sensing in Agriculture
1.38
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