Empirical Estimation of Total Nitrogen and Total Phosphorus Concentration of Urban Water Bodies in China Using High Resolution IKONOS Multispectral Imagery

Jiaming Liu,Di Yuan,Yanjun Zhang,Xingyuan Song

doi:10.3390/w7116551

Jiaming Liu, Di Yuan + Show 2 more

Open Access

https://doi.org/10.3390/w7116551

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Journal: Water	Publication Date: Nov 17, 2015
Citations: 39	License type: CC BY 4.0

Affiliation: Hubei Water Resources Research Institute, Wuhan University

Abstract

Measuring total nitrogen (TN) and total phosphorus (TP) is important in managing heavy polluted urban waters in China. This study uses high spatial resolution IKONOS imagery with four multispectral bands, which roughly correspond to Landsat/TM bands 1–4, to determine TN and TP in small urban rivers and lakes in China. By using Lake Cihu and the lower reaches of Wen-Rui Tang (WRT) River as examples, this paper develops both multiple linear regressions (MLR) and artificial neural network (ANN) models to estimate TN and TP concentrations from high spatial resolution remote sensing imagery and in situ water samples collected concurrently with overpassing satellite. The measured and estimated values of both MLR and ANN models are in good agreement (R2 > 0.85 and RMSE < 2.50). The empirical equations selected by MLR are more straightforward, whereas the estimated accuracy using ANN model is better (R2 > 0.86 and RMSE < 0.89). Results validate the potential of using high resolution IKONOS multispectral imagery to study the chemical states of small-sized urban water bodies. The spatial distribution maps of TN and TP concentrations generated by the ANN model can inform the decision makers of variations in water quality in Lake Cihu and lower reaches of WRT River. The approaches and equations developed in this study could be applied to other urban water bodies for water quality monitoring.

Highlights

Urbanization has become a ubiquitous global change over the 20th century [1]
Though the results demonstrate that the artificial neural network (ANN) model has a stronger ability to simulate the complex nonlinear relationship, it may be more prone to the effects of the local optimal solution developed on the basis of the empirical risk minimization theory [56]
The determination of total nitrogen (TN) and total phosphorus (TP) concentrations of small-sized urban water bodies from high-resolution IKONOS multispectral imagery are developed in two case studies

Summary

Introduction

Urbanization has become a ubiquitous global change over the 20th century [1]. As a “living laboratory”in urbanization [2], China has experienced rapid economic development and urbanization in the past three decades. In addition to cost and labor intensiveness, these traditional approaches are not suitable for monitoring a large number of water bodies at a regional or national scale because of spatial heterogeneity and temporal changes of water quality across aquatic ecosystems. This condition is especially true for urban lake and river systems, where numerous point and non-point inputs occur over relatively short distances [4]. With the constant development of environmental information technology, remote sensing plays an important and effective role in water quality monitoring because of its wider coverage, higher efficiency, and lower cost than traditional sampling methods. Nitrogen (N), which is needed for protein synthesis, and phosphorus (P), which is needed for DNA, RNA, and energy transfer, are both required to support aquatic plant growth and are the key limiting nutrients in most aquatic and terrestrial ecosystems [3,10,11]

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