Temporal partial unmixing of exotic salt cedar using Landsat time series. Issue 5 (3rd May 2016)

• Record Type: Journal Article
• Authors: Diao, Chunyuan; Wang, Le
• Is Part Of: Remote sensing letters. Volume 7:Issue 5(2016)
• Page Start: 466
• Page End: 475
• Publication Date: 2016-05-03
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2016.1149250
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: In the south-western United States, the rapid colonization of exotic salt cedar ( Tamarix spp.) along the riparian corridors poses a serious threat to the native plant diversity. Monitoring the salt cedar abundance in diversified riparian ecosystems is critically essential for evaluating the biodiversity loss and developing corresponding restoration strategies. To date, it still remains a significant challenge to estimate the abundance of plant species within a pixel, as many plants share similar spectral signatures. This challenge is even more daunting in species diverse ecosystems due to the difficulty of securing all the endmembers (e.g. plant species) in unmixing procedures. The objective of this study is to introduce a new concept, temporal partial unmixing, to estimate the relative abundance of plant species using Landsat time series. Temporal partial unmixing only requires the signature of the target endmember, but it emphasizes the importance of the temporal dimension of the target signature in estimating the corresponding abundance. Two types of temporal signatures that capture the phenological trajectory of the salt cedar growth were devised in this study. Compared to the traditional partial unmixing method ( R 2 = 0.35), temporal partial unmixing that exploited the temporal signatures greatly improved the relative abundance estimation accuracy ( R 2 = 0.56 or 0.49). It is concluded that the proposed temporal partial unmixing, along with the readily available Landsat imagery, offers unprecedented opportunities to monitor the abundance dynamics of plant species, especially in spatially heterogeneous landscapes.