scholarly journals Hyperspectral data as a biodiversity screening tool can differentiate among diverse Neotropical fishes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. A. Kolmann ◽  
M. Kalacska ◽  
O. Lucanus ◽  
L. Sousa ◽  
D. Wainwright ◽  
...  
Keyword(s):  
Screening Tool ◽  
Rapid Assessment ◽  
Interspecific Variation ◽  
Hyperspectral Data ◽  
Spectral Signature ◽  
Neotropical Fishes ◽  
Spectral Signatures ◽  
Floral Diversity ◽  
History Of ◽  
Taxonomic Confusion

AbstractHyperspectral data encode information from electromagnetic radiation (i.e., color) of any object in the form of a spectral signature; these data can then be used to distinguish among materials or even map whole landscapes. Although hyperspectral data have been mostly used to study landscape ecology, floral diversity and many other applications in the natural sciences, we propose that spectral signatures can be used for rapid assessment of faunal biodiversity, akin to DNA barcoding and metabarcoding. We demonstrate that spectral signatures of individual, live fish specimens can accurately capture species and clade-level differences in fish coloration, specifically among piranhas and pacus (Family Serrasalmidae), fishes with a long history of taxonomic confusion. We analyzed 47 serrasalmid species and could distinguish spectra among different species and clades, with the method sensitive enough to document changes in fish coloration over ontogeny. Herbivorous pacu spectra were more like one another than they were to piranhas; however, our method also documented interspecific variation in pacus that corresponds to cryptic lineages. While spectra do not serve as an alternative to the collection of curated specimens, hyperspectral data of fishes in the field should help clarify which specimens might be unique or undescribed, complementing existing molecular and morphological techniques.

Rapid Assessment Of Taal Volcano Protected Landscape (TVPL) Terrestrial Biodiversity

2017 ◽  
Vol 11 (1) ◽  
Keyword(s):  
Animal Species ◽  
Rapid Assessment ◽  
Ecological Status ◽  
Taal Volcano ◽  
Ecological Barriers ◽  
Floral Diversity ◽  
Forested Areas ◽  
Baseline Information ◽  
Study Sites ◽  
Terrestrial Biodiversity

With the exponential rise of human activities in the past decades, majority of studies conducted in Taal Volcano Protected Landscape (TVPL) are geared towards the conservation and preservation of Lake Taal’s remaining biodiversity. However, the current structure and assemblage of its terrestrial biotic communities remain relatively unstudied. In this study, we conducted biodiversity censuses in the four sites in TVPL to provide baseline information regarding the community structure of the selected study sites. Comparison of the plant diversity in Taal Volcano Crater Island and Romandan Falls within the forested areas of Mataas na Kahoy, Batangas reveal that both sites support remarkably different vegetation, with the former supporting a smaller floral diversity. The fairly small number of animal samples present difficulty in providing conclusive findings to the wildlife structure of the two study sites. However, the presence of 11 animal species exhibit valuable results in determining the ecological status of TVPL. It is deduced that several ecological barriers exist between the sites, which is attributed to their unique terrestrial biota.

Evaluation of the Use of a Diabetes Risk Test to Identify Prediabetes in an Employee Wellness Screening

2021 ◽  
pp. 089719002199701
Author(s):  
Eileen D. Ward ◽  
Whitney A. Hopkins ◽  
Kayce Shealy
Keyword(s):  
At Risk ◽  
American Diabetes Association ◽  
Hemoglobin A1c ◽  
Screening Tool ◽  
Screening Program ◽  
Diabetes Risk ◽  
Risk Scores ◽  
Cutoff Score ◽  
Employee Wellness ◽  
History Of

Background: The American Diabetes Association (ADA) Diabetes Risk Test (DRT) is a screening tool to identify people at risk for developing diabetes. Individuals with a DRT score of 5 or higher may have prediabetes or diabetes and should see a healthcare provider. Objective: To determine how many additional employees are identified as being at risk for developing diabetes during an employee wellness screening by using a more stringent DRT cutoff score of 4 instead of 5. Methods: During an annual employee wellness screening event, a hemoglobin A1C (A1c) was drawn for participants with a DRT score of > 4 or by request regardless of risk score. A1C values were classified as normal (<5.7%), prediabetes (>5.7 and <6.5%) or diabetes (>6.5%). Risk scores and A1C values were analyzed using descriptive statistics. Cost of additional laboratory testing was also reviewed. Results: An A1C was collected for 158 participants. Fourteen of 50 (28%) participants with a DRT of 4 had A1c values in the prediabetes range and no history of diabetes or prediabetes. Using the lower DRT score of 4 resulted in an additional expenditure of $305 with $85.40 resulting in the identification of an otherwise unaware person at risk for developing diabetes. Conclusion: Using a DRT cutoff score of 4 as part of an employee wellness screening program resulted in additional laboratory costs to identify persons at risk for developing diabetes but also allowed for earlier education to slow or stop the progression to diabetes which may reduce healthcare costs over time.

Algoritmo de Descomposición Ciega Basado en el Modelo de Mezcla Multi-Lineal

2021 ◽  
Author(s):  
◽  
J. N. Mendoza Chavarría
Keyword(s):  
State Of The Art ◽  
Hyperspectral Data ◽  
Spectral Unmixing ◽  
Mixing Models ◽  
Nonlinear Interactions ◽  
Estimation Errors ◽  
Spectral Signatures ◽  
Scattering Effects ◽  
Linear Unmixing ◽  
Multiple Light Scattering

Spectral unmixing has proven to be a great tool for the analysis of hyperspectral data, with linear mixing models (LMMs) being the most used in the literature. Nevertheless, due to the limitations of the LMMs to accurately describe the multiple light scattering effects in multi and hyperspectral imaging, new mixing models have emerged to describe nonlinear interactions. In this paper, we propose a new nonlinear unmixing algorithm based on a multilinear mixture model called Non-linear Extended Blind Endmember and Abundance Extraction (NEBEAE), which is based on a linear unmixing method established in the literature. The results of this study show that proposed method decreases the estimation errors of the spectral signatures and abundance maps, as well as the execution time with respect the state of the art methods.

scholarly journals High Positive Psychiatrie Screening Rates in an Urban Homeless Population

2013 ◽  
Vol 58 (6) ◽  
pp. 353-360 ◽  
Author(s):  
Aravind Ganesh ◽  
David J T Campbell ◽  
Janette Hurley ◽  
Scott Patten
Keyword(s):  
Mental Illness ◽  
Screening Tool ◽  
Psychiatric Symptoms ◽  
Homeless Population ◽  
Summary Statistics ◽  
Preliminary Assessment ◽  
Screening Process ◽  
Straightforward Application ◽  
History Of ◽  
Psychiatric Screening

Objective: To carry out a preliminary assessment of the use of a psychiatric screening tool in an urban homeless population, and to estimate the potential prevalence of undiagnosed and (or) unmanaged mental illness in this population. Methods: Participants ( n = 166) were recruited from the Calgary Drop-in and Rehab Centre to complete a questionnaire containing 6 modules screening for common psychiatric disorders. Summary statistics were used in the analysis. Results: Only 12 respondents (7%) screened negative on each of the 6 modules. The screening process determined that 60.2% of the sample ( n = 100) had probable mental illness but reported no history of psychiatric diagnosis or treatment. Conclusions: A straightforward application of screening (in which screen-positive subjects are referred for assessment) would be difficult in this population as most will screen positive. The results highlight the tremendous burden of psychiatric symptoms in this population.

scholarly journals An original method for tree species classification using multitemporal multispectral and hyperspectral satellite data

Silva Fennica ◽  
2020 ◽  
Vol 54 (2) ◽  
Author(s):  
Olga Grigorieva ◽  
Olga Brovkina ◽  
Alisher Saidov
Keyword(s):  
Tree Species ◽  
Original Method ◽  
Hyperspectral Data ◽  
Species Classification ◽  
Multispectral Data ◽  
Spectral Signatures ◽  
Tree Species Classification ◽  
Temporal Features ◽  
Study Sites ◽  
Near Future

This study proposes an original method for tree species classification by satellite remote sensing. The method uses multitemporal multispectral (Landsat OLI) and hyperspectral (Resurs-P) data acquired from determined vegetation periods. The method is based on an original database of spectral features taking into account seasonal variations of tree species spectra. Changes in the spectral signatures of forest classes are analyzed and new spectral–temporal features are created for the classification. Study sites are located in the Czech Republic and northwest (NW) Russia. The differences in spectral reflectance between tree species are shown as statistically significant in the sub-seasons of spring, first half of summer, and main autumn for both study sites. Most of the errors are related to the classification of deciduous species and misclassification of birch as pine (NW Russia site), pine as mixture of pine and spruce, and pine as mixture of spruce and beech (Czech site). Forest species are mapped with accuracy as high as 80% (NW Russia site) and 81% (Czech site). The classification using multitemporal multispectral data has a kappa coefficient 1.7 times higher than does that of classification using a single multispectral image and 1.3 times greater than that of the classification using single hyperspectral images. Potentially, classification accuracy can be improved by the method when applying multitemporal satellite hyperspectral data, such as in using new, near-future products EnMap and/or HyspIRI with high revisit time.

scholarly journals 1D-CONVOLUTIONAL AUTOENCODER BASED HYPERSPECTRAL DATA COMPRESSION

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 15-21
Author(s):  
J. Kuester ◽  
W. Gross ◽  
W. Middelmann
Keyword(s):  
Dimensional Space ◽  
Hyperspectral Data ◽  
Spectral Dimension ◽  
Sensor Technology ◽  
Spectral Signature ◽  
Support Vector ◽  
Data Sets ◽  
Reconstruction Accuracy ◽  
Spectral Correlation ◽  
Convolutional Autoencoder

Abstract. Hyperspectral sensor technology has been advancing in recent years and become more practical to tackle a variety of applications. The arising issues of data transmission and storage can be addressed with the help of compression. To minimize the loss of important information, high spectral correlation between adjacent bands is exploited. In this paper, we introduce an approach to compress hyperspectral data based on a 1D-Convolutional Autoencoder. Compression is achieved through reducing correlation by transforming the spectral signature into a low-dimensional space, while simultaneously preserving the significant features. The focus lies on compression of the spectral dimension. The spatial dimension is not used in the compression in order not to falsify correlation between the spectral dimension and accuracy of the reconstruction. The proposed 1D-Convolutional Autoencoder efficiently finds and extracts features relevant for compression. Additionally, it can be exploited as a feature extractor or for dimensionality reduction. The hyperspectral data sets Greding Village and Pavia University were used for the training and the evaluation process. The reconstruction accuracy is evaluated using the Signal to Noise Ratio and the Spectral Angle. Additionally, a land cover classification using a multi-class Support Vector Machine is used as a target application. The classification performance of the original and reconstructed data are compared. The reconstruction accuracy of the 1D-Convolutional Autoencoder outperforms the Deep Autoencoder and Nonlinear Principal Component Analysis for the used metrics and for both data sets using a fixed compression ratio.

scholarly journals Mobile Application Development for Spectral Signature of Weed Species in Rice Farming

2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Nor Athirah Roslin ◽  
Nik Norasma Che’Ya ◽  
Nursyazyla Sulaiman ◽  
Lutfi Amir Nor Alahyadi ◽  
Mohd Razi Ismail
Keyword(s):  
Mobile Application ◽  
Near Infrared ◽  
Spectral Signature ◽  
Weed Species ◽  
Application Development ◽  
Spectral Signatures ◽  
Weed Infestation ◽  
Access Information ◽  
Master Builder ◽  
And Control

Weed infestation happens when there is intense competition between rice and weeds for light, nutrients and water. These conditions need to be monitored and controlled to lower the growth of weeds as they affected crops production. The characteristics of weeds and rice are challenging to differentiate macroscopically. However, information can be acquired using a spectral signature graph. Hence, this study emphasises using the spectral signature of weed species and rice in a rice field. The study aims to generate a spectral signature graph of weeds in rice fields and develop a mobile application for the spectral signature of weeds. Six weeds were identified in Ladang Merdeka using Fieldspec HandHeld 2 Spectroradiometer. All the spectral signatures were stored in a spectral database using Apps Master Builder, viewed using smartphones. The results from the spectral signature graph show that the jungle rice (Echinochloa spp.) has the highest near-infrared (NIR) reflectance. In contrast, the saromacca grass (Ischaemum rugosum) shows the lowest NIR reflectance. Then, the first derivative (FD) analysis was run to visualise the separation of each species, and the 710 nm to 750 nm region shows the highest separation. It shows that the weed species can be identified using spectral signature by FD analysis with accurate separation. The mobile application was developed to provide information about the weeds and control methods to the users. Users can access information regarding weeds and take action based on the recommendations of the mobile application.

scholarly journals HYPERSPECTRAL REMOTE SENSING ROLE IN ENHANCING CROP MAPPING: A COMPARISON BETWEEN DIFFERENT SUPERVISED SEGMENTATION ALGORITHMS

2019 ◽  
Vol 1 (1) ◽  
pp. 25-37
Author(s):  
Mohamad M. Awad
Keyword(s):  
Remote Sensing ◽  
Eastern Mediterranean ◽  
Hyperspectral Data ◽  
Spectral Angle Mapper ◽  
New Approach ◽  
Spectral Signatures ◽  
Agriculture Sector ◽  
Supervised Segmentation ◽  
Eastern Mediterranean Basin ◽  
Crop Mapping

In agriculture sector there is need for cheap, fast, and accurate data and technologies to help decision makers to find solutions for many agricultural problems. Many solutions depend significantly on the accuracy and efficiency of the crop mapping and crop yield estimation processes. High resolution spectral remote sensing can improve substantially crop mapping by reducing similarities between different crop types which has similar ecological conditions. This paper presents a new approach of combining a new tool, hyperspectral images and technologies to enhance crop mapping.  The tool includes spectral signatures database for the major crops in the Eastern Mediterranean Basin and other important metadata and processing functions. To prove the efficiency of the new approach, major crops such as “winter wheat” and “spring potato” are mapped using the spectral signatures database in the new tool, three different supervised algorithms, and CHRIS-Proba hyperspectral satellite images. The evaluation of the results showed that deploying different hyperspectral data and technologies can improve crop mapping. The improvements can be noticed with the increase of the accuracy to more than 86% with the use of the supervised algorithm Spectral Angle Mapper (SAM).

Abstract 17208: Successful Implementation of Grip Strength Measurement as a Frailty Screening Tool

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Gloria Y Kim ◽  
Arati A Gangadharan ◽  
Craig S Brown ◽  
Nicholas H Osborne ◽  
Matthew Corriere
Keyword(s):  
Grip Strength ◽  
Screening Tool ◽  
Frailty Index ◽  
Assessment Tools ◽  
Successful Implementation ◽  
Strength Measurement ◽  
Strength Assessment ◽  
Related Information ◽  
History Of ◽  
Grip Strength Measurement

Introduction: Objective screening for frailty is seldom performed because existing tools are time consuming and usually applied post-hoc. Implementation of efficient and feasible frailty screening approaches within clinic is needed. Purpose and hypothesis: We implemented grip strength measurement as a frailty screening tool in a cardiovascular clinic setting and compared this to existing frailty assessment tools, including the modified frailty index-5 (mFI-5) and -11 (mFI-11). We hypothesized that grip strength would be comparable to the mFI-5 and -11, associated with common adverse events including urinary incontinence (UI) and falls, and increased diagnosis of frailty would occur as a result implementation. Methods: Grip strength measurement was integrated into clinic intake to screen for weakness, a frailty component. Measurements were performed routinely for cardiovascular clinic visits and entered into the EMR data field. Categorical frailty was assessed based on 20 th percentile for grip strength (kg) adjusted for gender and BMI. A “dotphrase” statement was built to streamline clinical documentation, and quarterly newsletters were used to disseminate coding and other related information. Categorical tests were used to evaluate associations between grip, weakness, and other measures of frailty. Results: A total of 4,447 unique patients had grip strength measured. Mean age was 63.3±15.6, BMI 29.6±7.0, 47.6% (n=2,115) were female, and 86.5% were Caucasian/White. Based on grip strength, 34.6% (n=1,538) were weak, and 22.0% (n=980) and 16.9% (n=754) were frail based on mFI-5 and mFI-11, respectively. Less than 10% (n=408, 9.25%) had a history of falls and 39 (0.88%) had UI. Falls were associated with weakness (P<0.001) but UI was not. Only 45 (1.01%) had a coded frailty diagnosis in the EMR. Among those with a frailty diagnosis, 35 (77.8%) were considered frail by grip. The negative predictive value (NPV) of the grip strength when mFI-5 is used as the gold standard is 0.84. Conclusions: Grip strength is both feasible and practical for frailty screening in clinical environments. Mismatch between screening-based and coding-based frailty prevalence suggests an opportunity to improve risk screening through routine grip strength assessment.

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