Spatial Vision

2014 ◽  
Author(s):  
Thomas W. Cronin ◽  
Sönke Johnsen ◽  
N. Justin Marshall ◽  
Eric J. Warrant
Keyword(s):  
High Resolution ◽  
Polarized Light ◽  
Spatial Vision ◽  
Visual Space ◽  
Visual Task ◽  
Animal Life ◽  
Natural Sources ◽  
The World

This chapter talks about how humans are accustomed to seeing the world in high resolution. Compared to many other animals, humans' eyes are not particularly sensitive to light; nor is their sense of color especially good. The undoubted splendors of nature's ultraviolet colors are totally invisible to humans, as are the world's rich natural sources of polarized light. But when it comes to discerning fine spatial detail, few animals come close to humans. But regardless of whether the visual task is to follow a tiny target or to keep track of the physical arrangements of objects in a scene, all aspects of animal life have steered the evolution of spatial vision, particularly the distribution of an eye's sampling stations in visual space.

Groundwater storage in Africa

2017 ◽  
Author(s):  
Gabin Archambault
Keyword(s):  
High Resolution ◽  
Effective Porosity ◽  
Data Sources ◽  
Groundwater Storage ◽  
British Geological Survey ◽  
Full List ◽  
The World ◽  
Storage Type ◽  
Porosity Range ◽  
Aquifer Flow

This 5 km resolution grid presents groundwater storage in Africa (in mm). This parameter was estimated by combining the saturated aquifer thickness and effective porosity of aquifers across Africa. For each aquifer flow/storage type an effective porosity range was assigned based on a series of studies across Africa and surrogates in other parts of the world. Groundwater storage is given in millimeters. Detailed description of the methodology, and a full list of data sources used to develop the layer can be found in the peer-reviewed paper available here: http://iopscience.iop.org/article/10.1088/1748-9326/7/2/024009/pdf The raster and a high resolution PDF file are available for download on the website of British Geological Survey (BGS): http://www.bgs.ac.uk/research/groundwater/international/africanGroundwater/mapsDownload.html Groundwater Storage

scholarly journals Heatwaves in Kenya 1987–2016: Facts from CHIRTS High Resolution Satellite Remotely Sensed and Station Blended Temperature Dataset

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Martial Amou ◽  
Amatus Gyilbag ◽  
Tsedale Demelash ◽  
Yinlong Xu
Keyword(s):  
High Resolution ◽  
Adaptation Strategies ◽  
Reference Period ◽  
The West ◽  
Tana River ◽  
Short Period ◽  
The World ◽  
Northern Side ◽  
Data Source

As global temperatures continue to rise unabated, episodes of heat-related catastrophes across the world have intensified. In Kenya, heatwave phenomena and their associated impacts are ignored and neglected due to several reasons, including unreliable and inconsistent weather datasets and heatwave detection metrics. Based on CHIRTS satellite infrared estimates and station blended temperature, this study investigated the spatiotemporal distribution of the heatwave events over Kenya during 1987–2016 using the Heatwave Magnitude Index daily (HWMId). The results showed that contrary to the absence of heatwave records in official national and international disaster database about Kenya, the country experienced heatwaves ranging from less severe (normal) to deadly (super-extreme) between 1987 and 2016. The most affected areas were located in the eastern parts of the country, especially in Garissa and Tana River, and in the west-northern side around the upper side of Turkana county. It was also found that the recent years’ heatwaves were more severe in magnitude, duration, and spatial extent. The highest magnitude of the heatwaves was recorded in 2015 (HWMId = 22.64) while the average over the reference period is around 6. CHIRTS and HWMId were able to reveal and capture most critical heatwave events over the study period. Therefore, they could be used respectively as data source and detection metrics, for heatwaves disaster emergency warning over short period as well as for long-term projection to provide insight for adaptation strategies.

scholarly journals Tracking late Pleistocene Neandertals on the Iberian coast

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eduardo Mayoral ◽  
Ignacio Díaz-Martínez ◽  
Jéremy Duveau ◽  
Ana Santos ◽  
Antonio Rodríguez Ramírez ◽  
...  
Keyword(s):  
High Resolution ◽  
Iberian Peninsula ◽  
Social Group ◽  
Microbial Mats ◽  
3D Models ◽  
Age Classes ◽  
Upper Pleistocene ◽  
Wide Range ◽  
The World ◽  
Flooded Area

AbstractHere, we report the recent discovery of 87 Neandertal footprints on the Southwest of the Iberian Peninsula (Doñana shoreline, Spain) located on an upper Pleistocene aeolian littoral setting (about 106 ± 19 kyr). Morphometric comparisons, high resolution digital photogrammetric 3D models and detailed sedimentary analysis have been provided to characterized the footprints and the palaeoenvironment. The footprints were impressed in the shoreline of a hypersaline swamped area related to benthic microbial mats, close to the coastline. They have a rounded heel, a longitudinal arch, relatively short toes, and adducted hallux, and represent the oldest upper Pleistocene record of Neandertal footprints in the world. Among these 87 footprints, 31 are longitudinally complete and measure from 14 to 29 cm. The calculated statures range from 104 to 188 cm, with half of the data between 130 and 150 cm. The wide range of sizes of the footprints suggests the existence of a social group integrated by individuals of different age classes but dominated, however, by non-adult individuals. The footprints, which are outside the flooded area are oriented perpendicular to the shoreline. These 87 footprints reinforce the ecological scenario of Neandertal groups established in coastal areas.

scholarly journals Monoterpenes and Sesquiterpenes of Essential Oils from Psidium Species and Their Biological Properties

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 965
Author(s):  
Renan Campos e Silva ◽  
Jamile S. da Costa ◽  
Raphael O. de Figueiredo ◽  
William N. Setzer ◽  
Joyce Kelly R. da Silva ◽  
...  
Keyword(s):  
Essential Oils ◽  
Biological Activities ◽  
Biological Properties ◽  
Chemical Diversity ◽  
New Drugs ◽  
Natural Sources ◽  
Biological Potential ◽  
The World ◽  
Review Reports ◽  
Collection Sites

Psidium (Myrtaceae) comprises approximately 266 species, distributed in tropical and subtropical regions of the world. Psidium taxa have great ecological, economic, and medicinal relevance due to their essential oils’ chemical diversity and biological potential. This review reports 18 Psidium species growing around the world and the chemical and biological properties of their essential oils. Chemically, 110 oil records are reported with significant variability of volatile constituents, according to their seasonality and collection sites. Monoterpenes and sesquiterpenes with acyclic (C10 and C15), p-menthane, pinane, bisabolane, germacrane, caryophyllane, cadinane, and aromadendrane skeleton-types, were the primary constituents. The essential oils showed various biological activities, including antioxidant, antifungal, antibacterial, phytotoxic, larvicidal, anti-inflammatory, and cytotoxic properties. This review contributes to the Psidium species rational and economic exploration as natural sources to produce new drugs.

High-Resolution Fiber and Fiber Tract Imaging Using Polarized Light Microscopy in the Human, Monkey, Rat, and Mouse Brain

2016 ◽  
pp. 369-389 ◽  
Author(s):  
Karl Zilles ◽  
Nicola Palomero-Gallagher ◽  
David Gräßel ◽  
Philipp Schlömer ◽  
Markus Cremer ◽  
...  
Keyword(s):  
High Resolution ◽  
Light Microscopy ◽  
Mouse Brain ◽  
Polarized Light ◽  
Polarized Light Microscopy ◽  
Fiber Tract

scholarly journals Accelerating Super-Resolution and Visual Task Analysis in Medical Images

2020 ◽  
Vol 10 (12) ◽  
pp. 4282
Author(s):  
Ghada Zamzmi ◽  
Sivaramakrishnan Rajaraman ◽  
Sameer Antani
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Task Analysis ◽  
Multiple Scales ◽  
Medical Images ◽  
Computational Cost ◽  
Super Resolution ◽  
Visual Task ◽  
Learning Networks ◽  
High Resolution Images

Medical images are acquired at different resolutions based on clinical goals or available technology. In general, however, high-resolution images with fine structural details are preferred for visual task analysis. Recognizing this significance, several deep learning networks have been proposed to enhance medical images for reliable automated interpretation. These deep networks are often computationally complex and require a massive number of parameters, which restrict them to highly capable computing platforms with large memory banks. In this paper, we propose an efficient deep learning approach, called Hydra, which simultaneously reduces computational complexity and improves performance. The Hydra consists of a trunk and several computing heads. The trunk is a super-resolution model that learns the mapping from low-resolution to high-resolution images. It has a simple architecture that is trained using multiple scales at once to minimize a proposed learning-loss function. We also propose to append multiple task-specific heads to the trained Hydra trunk for simultaneous learning of multiple visual tasks in medical images. The Hydra is evaluated on publicly available chest X-ray image collections to perform image enhancement, lung segmentation, and abnormality classification. Our experimental results support our claims and demonstrate that the proposed approach can improve the performance of super-resolution and visual task analysis in medical images at a remarkably reduced computational cost.

scholarly journals Visual numerosity estimation is based on anisotropic representations of visual space

2021 ◽  
Author(s):  
Miao Li ◽  
Bert Reynvoet ◽  
Bilge Sayim
Keyword(s):  
Visual Field ◽  
Convex Hull ◽  
Visual Fields ◽  
Spatial Vision ◽  
Visual Space ◽  
Stimulus Features ◽  
Numerosity Estimation ◽  
Numerosity Perception ◽  
Average Eccentricity ◽  
Shed Light

Humans can estimate the number of visually displayed items without counting. This capacity of numerosity perception has often been attributed to a dedicated system to estimate numerosity, or alternatively to the exploitation of various stimulus features, such as density, convex hull, the size of items and occupancy area. The distribution of the presented items is usually not varied with eccentricity in the visual field. However, our visual fields are highly asymmetric, and to date, it is unclear how inhomogeneities of the visual field impact numerosity perception. Besides eccentricity, a pronounced asymmetry is the radial-tangential anisotropy. For example, in crowding, radially placed flankers interfere more strongly with target perception than tangentially placed flankers. Similarly, in redundancy masking, the number of perceived items in repeating patterns is reduced when the items are arranged radially but not when they are arranged tangentially. Here, we investigated whether numerosity perception is subject to the radial-tangential anisotropy of spatial vision to shed light on the underlying topology of numerosity perception. Observers were presented with varying numbers of discs and asked to report the perceived number. There were two conditions. Discs were predominantly arranged radially in the “radial” condition and tangentially in the “tangential” condition. Additionally, the spacing between discs was scaled with eccentricity. Physical properties, such as average eccentricity, average spacing, convex hull, and density were kept as similar as possible in the two conditions. Radial arrangements were expected to yield underestimation compared to tangential arrangements. Consistent with the hypothesis, numerosity estimates in the radial condition were lower compared to the tangential condition. Magnitudes of radial alignment (as well as predicted crowding strength) correlated with the observed numerosity estimates. Our results demonstrate a robust radial-tangential anisotropy, suggesting that the topology of spatial vision determines numerosity estimation. We suggest that asymmetries of spatial vision should be taken into account when investigating numerosity estimation.

scholarly journals Contribution to the Knowledge of the Genus Proceratium Roger (Hymenoptera: Formicidae: Proceratiinae) in the New World

Sociobiology ◽  
2019 ◽  
Vol 66 (4) ◽  
pp. 551
Author(s):  
Itanna Oliveira Fernandes ◽  
Jacques Hubert Charles Delabie ◽  
Fernando Castiblanco Fernández
Keyword(s):  
High Resolution ◽  
South America ◽  
New Record ◽  
New World ◽  
Distribution Data ◽  
Caribbean Islands ◽  
The World ◽  
High Resolution Images ◽  
South Of Brazil ◽  
First Time

The genus Proceratium Roger comprises rare ants that are irregularly distributed in tropical and temperate regions of the world. Despite this global distribution, these ants are rarely collected, likely due to their cryptobiotic lifestyle. In the New World, the genus comprises 22 known species distributed from Southern Canada to the South of Brazil, and in some Caribbean islands. The taxonomy of the genus Proceratium is here updated for South America. We describe P. amazonicum sp. nov, from Rondônia state and provide distribution data for P. brasiliense, P. convexipes, and P. silaceum. We also present, for the first time, high-resolution images of the P. colombicum type and P. ecuadoriense, and provide a new record of P. micrommatum from Peru, and comment about its morphological variation and distribution. A key for the workers of the P. micrommatum clade is also provided. The species we describe belongs to P. micrommatum clade and represents the second species recorded from Brazil after 60 years, since only P. brasiliense was known previously in the country.

scholarly journals High-resolution computational imaging of leaf hair patterning using polarized light microscopy

2013 ◽  
Vol 73 (4) ◽  
pp. 701-708 ◽  
Author(s):  
Marcelo Pomeranz ◽  
Jeffrey Campbell ◽  
Dan Siegal-Gaskins ◽  
Jacob Engelmeier ◽  
Tyler Wilson ◽  
...  
Keyword(s):  
High Resolution ◽  
Light Microscopy ◽  
Polarized Light ◽  
Computational Imaging ◽  
Polarized Light Microscopy

Collecting training data to map forest management at global scale

2021 ◽  
Author(s):  
Myroslava Lesiv ◽  
Dmitry Schepaschenko ◽  
Martina Dürauer ◽  
Marcel Buchhorn ◽  
Ivelina Georgieva ◽  
...  
Keyword(s):  
Forest Management ◽  
High Resolution ◽  
Remotely Sensed ◽  
Global Scale ◽  
Google Earth ◽  
Training Data ◽  
Tree Cover ◽  
Data Set ◽  
The World ◽  
Very High

<p>Spatially explicit information on forest management at a global scale is critical for understanding the current status of forests for sustainable forest management and restoration. Whereas remotely sensed based datasets, developed by applying ML and AI algorithms, can successfully depict tree cover and other land cover types, it has not yet been used to depict untouched forest and different degrees of forest management. We show for the first time that with sufficient training data derived from very high-resolution imagery a differentiation within the tree cover class of various levels of forest management is possible.</p><p>In this session, we would like to present our approach for labeling forest related training data by using Geo-Wiki application (https://www.geo-wiki.org/). Moreover, we would like to share a new open global training data set on forest management we collected from a series of Geo-Wiki campaigns. In February 2019, we organized an expert workshop to (1) discuss the variety of forest management practices that take place in different parts of the world; (2) generalize the definitions for the application at global scale; (3) finalize the Geo-Wiki interface for the crowdsourcing campaigns; and (4) build a data set of control points (or the expert data set), which we used later to monitor the quality of the crowdsourced contributions by the volunteers. We involved forest experts from different regions around the world to explore what types of forest management information could be collected from visual interpretation of very high-resolution images from Google Maps and Microsoft Bing, in combination with Sentinel time series and Normalized Difference Vegetation Index (NDVI) profiles derived from Google Earth Engine (GEE). Based on the results of this analysis, we expanded these campaigns by involving a broader group of participants, mainly people recruited from remote sensing, geography and forest research institutes and universities.</p><p>In total, we collected forest data for approximately 230 000 locations globally. These data are of sufficient density and quality and therefore could be used in many ML and AI applications for forests at regional and local scale.  We also provide an example of ML application, a remotely sensed based global forest management map at a 100 m resolution (PROBA-V) for the year 2015. It includes such classes as intact forests, forests with signs of human impact, including clear cuts and logging, replanted forest, woody plantations with a rotation period up to 15 years, oil palms and agroforestry. The results of independent statistical validation show that the map’s overall accuracy is 81%.</p>

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