Assessment of values and trends in coarse spatial resolution NDVI datasets in Southeast Asia landscapes. Issue 1 (1st January 2018)

• Record Type: Journal Article
• Authors: Arjasakusuma, Sanjiwana; Yamaguchi, Yasushi; Nakaji, Tatsuro; Kosugi, Yoshiko; Shamsuddin, Siti-Aisah; Lion, Marryanna
• Is Part Of: European journal of remote sensing. Volume 51:Issue 1(2018)
• Page Start: 863
• Page End: 877
• Publication Date: 2018-01-01
• Subjects: Pairwise correlation -- trend assessment -- breakpoint analysis -- spatial similarity; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2018.1496799
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: Normalized difference vegetation index (NDVI) has been widely applied for monitoring vegetation dynamics. However, NDVI values are known to be profoundly affected by various external factors. In this study, the variation of NDVI values and trends among the several long-term NDVI datasets with resolution of 1, 4 and 8 km were assessed to understand the differences between the available datasets. The assessment items were 1) Pearson's correlation coefficient, 2) trend map and breakpoint spatial similarities and 3) comparison of NDVI from Landsat and Flux tower in 2007–2015. The comparison revealed a maximum correlation coefficient of 0.67 among NDVI datasets and average spatial similarity of 37.2% among the trend maps estimated from NDVI datasets. Furthermore, there was a possibility of having significantly opposite trends between two trend maps from different NDVI products. Comparisons with NDVI from vegetation pixel in Landsat 5 TM and 8 OLI resulted in the R 2 between 0.06 and 0.68 and RMSE of 0.07–0.2, while comparison with NDVI from flux tower data yielded the RMSE of 0.04–0.41, although the R 2 was relatively weak at 0–0.18. Our study highlights the possibility of differences among NDVI datasets, and suggests that these differences should be reconciled especially in time-series analysis.