CLUSTERING CHLOROPHYLL-A SATELLITE DATA USING QUANTILES

• 成果类型: Article
• 署名作者: Gaetan, Carlo; Girardi, Paolo; Pastres, Roberto; Mangin, Antoine
• 署名单位: Universita Ca Foscari Venezia
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/16-AOAS923
• 发表日期: 2016
• 页码: 964-988
• 关键词: time-series; regression; CURVES; ocean; MODEL

摘要

The use of water quality indicators is of crucial importance to identify risks to the environment, society and human health. In particular, the Chlorophyll type A (Chl-a) is a shared indicator of trophic status and for monitoring activities it may be useful to discover local dangerous behaviours (for example, the anoxic events). In this paper we consider a comprehensive data set, covering the whole Adriatic Sea, derived from Ocean Colour satellite data, during the period 2002-2012, with the aim of identifying homogeneous areas. Such zonation is becoming extremely relevant for the implementation of European policies, such the Marine Strategy Framework Directive. As an alternative to clustering based on an average value over the whole period, we propose a new clustering procedure for the time series. The procedure shares some similarities with the functional data clustering and combines nonparametric quantile regression with an agglomerative clustering algorithm. This approach permits to take into account some features of the time series as nonstationarity in the marginal distribution and the presence of missing data. A small simulation study is also presented for illustrating the relative merits of the procedure.