Remote Monitoring of NH3-N Content in Small-Sized Inland Waterbody Based on Low and Medium Resolution Multi-Source Remote Sensing Image Fusion

Author:

Li Jian,Ke Meiru,Ma Yurong,Cui Jian

Abstract

In applying quantitative remote sensing in water quality monitoring for small inland rivers, the time-frequency of monitoring dramatically impacts the accuracy of time-spatial changes estimates of the water quality parameters. Due to the limitation of satellite sensor design and the influence of atmospheric conditions, the number of spatiotemporal dynamic monitoring images of water quality parameters is insufficient. Meanwhile, MODIS and other high temporal resolution images’ spatial resolution is too low to effectively extract small inland river boundaries. To solve the problem, many researchers used Spatio-temporal fusion models in multisource data remote sensing monitoring of ground features. The wildly used Spatio-temporal fusion models, such as FSDAF (flexible spatial-temporal data fusion), have poor performance in heterogeneous changes of ground objects. We proposed a spatiotemporal fusion algorithm SR-FSDAF (Super-resolution based flexible spatiotemporal data fusion) to solve the problem. Based on the FSDAF, it added ESPCN to reconstruct the spatial change prediction image, so as to obtain better prediction results for heterogeneous changes. Both qualitative and quantitative evaluation results showed that our fusion algorithm obtained better results. We compared the band sensitivity of the images before and after fusion to find out that the sensitive band combination of NH3-N has not changed, which proved that the fusion method can be used to improve the time-frequency of NH3-N inversion. After the fusion, we compared the accuracy of linear regression and random forest inversion models and selected the random forest model with better accuracy to predict the NH3-N concentration. The inversion accuracy of NH3-N was as follows: the R2 was 0.75, the MAPE was 23.7% and the RMSE was 0.15. The overall concentration change trend of NH3-N in the study area was high-water period < water-stable period < low water period. NH3-N pollution was serious in some reaches.

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

Reference42 articles.

1. Evaluating the effect of diffuse and point source nutrient transfers on water quality in the Kombolcha River Basin, an industrializing Ethiopian catchment

2. Preliminary Exploring of Hyperspectral Remote Sensing Experiment for Nitrogen and Phosphorus in Water;Gong;Spectrosc. Spectr. Anal.,2008

3. Applying support vector regression to water quality modelling by remote sensing data

4. Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

5. Deteriorating Water Clarity in Shallow Waters: Evidence from Long Term Modis and in-Situ Observations;Kun;Int. J. Appl. Earth Obs. Geoinf.,2017

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