Evaluation of consistency among three NDVI products applied to High Mountain Asia in 2000–2015

The current study evaluates consistency among three Normalized Difference Vegetation Index (NDVI) datasets, namely GIMMS, MODIS and SPOT, to characterize alpine vegetation dynamics (greening browning) across High Mountain Asia (HMA) in 2001–2015. utility of these datasets is explored evaluate the vegetation's variability at different spatial-temporal scales and, elevation, compare their spatial trends distribution patterns. In addition Pearson correlation coefficients performed quantitatively analyze inconsistency each dataset, an NDVI quality control (QC) layer Landsat are also used findings. results indicate that GIMMS has highest mean, while SPOT lowest. However, showed a browning trend for both Tianshan (TS) Qinghai Tibet Plateau (TP) rate ?0.3 × 10 ?3 per year, whereas exhibit greening (TS = 0.5 TS 0.6 TP 0.9 1.6 year). Furthermore, MODIS-SPOT shows (R GREEN 0.73; R BROWN 0.47), followed by MODIS-GIMMS, GIMMS-SPOT. overall, appears be higher TS. Finally, consistent pixels mainly distributed central stretching northeastern part, western eastern TS, account 32.14%, 8.32% concentrated southwestern inconsistent 59.54%, with 39.21% being widely HMA, 20.58% relatively pronounced southern TP. This provides baseline inferences selection reconstruction data follow-up studies on dynamics. • Three indices products were Asia. Consistency evaluation elevations, time spaces. Consistent accounted 32.14% pixels. Inconsistent 59.54% browning. value large, but less than SPOT.