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The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
by
Li, Shuangcheng
, Airiken, Muhadaisi
in
Artificial intelligence
/ China
/ Climate change
/ Climatic changes
/ Distribution
/ Ecological effects
/ Environmental aspects
/ Environmental impact
/ Environmental quality
/ Environmental security
/ Forecasts and trends
/ Geography
/ Google Earth Engine
/ Internet
/ Land use
/ Machine learning
/ Measurement
/ Monitoring
/ Observations
/ Precipitation
/ Principal components analysis
/ Regression analysis
/ Remote sensing
/ Remote Sensing-based Ecological Index
/ SHAP
/ Soil moisture
/ Soil temperature
/ soil water
/ Spatial variations
/ Statistical analysis
/ temperature
/ Time series
/ Trends
2024
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The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
by
Li, Shuangcheng
, Airiken, Muhadaisi
in
Artificial intelligence
/ China
/ Climate change
/ Climatic changes
/ Distribution
/ Ecological effects
/ Environmental aspects
/ Environmental impact
/ Environmental quality
/ Environmental security
/ Forecasts and trends
/ Geography
/ Google Earth Engine
/ Internet
/ Land use
/ Machine learning
/ Measurement
/ Monitoring
/ Observations
/ Precipitation
/ Principal components analysis
/ Regression analysis
/ Remote sensing
/ Remote Sensing-based Ecological Index
/ SHAP
/ Soil moisture
/ Soil temperature
/ soil water
/ Spatial variations
/ Statistical analysis
/ temperature
/ Time series
/ Trends
2024
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Do you wish to request the book?
The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
by
Li, Shuangcheng
, Airiken, Muhadaisi
in
Artificial intelligence
/ China
/ Climate change
/ Climatic changes
/ Distribution
/ Ecological effects
/ Environmental aspects
/ Environmental impact
/ Environmental quality
/ Environmental security
/ Forecasts and trends
/ Geography
/ Google Earth Engine
/ Internet
/ Land use
/ Machine learning
/ Measurement
/ Monitoring
/ Observations
/ Precipitation
/ Principal components analysis
/ Regression analysis
/ Remote sensing
/ Remote Sensing-based Ecological Index
/ SHAP
/ Soil moisture
/ Soil temperature
/ soil water
/ Spatial variations
/ Statistical analysis
/ temperature
/ Time series
/ Trends
2024
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The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
Journal Article
The Dynamic Monitoring and Driving Forces Analysis of Ecological Environment Quality in the Tibetan Plateau Based on the Google Earth Engine
2024
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Overview
As a region susceptible to the impacts of climate change, evaluating the temporal and spatial variations in ecological environment quality (EEQ) and potential influencing factors is crucial for ensuring the ecological security of the Tibetan Plateau. This study utilized the Google Earth Engine (GEE) platform to construct a Remote Sensing-based Ecological Index (RSEI) and examined the temporal and spatial dynamics of the Tibetan Plateau’s EEQ from 2000 to 2022. The findings revealed that the RSEI of the Tibetan Plateau predominantly exhibited a slight degradation trend from 2000 to 2022, with a multi-year average of 0.404. Utilizing SHAP (Shapley Additive Explanation) to interpret XGBoost (eXtreme Gradient Boosting), the study identified that natural factors as the primary influencers on the RSEI of the Tibetan Plateau, with temperature, soil moisture, and precipitation variables exhibiting higher SHAP values, indicating their substantial contributions. The interaction between temperature and precipitation showed a positive effect on RSEI, with the SHAP interaction value increasing with rising precipitation. The methodology and results of this study could provide insights for a comprehensive understanding and monitoring of the dynamic evolution of EEQ on the Tibetan Plateau amidst the context of climate change.
Publisher
MDPI AG
Subject
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