%0 Dataset
%T Arctic Land Vegetation Dataset (1982-2015)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/7a098d73-2d3c-4a1a-b6a2-1d818a563c64
%W NCDC
%R 10.12072/ncdc.arctic-change.db7150.2026
%A Yu Linfei
%A Leng Guoyong
%K Multi source data;vegetation;land evapotranspiration;temperature effects
%X This dataset provides vegetation dynamic monitoring data for Arctic land areas (north of 66°N) from 1982 to 2015, including vegetation index (NDVI) for July and August, with a spatial resolution of 10 km and projected using the Equal-Area Scalable Earth Grid (EASE-Grid 2.0). The dataset is constructed through the fusion of multi-source remote sensing data, integrating GIMMS NDVI3g v1 (1982–2015, biweekly scale) and MODIS vegetation products (2000–2015, including MOD13C2 NDVI). Long-term, continuous, and consistent vegetation parameter sequences are generated through time-series reconstruction and spatial fusion algorithms. Advanced vegetation dynamic extraction techniques are employed in data processing: cross-calibration and radiometric normalization methods are used to eliminate systematic biases between different satellite sensors, and adaptive filtering algorithms (such as SG filtering and HANTS models) effectively remove anomalies caused by cloud contamination, atmospheric interference, and snow/ice cover. Comparisons with FLUXNET flux station vegetation observations and ground survey data show that NDVI errors are controlled within ±0.05, and the detection accuracy for growing season length reaches 85%.