A time series of annual land use and land cover maps of China from 1982 to 2013 generated using AVHRR GIMMS NDVI3g data

A time series of annual land use and land cover (LULC) maps that cover an extended period of time is a key dataset for climatological studies investigating land-atmosphere interaction. Change in LULC can influence regional climate by altering the surface roughness, soil moisture, heat flux partition, and terrestrial carbon storage. Although annual global LULC maps are generated from Moderate-resolution Imaging Spectroradiometer (MODIS) data, the earliest MODIS LULC map is for 2001, which limits the potential time period for climatological analyses. This study produced a continuous series of annual LULC maps of China from 1982 to 2013 using random forest classification of 19 phonological metrics derived from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) third generation NDVI (NDVI3g) data. The classifier was trained using reference data derived from the MODIS land cover type product (MCD12Q1). Based on a comparison with Google Earth images, the overall accuracy of a simplified eight-class version of our 2012 LULC map is 73.8%, which is not significantly different from the accuracy of the MODIS map of the same year. Our maps indicate that for the three decades studied, the area of croplands and forests in China increased, and the area of grasslands decreased. These annual maps of land cover will be an important dataset for future climate studies, and the methodologies used in this study can be applied to other geographical regions where availability of continuous time series of LULC maps is limited. (C) 2017 Elsevier Inc. All rights reserved.