Understanding vegetation changes in northern China and Mongolia with change vector analysis

Area of Science:

• Environmental Science
• Remote Sensing
• Climate Science

Background:

• Established link between vegetation and climate change.
• Remote sensing, particularly NDVI time series, detects vegetation shifts.

Purpose of the Study:

• Utilize Change Vector Analysis (CV magnitude) to understand vegetation dynamics.
• Identify and characterize regions of vegetation change.
• Predict future vegetation changes.

Main Methods:

• Employed Change Vector Analysis (CV magnitude) on 10-day remote sensing data (April-October).
• Analyzed statistical measures (maxima, range, std dev, mean, minima) of CV magnitude.
• Identified 11 distinct regions of vegetation change.

Main Results:

• CV magnitude effectively indicates vegetation condition variations across years.
• 11 typical regions with distinct vegetation changes (1999-2006) were identified.
• Months of maximum CV magnitude were determined for predictive insights.

Conclusions:

• CV magnitude is a valuable indicator for comparing inter-annual vegetation conditions.
• The study successfully delineated 11 regions with significant vegetation changes.
• Analysis provides a basis for predicting future vegetation dynamics.