A comparison of NDVI and EVI in the DisTrad model for thermal sub-pixel mapping in densely vegetated areas: a case study in Southern China

ABSTRACT

The DisTrad (Disaggregation Procedure for Radiometric Surface Temperature) model shows limited applicability for sub-pixel mapping of thermal remote-sensing images in densely vegetated areas due to the phenomenon of normalized difference vegetation index (NDVI) saturation. In this article, we compared the effect of NDVI and enhanced vegetation index (EVI) in the DisTrad model for thermal sub-pixel mapping in densely vegetated areas due to their different sensitivity in densely vegetated areas. Taking Ganzhou in Southern China as an example, we produced 250-m thermal remote-sensing images from a 1000-m image using 250-m NDVI and EVI data. After comparing with the synchronous 90-m thermal image from advanced spaceborne thermal emission and reflection radiometer, we found that the EVI can achieve a better result than NDVI in densely vegetated areas.

Acknowledgements

Natural Science Foundation, NSFC (41401485), the China National Key Technology R&D Program (2012BAH32B03) and the China National 863 Program (2006AA06A306) are acknowledged for financial supports. Jake Carpenter of Beverly Hills English is thanked for the comments and corrections. This is contribution No. IS-2485 from GIGCAS.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by NSFC [41401485]; the China National Key Technology R&D Program [2012BAH32B03]; China National 863 Program [2006AA06A306] and Natural Science Foundation.