Water quality and optical properties of coastal waters from hyperspectral data

2002 ◽  
Author(s):  
F. Lahet ◽  
S. Ouillon ◽  
P. Forget
Keyword(s):  
Water Quality ◽  
Optical Properties ◽  
Coastal Waters ◽  
Hyperspectral Data

Management and Status of Japanese Public Waters

1991 ◽  
Vol 23 (1-3) ◽  
pp. 1-10 ◽  
Author(s):  
Takeshi Goda
Keyword(s):  
Water Quality ◽  
Coastal Waters ◽  
Industrial Wastewater ◽  
Quality Standards ◽  
Water Bodies ◽  
Industrial Wastewaters ◽  
Quality Of Water ◽  
Japanese Rivers ◽  
Per Capita

The management and status of public water bodies in Japan is discussed. The environmental quality standards which have been set and the levels of compliance with these standards are shown. The water quality of Japanese rivers, lakes, reservoirs, wetlands and coastal waters is described, and eutrophication problems are mentioned. The effects of changes in population density and levels of recycling of industrial wastewaters on the quality of water bodies are discussed. Almost 75% of industrial wastewater is now recycled. Per capita availability of freshwater in Japan is comparatively low, and the construction of 530 dams, in addition to the 2393 dams already in operation, is planned. Irrigation effluents from paddy fields are a major factor which influences river water quality in Japan. The improvement of water quality using various methods is discussed.

scholarly journals Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity

2018 ◽  
Vol 15 (9) ◽  
pp. 1881 ◽  
Author(s):  
Sina Keller ◽  
Philipp Maier ◽  
Felix Riese ◽  
Stefan Norra ◽  
Andreas Holbach ◽  
...  
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
Chlorophyll A ◽  
Green Algae ◽  
Hyperspectral Data ◽  
Coefficient Of Determination ◽  
Inland Waters ◽  
Learning Approaches ◽  
River Elbe ◽  
Regression Framework

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June–12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

scholarly journals Ekologi Perairan Semarang – Demak : Inventarisasi Jenis Kerang yang Ditemukan di Dasar Perairan

2017 ◽  
Vol 20 (2) ◽  
pp. 84
Author(s):  
Chrisna Adhi Suryono ◽  
Ita Riniatsih ◽  
Ria Azizah ◽  
Ali Djunaedi ◽  
Baskoro Rochaddi ◽  
...  
Keyword(s):  
Water Quality ◽  
Coastal Waters ◽  
Bottom Trawl ◽  
Anadara Granosa

The present study was conducted to inventory the cockles (bivalve) in coastal waters between Semarang to Demak.  The samples were collected by bottom trawl modification (dragger) around those areas.  The results were found ten various cockles there were Anadara granosa, A. pilula, A. gubernaculum, A. inaequivalvis, Pharella javanica, Paphia undulate, Marcia hiantina, Harvella plicataria, Mactra violacea, and Placuna placenta.  Meanwhile the waters quality in the in this areas still support to organisms to survive based on the standard water quality from Indonesian Ministry of Environmental.  Abstrak Tujuan penelitian ini adalah untuk menginventarisasi jenis jenis kerang yang ada di perairan antara Semarang dan Demak.  Sampel diambil dengan trawl dasar modivikasi (dragger) sekitar perairan tersebut.  Hasil penelitian menunjukakan beberapa jenis kerang didapat seperti: Anadara granosa, A. pilula, A. gubernaculum, A. inaequivalvis, Pharella javanica, Paphia undulate, Marcia hiantina, Harvella plicataria, Mactra violacea, and Placuna placenta. Berdasar Kepmen Lingkungan Hidup kualitas perairan yang ada di daerah tersebut dapat dikatakan masih mendukung untuk kehidupan organisme.

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