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. Issue 8 (18th April 2018)

• Record Type: Journal Article
• Authors: Qiu, Jizhong; Yang, Jingxue; Wang, Yunpeng; Su, Hua
• Is Part Of: International journal of remote sensing. Volume 39:Issue 8(2018)
• Page Start: 2105
• Page End: 2118
• Publication Date: 2018-04-18
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2017.1420929
• Languages: English
• ISSNs: 0143-1161

Abstract

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.