Comparison of single channel indices for U-Net based segmentation of vegetation in satellite images

2020 ◽  
Author(s):  
Irem Ulku ◽  
Panagiotis Barmpoutis ◽  
Tania Stathaki ◽  
Erdem Akagunduz
Keyword(s):  
Satellite Images ◽  
Single Channel

scholarly journals HORIZONTAL DEFORMATIONS OF THE SUKIL RIVERBED WITHIN THE PRE-CARPATHIAN HEIGHT IN 1880-2019

2021 ◽  
pp. 197-211
Keyword(s):  
Satellite Images ◽  
Single Channel ◽  
Field Research ◽  
Earth Satellite ◽  
Natural Increase ◽  
Google Earth ◽  
Historical Maps ◽  
Third Stage ◽  
The Village

The article presents the results of the study of horizontal riverbed deformations of the Sukil river in the area from the town of Bolekhiv to its confluence with the Svicha river during 1880–2019. The studied section of the riverbed is located within the Precarpathian height and is marked by significant dynamics of the riverbed, which is mainly due to frequent floods, including catastrophic ones. The analysis of long-term horizontal riverbed deformations of the Sukil river and identification of the main factors of their manifestation were carried out in three stages. The first stage involved an assessment of the riverbed displacement over a long-term period of tens of years and was performed based on topographic maps of 1880, 1929-1939, and 1990. The second stage focused on the analysis of the riverbed displacement during a short-term period of 5-7 years and was conducted on the basis of Google Earth satellite images of 2006, 2011, and 2017–2019. The third stage was dedicated to the verification of the obtained results by field research and to the identification of the main reasons for the development of horizontal riverbed deformations. The analysis of historical maps and satellite images was mainly conducted by cartographic methods using ArcGIS 10.1. The riverbed of the Sukil river has significant differences in the development of horizontal deformations on the section of Bolekhiv – the village of Podorozhnie (the mouth of the river). According to the type of manifestation and scale of the riverbed deformations development, two sections (hereinafter dynamic sections) with significant horizontal deformations have been identified: the first one – from Bolekhiv to the village of Lysovychi; the second one – from the village of Lysovychi to the village of Podorozhnie (the Sukil mouth). On dynamic section 1, the horizontal deformations are differently manifested depending on the type of the riverbed. The maximum displacements which were found on the meandering sections are approximately 340 m. They were recorded during the period of 1880–1939. On the sections with a “transitional” type of riverbeds (in the late 19th-early 20th century they were braided, and now they are single channel), the deformations are small (up to 60 m) and are manifested mainly within the boundaries of the riverbed. On dynamic section 2, the Sukil riverbed is meandering and the deformations are much larger. The maximum riverbed displacements reach approximately 500 m (during the period of 1880–1939). For dynamic section 2 as well as for the whole section of the Sukil riverbed from Bolekhiv to the mouth, a certain tendency of the riverbed changes on the plan has been revealed. Thus, from 1889 to 1990 we observe a decrease in the meandering of the riverbed caused by anthropogenic influence, in particular, by the straightening of the riverbed in the 70-80s of the last century and by change in the position of the mouth; since 1990, a natural increase in the Sukil riverbed’s meandering has been observed. Key words: horizontal deformations; riverbed types; Sukil; meandering; historical maps; remote sensing.

Data Acquisition and Handling Unit for a Quantitative Use of Electron Energy Loss Spectroscopy

1977 ◽  
Vol 35 ◽  
pp. 232-233 ◽  
Author(s):  
P. Trebbia ◽  
P. Ballongue ◽  
C. Colliex
Keyword(s):  
Electron Microscope ◽  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Single Channel ◽  
Detection System ◽  
Surface Barrier ◽  
Solid State Detector ◽  
Electrostatic Mirror ◽  
Electron Energy Loss

An effective use of electron energy loss spectroscopy for chemical characterization of selected areas in the electron microscope can only be achieved with the development of quantitative measurements capabilities.The experimental assembly, which is sketched in Fig.l, has therefore been carried out. It comprises four main elements.The analytical transmission electron microscope is a conventional microscope fitted with a Castaing and Henry dispersive unit (magnetic prism and electrostatic mirror). Recent modifications include the improvement of the vacuum in the specimen chamber (below 10-6 torr) and the adaptation of a new electrostatic mirror.The detection system, similar to the one described by Hermann et al (1), is located in a separate chamber below the fluorescent screen which visualizes the energy loss spectrum. Variable apertures select the electrons, which have lost an energy AE within an energy window smaller than 1 eV, in front of a surface barrier solid state detector RTC BPY 52 100 S.Q. The saw tooth signal delivered by a charge sensitive preamplifier (decay time of 5.10-5 S) is amplified, shaped into a gaussian profile through an active filter and counted by a single channel analyser.

Instrumentation for Measurement of Lingual Strength

1968 ◽  
Vol 11 (1) ◽  
pp. 189-193 ◽  
Author(s):  
Lois Joan Sanders
Keyword(s):  
Single Channel ◽  
Displacement Transducer ◽  
Tongue Pressure ◽  
Maximum Pressure ◽  
Research Use ◽  
Direct Writing ◽  
Significant Difference ◽  
Pressure Unit ◽  
Force Displacement ◽  
Consistent Response

A tongue pressure unit for measurement of lingual strength and patterns of tongue pressure is described. It consists of a force displacement transducer, a single channel, direct writing recording system, and a specially designed tongue pressure disk, head stabilizer, and pressure unit holder. Calibration with known weights indicated an essentially linear and consistent response. An evaluation of subject reliability in which 17 young adults were tested on two occasions revealed no significant difference in maximum pressure exerted during the two test trials. Suggestions for clinical and research use of the instrumentation are noted.

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Multitemporal distribution analysis of Dodonaea viscosa (L.) Jacq. by remote sensing in Durango, Mexico

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Marco, A. Márquez-Linares ◽  
Jonathan G. Escobar--Flores ◽  
Sarahi Sandoval- Espinosa ◽  
Gustavo Pérez-Verdín
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Design Methodology ◽  
Supervised Classification ◽  
Satellite Images ◽  
Ground Cover ◽  
Distribution Analysis ◽  
Dodonaea Viscosa ◽  
Artificial Neural ◽  
Landsat Satellite

Objective: to determine the distribution of D. viscosa in the vicinity of the Guadalupe Victoria Dam in Durango, Mexico, for the years 1990, 2010 and 2017.Design/Methodology/Approach: Landsat satellite images were processed in order to carry out supervised classifications using an artificial neural network. Images from the years 1990, 2010 and 2017 were used to estimate ground cover of D. viscosa, pastures, crops, shrubs, and oak forest. This data was used to calculate the expansion of D. viscosa in the study area.Results/Study Limitations/Implications: the supervised classification with the artificial neural network was optimal after 400 iterations, obtaining the best overall precision of 84.5 % for 2017. This contrasted with the year 1990, when overall accuracy was low at 45 % due to less training sites (fewer than 100) recorded for each of the land cover classes.Findings/Conclusions: in 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, and based on the distribution of D. viscosa, it is likely that in a few years it will have the ability to invade half the study area, occupying agricultural, forested, and shrub areas

Designing a coherent land registration system for rural Portugal

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Tiago NUNES ◽  
Miguel COUTINHO
Keyword(s):  
Satellite Images ◽  
Field Research ◽  
Digital Native ◽  
Web Based ◽  
Registration System ◽  
Land Registration ◽  
Daily Rate ◽  
Property Owners ◽  
Property Identification

After almost a century of several attempts to establish a coherent land registration system across the whole country, in 2017 the Portuguese government decided to try a new, digital native approach to the problem. Thus, a web-based platform was created, where property owners from 10 pilot municipalities could manually identify their lands’ properties using a map based on satellite images. After the first month of submissions, it became clear that at the current daily rate, it would take years to achieve the goal of 100% rural property identification across just the 10 municipalities. Field research during the first month after launch enabled us to understand landowners’ relationships with their land, map their struggles with the platform, and prototype ways to improve the whole service. Understanding that these improvements would still not be enough to get to the necessary daily rate, we designed, tested and validated an algorithm that allows us to identify a rural property shape and location without coordinates. Today, we are able to help both Government and landowners identify a rural property location with the click of a button.

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