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DOI10.1016/j.rse.2013.03.002
Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models
Chang, Ni-Bin1; Xuan, Zhemin1; Yang, Y. Jeffrey2
发表日期2013-07-01
ISSN0034-4257
卷号134页码:100-110
英文摘要

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.


英文关键词Remote sensing;Coastal bay;Nutrient monitoring;MODIS;Genetic programming
语种英语
WOS记录号WOS:000319233200008
来源期刊REMOTE SENSING OF ENVIRONMENT
来源机构美国环保署
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/58050
作者单位1.Univ Cent Florida, Dept Civil Environm & Construct Engn, Orlando, FL 32816 USA;
2.US EPA, Off Res & Dev, Natl Risk Management Res Lab, Cincinnati, OH 45268 USA
推荐引用方式
GB/T 7714
Chang, Ni-Bin,Xuan, Zhemin,Yang, Y. Jeffrey. Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models[J]. 美国环保署,2013,134:100-110.
APA Chang, Ni-Bin,Xuan, Zhemin,&Yang, Y. Jeffrey.(2013).Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models.REMOTE SENSING OF ENVIRONMENT,134,100-110.
MLA Chang, Ni-Bin,et al."Exploring spatiotemporal patterns of phosphorus concentrations in a coastal bay with MODIS images and machine learning models".REMOTE SENSING OF ENVIRONMENT 134(2013):100-110.
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