scholarly journals Analysis of water quality at hydrographic basin scale using satellite images, co-occurrence matrices and Bayes classifier

2021 ◽  
Author(s):  
M. G. G. Silva ◽  
D. J. Silva ◽  
P. D. Costa ◽  
R. C. Silva ◽  
T. E. B. Cassimiro ◽  
...  
Keyword(s):  
Water Quality ◽  
Satellite Images ◽  
Digital Processing ◽  
Training Stage ◽  
Basin Scale ◽  
Testing Stage ◽  
Otsu’S Method ◽  
Laplacian Filter ◽  
Processing Techniques ◽  
Computational Platform

Abstract Given the increased risks of water scarcity and the presence of polluting agents in water resources, this paper aims at the development and presentation of a computational tool capable of assessing water quality based on digital processing techniques applied to satellite images. Initially, a database was created for Brazilian regions, consisting of hydrographic basins satellite images associated with the Water Quality Index (WQI), according to the criteria established by the National Water Agency (ANA). Hitherto, the database consists of 85 images, 61 are used in the training stage and 24 in the testing stage. In both stages, the images are subjected to thresholding using the Otsu's Method, binarization, linear expansion on saturation, application of a Laplacian filter, extraction of characteristics by using co-occurrence matrices and classification by the Bayes Discriminant. Such techniques were also implemented on a computational platform in MATLAB® environment, responsible for the interface between the system and users. The proposed system presented an approximate 70% success rate regarding the classification of WQIs, which can be improved as more information is made available to improve the databases.

Implications of Digital Image Processing in the Paraclinical Assessment of the Partially Edentated Patient

2018 ◽  
Vol 69 (2) ◽  
pp. 521-524
Author(s):  
Magda Ecaterina Antohe ◽  
Doriana Agop Forna ◽  
Cristina Gena Dascalu ◽  
Norina Consuela Forna
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Treatment Plan ◽  
Digital Processing ◽  
Contour Detection ◽  
Anatomical Structures ◽  
Imaging Processing ◽  
Point To Point ◽  
Radiological Image ◽  
Processing Techniques

The application of certain digital processing techniques offers the possibility of extra accuracy in the interpretation of paraclinical examinations of this type, with profound implications in the diagnosis as well as in the hierarchy of the treatment plan. The purpose of this study is to identify the type of imaging processing for the identification of pathological elements from orthopantomographies and articular tomographies. A number of 20 orthopantomographies and 15 temporo-mandibular joint tomography have undergone through various image enhancement techniques. Various methods of image enhancement (enhancement) have been used for those procedures whereby it becomes more useful in the following aspects: specific details are highlighted; noise is eliminated; the image becomes more visually attractive. The workings were done in Corel PhotoPaint 7.0, using the automatic procedures available.The choice of a particular type of image enhancement technique has been selected for each type of pathology found in orthopantomographies or articular tomography, providing the best accuracy for an optimal imaging interpretation that underpins a precision diagnosis.Of the most useful imaging processing in the optimization of the orthopantomographic image accuracy the point-to-point transformations are to be noted. The image processing proposed in this article focused primarily on improving the radiological image attributes to highlight specific anatomical structures, and secondly, the contour detection, where it was necessary for the diagnostic purposes as well.

Innovative Tools for Water Quality Management and Policy Analysis: Desert and Streamplan

1999 ◽  
Vol 40 (10) ◽  
pp. 103-110
Author(s):  
Carlo De Marchi ◽  
Pavel Ivanov ◽  
Ari Jolma ◽  
Ilia Masliev ◽  
Mark Griffin Smith ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Policy Analysis ◽  
River Basin ◽  
Emission Reduction ◽  
Water Quality Management ◽  
Water Quality Modeling ◽  
Detailed Model ◽  
Basin Scale ◽  
Alternative Water

This paper presents the major features of two decision support systems (DSS) for river water quality modeling and policy analysis recently developed at the International Institute of Applied Systems Analysis (IIASA), DESERT and STREAMPLAN. DESERT integrates in a single package data management, model calibration, simulation, optimization and presentation of results. DESERT has the flexibility to allow the specification of both alternative water quality models and flow hydraulics for different branches of the same river basin. Specification of these models can be done interactively through Microsoft® Windows commands and menus and an easy to use interpreted language. Detailed analysis of the effects of parameter uncertainty on water quality results is integrated into DESERT. STREAMPLAN, on the other hand, is an integrated, easy-to-use software system for analyzing alternative water quality management policies on a river basin level. These policies include uniform emission reduction and effluent standard based strategies, ambient water quality and least-cost strategies, total emission reduction under minimized costs, mixed strategies, local and regional policies, and strategies with economic instruments. A distinctive feature of STREAMPLAN is the integration of a detailed model of municipal wastewater generation with a water quality model and policy analysis tools on a river basin scale.

scholarly journals ROAD NETWORK IDENTIFICATION AND EXTRACTION IN SATELLITE IMAGERY USING OTSU'S METHOD AND CONNECTED COMPONENT ANALYSIS

2018 ◽  
Vol XLII-5 ◽  
pp. 91-98 ◽  
Author(s):  
P. Yadav ◽  
S. Agrawal
Keyword(s):  
High Resolution ◽  
Road Network ◽  
Satellite Images ◽  
Component Analysis ◽  
Morphological Operations ◽  
Connected Component ◽  
Road Detection ◽  
Connected Component Analysis ◽  
High Resolution Satellite Images ◽  
Otsu’S Method

<p><strong>Abstract.</strong> As the high resolution satellite images have become easily available, this has motivated researchers for searching advanced methods for object detection and extraction from satellite images. Roads are important curvilinear object as they are a used in urban planning, emergency response, route planning etc. Automatic road detection from satellite images has now become an important topic in photogrammetry with the advances in remote sensing technology. In this paper, a method for road detection and extraction of satellite images has been introduced. This method uses the concept of histogram equalization, Otsu's method of image segmentation, connected component analysis and morphological operations. The aim of this paper is to discover the potential of high resolution satellite images for detecting and extracting the road network in a robust manner.</p>

Interactive processing of satellite images for structural and lithological mapping in northeast Africa

1986 ◽  
Vol 123 (4) ◽  
pp. 393-403 ◽  
Author(s):  
S. M. Berhe ◽  
D. A. Rothery
Keyword(s):  
Principal Components ◽  
Satellite Images ◽  
Spatial Filtering ◽  
Digital Processing ◽  
Horn Of Africa ◽  
Lithological Mapping ◽  
Late Precambrian ◽  
Late Proterozoic ◽  
Pan African ◽  
Multispectral Satellite Images

AbstractInteractive digital processing of multispectral satellite images (Landsat MSS) using principal components transformations and spatial filtering has clarified the position of continuous sutures linking apparently isolated Pan African (late Proterozoic) ophiolites. These have been field-checked and an arrangement of Pan African suture zones is proposed. Spatial filtering has also highlighted faults with various trends which can be related to the late Precambrian tectonics of the Horn of Africa region.

Comparison of Omegawave Device and an Ambulatory ECG for RR Interval Measurement at rest

2020 ◽  
Author(s):  
José Naranjo-Orellana ◽  
José Francisco Ruso-Álvarez ◽  
José Luis Rojo-Álvarez
Keyword(s):  
Cross Correlation ◽  
Digital Processing ◽  
Altman Analysis ◽  
Rr Intervals ◽  
Rr Interval ◽  
Electrocardiogram Signals ◽  
Baseline Noise ◽  
Processing Techniques ◽  
High Pass ◽  
Strong Agreement

AbstractThe aim of this study was to validate the measurements of the beat intervals taken at rest by the Omegawave® device by comparing them to an ambulatory electrocardiogram system. For this purpose, the electrocardiogram was digitally processed, time-aligned, and scrutinized for its suitable use as gold-standard. Rest measurements were made for 10 minutes on 5 different days to 10 men and 3 women (24.8±5.05 years; 71.82±11.02 kg; 174.35±9.13 cm). RR intervals were simultaneously recorded using the Omegawave device and a Holter electrocardiogram. The processing of Holter electrocardiogram signals included the detrending of baseline noise and a high-pass filtering for emphasizing the QRS complexes and attenuating the T waves. After obtaining the RR intervals from the electrocardiogram, those from the Omegawave device were automatically aligned to them with cross-correlation digital processing techniques and compared to check whether both measurements could be considered superimposable. A Bland-Altman analysis was applied to the 5 measurements made for all subjects. The Omegawave device exhibited very strong agreement with a quality-controlled Holter electrocardiogram. Deviations not exceeding 25 ms could be expected in 95% of the cases, which is within manageable ranges both for clinical practice and for sports.

scholarly journals A Spatial Analysis to Define Data Requirements for Hydrological and Water Quality Models in Data-Limited Regions

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 267 ◽  
Author(s):  
Ersilia D’Ambrosio ◽  
Anna De Girolamo ◽  
Marinella Spanò ◽  
Vera Corbelli ◽  
Gennaro Capasso ◽  
...  
Keyword(s):  
Water Quality ◽  
Spatial Analysis ◽  
Surface Water ◽  
Source Parameters ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Limited Area ◽  
Climatic Data ◽  
Basin Scale

The objective of the present work is a spatial analysis aimed at supporting hydrological and water quality model applications in the Canale d’Aiedda basin (Puglia, Italy), a data-limited area. The basin is part of the sensitive environmental area of Taranto that requires remediation of the soil, subsoil, surface water, and groundwater. A monitoring plan was defined to record the streamflow and water quality parameters needed for calibrating and validating models, and a database archived in a GIS environment was built, which includes climatic data, soil hydraulic parameters, groundwater data, surface water quality parameters, point-source parameters, and information on agricultural practices. Based on a one-year monitoring of activities, the average annual loads of N-NO3 and P-PO4 delivered to the Mar Piccolo amounted to about 42 t year−1, and 2 t year−1, respectively. Knowledge uncertainty in monthly load estimation was found to be up to 25% for N-NO3 and 40% for P-PO4. The contributions of point sources in terms of N-NO3 and P-PO4 were estimated at 45% and 77%, respectively. This study defines a procedure for supporting modelling activities at the basin scale for data-limited regions.

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