Accuracy assessment of the global forest watch tree cover 2000 in China

Inaccurate information on forest resources could hamper forest conservation, reforestation and sustainable management. Remote-sensing products have emerged as key tools in forest cover monitoring. The Global Forest Watch (GFW) dataset as an interactive remote sensing product, is now applied by more than 2 million users including researchers, conservationists and local communities for analyzing forest cover changes. The quality of this product varies spatially, and local validations are recommended before using the data for inventory and management tasks. Our study evaluated the accuracy and suitability of the GFW dataset for analyzing China's forest cover. We conducted a validation based on a streamlined visual interpretation procedure using high resolution optical imagery on Google Earth to map the uncertainties and inaccuracies of GFW Tree Cover 2000 in China. We then estimated China's forest area after considering the data uncertainty, made a comparison with the data reported by the National Forest Inventory of China (CNFI) to understand where and how the land-based inventory differs from the presence/absence-based remote sensing data. The results showed that the overall accuracy of the GFW Tree Cover 2000 data reached 94.5 %. The user's and producer's accuracy of forest classification was 89.26 % and 82.13 %. The sample-based area estimation using GFW showed a larger forest area than the figure reported by CNFI in mainland China, while data discrepancy varied at provincial levels. The study provides a detailed performance assessment of GFW in terms of accuracy of defining forest, and we advise the consideration of data uncertainty in forest cover estimates for future forest management.