Version 1
: Received: 6 April 2024 / Approved: 8 April 2024 / Online: 9 April 2024 (08:49:48 CEST)
How to cite:
Cook, M.; Chapman, T.; Hart, S.; Paudel, A.; Balch, J. Mapping Quaking Aspen (Populus tremuloides Michx.) Using Seasonal Sentinel-1 and Sentinel-2 Composite Imagery across the Southern Rockies, USA. Preprints2024, 2024040606. https://doi.org/10.20944/preprints202404.0606.v1
Cook, M.; Chapman, T.; Hart, S.; Paudel, A.; Balch, J. Mapping Quaking Aspen (Populus tremuloides Michx.) Using Seasonal Sentinel-1 and Sentinel-2 Composite Imagery across the Southern Rockies, USA. Preprints 2024, 2024040606. https://doi.org/10.20944/preprints202404.0606.v1
Cook, M.; Chapman, T.; Hart, S.; Paudel, A.; Balch, J. Mapping Quaking Aspen (Populus tremuloides Michx.) Using Seasonal Sentinel-1 and Sentinel-2 Composite Imagery across the Southern Rockies, USA. Preprints2024, 2024040606. https://doi.org/10.20944/preprints202404.0606.v1
APA Style
Cook, M., Chapman, T., Hart, S., Paudel, A., & Balch, J. (2024). Mapping Quaking Aspen (Populus tremuloides Michx.) Using Seasonal Sentinel-1 and Sentinel-2 Composite Imagery across the Southern Rockies, USA. Preprints. https://doi.org/10.20944/preprints202404.0606.v1
Chicago/Turabian Style
Cook, M., Asha Paudel and Jennifer Balch. 2024 "Mapping Quaking Aspen (Populus tremuloides Michx.) Using Seasonal Sentinel-1 and Sentinel-2 Composite Imagery across the Southern Rockies, USA" Preprints. https://doi.org/10.20944/preprints202404.0606.v1
Abstract
Quaking aspen (Populus tremuloides Michx.) is an important deciduous species in western U.S. forests. Existing maps of aspen distribution are based on Landsat imagery and often miss small stands (<0.09 ha or 30 m²), which rapidly regrow when managed or following disturbance. In this study, we present methods for deriving a new regional map of aspen forests using one year of Sentinel-1 (S1) and Sentinel-2 (S2) imagery in Google Earth Engine. We assessed the annual phenology of aspen in the Southern Rockies and leveraged the frequent temporal resolution of S1 and S2 to create ecologically relevant seasonal composites. Additionally, we derived spectral indices and radar textural features targeting the canopy structure, moisture, and chlorophyll content. Using spatial block cross-validation and Random Forests, we assessed the accuracy of different scenarios and selected the best performing set of features for classification. Comparisons were then made with existing landcover products across the study region. The resulting map improves on existing landcover products in both accuracy (average F1-score = 93.1%) and detection of smaller forest patches. These methods enable accurate mapping at spatial and temporal scales relevant to forest management for one of the most widely distributed tree species in North America.
Keywords
Forest species classification; Sentinel-1; Sentinel-2; seasonal imagery; phenology; spatial block cross-validation; Random Forests; Southern Rockies; landscape patch dynamics; Google Earth Engine
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
