Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment

Area of Science:

• Ecology
• Remote Sensing
• Climate Change Science

Background:

• Satellite-derived indices of photosynthetic activity are crucial for monitoring global vegetation productivity.
• Long-term vegetation records require careful handling of uncertainties in satellite data time series.
• Assessing ecosystem responses to climate change relies on accurate vegetation productivity assessments.

Purpose of the Study:

• To compare long-term vegetation productivity changes at high northern latitudes (>50°N) using various satellite NDVI datasets.
• To identify areas of agreement and conflict among different NDVI datasets regarding vegetation productivity trends.
• To evaluate the impact of data processing and sensor differences on vegetation productivity trend assessments.

Main Methods:

• Analysis of growing season Normalized Difference Vegetation Index (NDVI) trends from GIMMSg, GIMMS3g, SeaWiFS, SPOT-VGT, and MODIS datasets.
• Comparison of NDVI time series over common periods to identify consistent and conflicting patterns.
• Statistical analysis of vegetation productivity trends, focusing on significant increases (greening) and decreases.

Main Results:

• Large areas (40%) showed similar vegetation productivity trends across datasets, while others exhibited conflicting patterns.
• The GIMMS3g dataset indicated significant greening in over 15% of the study area, a trend not observed in the predecessor GIMMSg.
• Discrepancies, particularly pronounced greening in GIMMS3g for Eurasia, have implications for previous findings based on GIMMSg.

Conclusions:

• Significant uncertainties exist in assessing ecosystem responses to climate change using satellite-derived vegetation indices.
• The newer GIMMS3g dataset reveals more pronounced greening trends than older datasets, necessitating re-evaluation of past studies.
• Further validation of NDVI time series with field measurements is essential for robust ecosystem change assessments.