Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models

    Authors

    N. B. Chang; Z. M. Xuan;Y. J. Yang

    Comments

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    Abbreviated Journal Title

    Remote Sens. Environ.

    Keywords

    Remote sensing; Coastal bay; Nutrient monitoring; MODIS; Genetic; programming; CHLOROPHYLL-A ESTIMATION; THEMATIC MAPPER DATA; OCEAN COLOR; SATELLITE; DATA; TROPHIC STATE; WATERS; SEA; QUANTIFICATION; ALGORITHMS; FINLAND; Environmental Sciences; Remote Sensing; Imaging Science & Photographic; Technology

    Abstract

    This paper explores the spatiotemporal patterns of total phosphorus (TP) in Tampa Bay (Bay), Florida, with the aid of Moderate Resolution Imaging Spectroradiometer (MODIS) images and genetic programming (GP) models. The study was designed to link TP concentrations with relevant water quality parameters and remote sensing reflectance bands in aquatic environments using in-situ data from a local database to support the calibration and validation of the GP model. The GP models show the effective capacity to demonstrate snapshots of spatiotemporal distributions of TP across the Bay, which helps to delineate the short-term seasonality effects and the decadal trends of TP in an environmentally sensitive coastal bay area. In the past decade, urban development and agricultural activities in the Bay area have substantially increased the use of fertilizers. Landfall hurricanes, including Frances and Jeanne in 2004 and Wilma in 2005, followed by continuous droughts from 2006 to 2008 in South Florida, made the Bay area an ideal place for a remote sensing impact assessment. A changing hydrological cycle, triggered by climate variations, exhibited unique regional patterns of varying TP waste loads into the Bay over different time scales ranging from seasons to years. With the aid of the derived GP model in this study, we were able to explore these multiple spatiotemporal distributions of TP concentrations in the Tampa Bay area aquatic environment and to elucidate these coupled dynamic impacts induced by both natural hazards and anthropogenic perturbations. This advancement enables us to identify the hot moments and hot spots of TP concentrations in the Tampa Bay region. (c) 2013 Elsevier Inc. All rights reserved.

    Journal Title

    Remote Sensing of Environment

    Volume

    134

    Publication Date

    1-1-2013

    Document Type

    Article

    Language

    English

    First Page

    100

    Last Page

    110

    WOS Identifier

    WOS:000319233200008

    ISSN

    0034-4257

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