Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion
Abstract
:1. Introduction
2. Study Area
3. Data and Methods
3.1. Data
3.1.1. JRC Water Transition Map
3.1.2. Landsat Image Collection
3.1.3. Auxiliary Data
3.2. Method
3.2.1. Data Preprocessing
3.2.2. LandTrendr Algorithm
3.2.3. Greening Trend Analysis
3.2.4. Machine Learning Model
4. Results
4.1. Analysis of the Detected Lake Drainage Events
4.2. Analysis of Vegetation Dynamics in Drained Lake Basins
4.3. Quantifying the Contribution to the Regional Greening Trend
4.4. Identifying Key Environmental Drivers Influencing DLBs Vegetation
5. Discussion and Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Parameter | Value | Description |
---|---|---|
learning_rate | 0.1 | Rate of weight adjustment in boosting |
max_depth | 40 | Max depth of individual trees |
min_samples_leaf | 5 | Minimum samples in a leaf node |
l2_regularization | 0.1 | L2 regularization for leaf weights |
max_bins | 60 | Maximum number of bins for grouping |
max_iter | 800 | Maximum boosting iterations during training |
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Liu, A.; Chen, Y.; Cheng, X. Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion. Remote Sens. 2023, 15, 4561. https://doi.org/10.3390/rs15184561
Liu A, Chen Y, Cheng X. Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion. Remote Sensing. 2023; 15(18):4561. https://doi.org/10.3390/rs15184561
Chicago/Turabian StyleLiu, Aobo, Yating Chen, and Xiao Cheng. 2023. "Effects of Thermokarst Lake Drainage on Localized Vegetation Greening in the Yamal–Gydan Tundra Ecoregion" Remote Sensing 15, no. 18: 4561. https://doi.org/10.3390/rs15184561