scholarly journals IDENTIFICATION AND CLASSIFICATION OF LAKE BOTTOM SURFACE AND AQUATIC VEGETATION IN LAUT TAWAR LAKE, ACEH

2015 ◽  
Vol 21 (1) ◽  
pp. 1
Author(s):  
Zulkarnaen Fahmi ◽  
Husnah Husnah
Keyword(s):  
Aquatic Vegetation ◽  
Acoustic Method ◽  
Visual Observation ◽  
Bottom Surface ◽  
Line Transect ◽  
Survey Analysis ◽  
Soft Bottom ◽  
Bottom Type ◽  
Spatial Coverage

Identification and classification of benthic habitats in Lake of Laut Tawar, Aceh by using hydro acoustic method can provide data and information on types of substrate and aquatic vegetation in a short time and wide spatial coverage, as done in the present work. Data acoustic collection was performed in 2013 using quantitative echosounder with split beam frequency of 120 kHz, and through a visual observation. The later is destined to look at the bottom types and macrophytes that lie on the line transect of acoustic survey. Analysis of data is to extract the value of bottom volume backscattering for each transect of 0.5-1 km. Classification of the bottom type was done based on the value of Sv using geospatial models. Results show the interval value of Sv for soft bottom ranged between -24.00 dB and -32.00 dB, the type of hard bottom (e.g. rocks, rocky sand substrate) ranged between -14.00 dB and -22.00 dB, whereas the Sv value of macrophyte ranged between- 45.00 dB and -54.00 dB. The percent covers were about 42.90%, 44.71% and 12.93% for hard bottom type, soft bottom and macrophytes, respectively. The types of aquatic vegetation commonly found in the lake were two genera belonging Hydrocharitaceaea and Gramineae. The current work is still lack of information on the classification of organisms into genera scales. Therefore, more signal verification and algorithms verification would be needed in order to estimate macrophytes biomass by comparing with other visual observation.

Classification of landslide activity based on spaceborne interferometric SAR at the Moselle Valley, Germany

2021 ◽  
Author(s):  
Andre C. Kalia
Keyword(s):  
Time Series ◽  
Clustering Algorithm ◽  
Statistical Tests ◽  
Spatial Density ◽  
Deformation Pattern ◽  
Visual Interpretation ◽  
Landslide Activity ◽  
Spatial Coverage ◽  
Interferometric Sar

<p>Landslide activity is an important information for landslide hazard assessment. However, an information gap regarding up to date landslide activity is often present. Advanced differential interferometric SAR processing techniques (A-DInSAR), e.g. Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) are able to measure surface displacements with high precision, large spatial coverage and high spatial sampling density. Although the huge amount of measurement points is clearly an improvement, the practical usage is mainly based on visual interpretation. This is time-consuming, subjective and error prone due to e.g. outliers. The motivation of this work is to increase the automatization with respect to the information extraction regarding landslide activity.</p><p>This study focuses on the spatial density of multiple PSI/SBAS results and a post-processing workflow to semi-automatically detect active landslides. The proposed detection of active landslides is based on the detection of Active Deformation Areas (ADA) and a subsequent classification of the time series. The detection of ADA consists of a filtering of the A-DInSAR data, a velocity threshold and a spatial clustering algorithm (Barra et al., 2017). The classification of the A-DInSAR time series uses a conditional sequence of statistical tests to classify the time series into a-priori defined deformation patterns (Berti et al., 2013). Field investigations and thematic data verify the plausibility of the results. Subsequently the classification results are combined to provide a layer consisting of ADA including information regarding the deformation pattern through time.</p>

Fatalities caused by floods: a comparison between global databases and country scale historical research

2021 ◽  
Author(s):  
Michele Mercuri ◽  
Olga Petrucci
Keyword(s):  
Natural Disasters ◽  
Developed Countries ◽  
Global Scale ◽  
European Countries ◽  
Insurance Companies ◽  
Economic Damage ◽  
Global Databases ◽  
Humanitarian Organizations ◽  
Spatial Coverage

<p>Datasets supporting the study of natural disasters and allowing spatial/temporal analyses of phenomena and their interactions with human societies is rapidly growing, due to the efforts of insurance companies, universities and humanitarian organizations. At the global scale, several disasters catalogues are available, even if some are only partially accessible. Generally, the focus is on the complete impact of disasters, in terms of areas affected and economic damage. Each record is a natural disaster, while database fields contain parameters assessing disaster magnitude. One of this parameter is the number of fatalities.</p><p>In Australia and USA, databases of fatalities caused by specific kinds of natural disasters are available, while, for Europe, natural disasters mortality is often investigated using global databases.</p><p>The present research focus on floods and their effects on people mortality. We named “flood fatalities” (FFs) people killed by direct impact of flood events due to the following short-term clinical causes: 1) Drowning; 2) Collapse/Heart attack; 3) Poly-trauma; 4) Poly-trauma and Suffocation; 5) Hypothermia; 6) Suffocation; 7) Electrocution.</p><p>For a 40-years study period and for 9 European study areas, we performed a survey of FFs reported in four of the widely known global databases. Then we compared figures with the results of a very specific research carried out for the same study areas and study period at a country scale, and focusing on a very restricted field: fatalities caused by floods.</p><p>The comparison highlights as the use of global databases can supply figures of FFs not correctly estimated, either underestimated or overestimated.</p><p>Underestimation depends on the fact that collecting data at the global scale needs some severity threshold of floods to be included in the database. Thus, local events causing a few FFs, as i.e. flash flooding, are systematically excluded, even if the majority of floods that occur in developed countries kill less than 10 people. This results in an underestimation of FFs, which is going to increase due to the increasing frequency of localized floods or flash floods related to climate change. Overestimation, instead, can happen due to the classification of fatalities occurred at the same time of the flood, even if they are caused by other phenomena (i.e., landslides, debris flows and wind).</p><p>This work aims to demonstrate how a database of flood fatalities realized at a country scale can supply realistic figures of fatalities in European countries, providing information that can reduce flood fatalities in the future. Our database is available for the period 1980-2018 (Petrucci et al., 2019). We encourage researchers working in European countries to collaborate with us to increase spatial coverage of the database and promote its common use in studies on flood mortality.</p><p>Petrucci O., Aceto, L., Bianchi, C., Bigot, V., Brázdil, R., Pereira, S., Kahraman, A., Kılıç, O., Kotroni, V., Llasat, M.C., Llasat-Botija, M., Papagiannaki, K., Pasqua. A.A., Řehoř J., Rossello Geli, J. Salvati, P., Vinet, F., Zêzere, J.L. (2019). Flood Fatalities in Europe, 1980–2018: Variability, Features, and Lessons to Learn. Water, 11(8), 1682.</p>

Classification of Danube Delta lakes based on aquatic vegetation and turbidity

1999 ◽  
pp. 187-191
Author(s):  
Hugo Coops ◽  
Jenica Hanganu ◽  
Marian Tudor ◽  
Willem Oosterberg
Keyword(s):  
Aquatic Vegetation ◽  
Danube Delta

Aquatic Vegetation as a Basis for Classification of Anopheles albimanus Weideman (Diptera: Culicidae) Larval Habitats

1992 ◽  
Vol 21 (3) ◽  
pp. 598-603 ◽  
Author(s):  
E. Rejmankova ◽  
H. M. Savage ◽  
M. H. Rodriguez ◽  
D. R. Roberts ◽  
M. Rejmanek
Keyword(s):  
Aquatic Vegetation ◽  
Anopheles Albimanus ◽  
Larval Habitats

scholarly journals Signal Classification of Submerged Aquatic Vegetation Based on the Hemispherical–Conical Reflectance Factor Spectrum Shape in the Yellow and Red Regions

2013 ◽  
Vol 5 (4) ◽  
pp. 1856-1874 ◽  
Author(s):  
Fernanda Watanabe ◽  
Nilton Imai ◽  
Enner Alcântara ◽  
Luiz da Silva Rotta ◽  
Alex Utsumi
Keyword(s):  
Submerged Aquatic Vegetation ◽  
Aquatic Vegetation ◽  
Signal Classification ◽  
Spectrum Shape ◽  
Reflectance Factor

scholarly journals Virometer: an optical instrument for visual observation, measurement and classification of free viruses.

1977 ◽  
Vol 25 (7) ◽  
pp. 719-723 ◽  
Author(s):  
T Hirschfeld ◽  
M J Block ◽  
W Mueller
Keyword(s):  
Nucleic Acid ◽  
Visual Observation ◽  
Total Reflection ◽  
Data Handling ◽  
Fluorescent Staining ◽  
Optical Instrument ◽  
Fluorescence Correlation ◽  
Acid Type

An instrument based on fluorescence correlation spectrometry and total reflection fluorescence visually and photoelectrically detects and sizes viruses at moderate concentrations in biologic fluids in minutes. Viruses can be classified using their nucleic acid type and amount determined by new fluorescent staining and data handling techniques.

Formalized classification of species-poor vegetation: a proposal of a consistent protocol for aquatic vegetation

2015 ◽  
Vol 26 (4) ◽  
pp. 791-803 ◽  
Author(s):  
Flavia Landucci ◽  
Lubomír Tichý ◽  
Kateřina Šumberová ◽  
Milan Chytrý
Keyword(s):  
Aquatic Vegetation

scholarly journals Composition and Classification of Tree Species in a Degraded Tropical Humid Rainforest in Southwest Nigeria

2020 ◽  
pp. 41-48
Author(s):  
S. T. Ebeniro ◽  
M. D. Wali
Keyword(s):  
Tree Species ◽  
Tropical Rainforest ◽  
Line Transect ◽  
Height Distribution ◽  
New Techniques ◽  
Tree Species Composition ◽  
The Third ◽  
Forest Meteorology ◽  
Southwest Nigeria

Tree species information is essential for forest studies such as forest meteorology, botany and ecology, and across the relevant fields new techniques efficient for classifying tree species are desperately in demand. This study assessed tree species composition and classification in a degraded tropical rainforest in Southwest Nigeria. Data was collected from the Olukayode compartment of the study area of size 2 ha. Eight (8) Temporary sample plots of size 50 m x 50 m was laid using systematic line transect at 100 m intervals in the compartment. Hierarchical clustering in SPSS was used to find clusters of patterns in the measurement space. Tree species such as; Eucalyptus cameldulensis, Eucalyptus tereticornis, Khaya ivorensis, Khaya senegalensis,Nauclea diderichi, Terminalia randii, and Terminalia superba with a total frequency of 60 were identified, belonging to 3 different families. At similarity 5.0 from the dendrogram using ward linkage, samples 48 - 6 formed the first cluster, samples 28 - 9 constituted the second cluster while samples 20 - 13 constituted the third cluster. From the dendrogram using centroid linkage, at similarity 5.0, samples 59 - 7 formed the first cluster, samples 32 - 31 constituted the second cluster, and samples 8 - 28 formed the third cluster while the fourth cluster combined samples 17 - 21 which is a combination of trees from the three families. Histogram was used to show the diameter at breast height and total height distribution.

scholarly journals A Latent Measure of Political Protest

2020 ◽  
Author(s):  
Erica Chenoweth ◽  
Vito D'Orazio ◽  
Joseph Wright
Keyword(s):  
Empirical Studies ◽  
Political Protest ◽  
Irt Models ◽  
Sample Classification ◽  
Spatial Coverage ◽  
Out Of Sample ◽  
Latent Dimension ◽  
Authoritarian Breakdown ◽  
Coding Rules

In recent years, scholars have developed a number of new databases with which to measure protest. Although these databases have distinct coding rules, all attempt to capture incidents of social conflict. We argue, however, that due to a variety of sources of measurement error, subjective coding decisions, and operational specifications, no single indicator of protest adequately measures how much protest exists in a given place at a given time. As a result, empirical studies that employ these measures yield inferences with limited generalizability. To increase the generalizability of the empirical findings, we suggest using an Item Response Theory (IRT) approach to estimate a latent dimension of protest using nine different protest measures that vary in their operational specifications as well as their temporal and spatial coverage. The estimates of the IRT models are used in two ways. First, to demonstrate how existing measures differ, the IRT’s item estimates are used to compare the nine measures of protest based on their degree of difficulty (the quantity of latent protest required to observe a ‘1’ in the data) and their ability to discriminate (the speed with which changes in the latent quantity of protest affect the probability of observing a ‘1’ in the data). Second, the estimated quantity of protest is applied to both monthly and yearly models of authoritarian breakdown. The results demonstrate that the latent protest variable increases the out-of-sample classification of authoritarian breakdown events; and improves in-sample prediction relative to existing global protest variables. Our study illustrates the potential value of modeling a latent dimension of protest rather than solely relying on observed indicators.

scholarly journals Seabed acoustic classification in the Pelotas basin, Brazil

2013 ◽  
Vol 61 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Paloma Lumi Costa ◽  
Lauro A. Saint Pastous Madureira ◽  
Marcelo Peres de Pinho
Keyword(s):  
Acoustic Method ◽  
Acoustic Parameter ◽  
Acoustic Energy ◽  
Bottom Surface ◽  
Fine Sediments ◽  
Lack Of Information ◽  
Sediment Types ◽  
Pelotas Basin ◽  
Reflectivity Data ◽  
Map Data

The present study sought to develop a seabed map of the region of the Pelotas Basin using acoustic methods. A total number of 1,507,823 seabed reflectivity data, collected during six oceanographic surveys, were processed to generate a seabed map. Data processing consisted of the classification of the acoustic parameter BSBS (Bottom Surface Backscattering Strength) obtained with the Scientific Echosounder EK 500 operating at a frequency of 38 kHz. BSBS is expressed in decibels (dB), and corresponds to a logarithm of the ratio between incident acoustic energy and the energy reflected by the seabed. Four BSBS value classes, associated with different sediment types, were established. High BSBS values are associated with coarse sediments, whereas low values indicate fine sediments. A seabed reflectivity map was generated using the Natural Neighbor method to interpolate the BSBS values organized according to the pre-established classes. Four features with high BSBS values were identified at 100-200 m depth. The largest one was found in the region of Santa Marta Cape and attributed mainly to consolidated seabed and/or the presence of biodetritic material, according to comparison with maps available in the literature. Above 500m depth, there was a predominance of acoustically low reflectivity sea floor, which was attributed to the presence of muddy sediment. Considering the lack of information on the seabed at great depths, the acoustic method was shown to be an alternative tool to obtain data on seabed characteristics in these regions.

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