Mapping rubber tree plantations using a Landsat-based phenological algorithm in Xishuangbanna, southwest China

Abstract

A simple and effective phenology-based algorithm was developed to detect and map rubber tree plantations in Xishuangbanna, a prefecture in southwest China’s Yunnan province. This algorithm highlighted the unique phenological characteristics of deciduous rubber tree plantations during the dry season. Phenology of rubber tree plantations and natural evergreen forests was delineated with Normalized Difference Vegetation Index (NDVI), Land Surface Water Index (LSWI) and Normalized Burn Ratio (NBR) derived from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and Operational Land Imager imagery during 2009–2014. The results showed that the differences of NBR were larger than those of NDVI and LSWI from defoliation stage to foliation stage. Then, the change rate of NBR derived between defoliation stage and foliation stage was used to map rubber tree plantations in 2014, by combining a Landsat-based forest mask and a Digital Elevation Model mask. Our study demonstrates that Landsat imagery holds great potential for rubber tree plantations mapping, as it not only improves the classification results but also reduces the data demand.

Acknowledgements

Landsat-5/7/8 imagery is available from the US Geological Survey (USGS) EROS Data Center. Special thanks would go to Dr Johan Pontus Olofsson from Boston University for his guidance on the accuracy assessment. We thank the anonymous reviewers and the editors for their comments that helped improve the manuscript.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) under Grants [41271117, 41301090 and 41401625].