scholarly journals An Environmental GIS-based Variable Analysis of SARS-CoV-2 in the City of Recife, Brazil

2020 ◽  
Author(s):  
Arthur Souza ◽  
Caroline Mota ◽  
Amanda Rosa ◽  
Ciro Figueiredo ◽  
Ana Lucia Candeias
Keyword(s):  
Low Income ◽  
Public Services ◽  
Spatial Regression ◽  
Case Fatality ◽  
Global Scale ◽  
Environmental Data ◽  
Data Sets ◽  
Spatial Regression Analysis ◽  
Effective Drugs ◽  
The City

Abstract Background: Given the increasing rates at which cases of people infected by Covid-19 have been evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs and as yet no vaccine. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peak and descending behaviours of the curve of infections.Results: This study highlights the importance of identifying and mapping clusters of the most affected neighbourhoods and their determinant effects. We have identified that it is increasingly common for there to be a phase in which hotspots of confirmed cases appear in a well-developed and heavily densely-populated neighbourhood of the city of Recife. From there, the disease is carried to areas characterised by having a precarious provision of public services and a low-income population and this quickly creates hotspots of case-fatality rates. The results also help to understand the influence of the age, income, level of education of the population and, additionally, of the extent to which they can access public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

Recent Progress in Applying Advanced Computation Methods to Radar-Based Wave Measurements

2021 ◽  
Author(s):  
Morten Loell Vinther ◽  
Torbjørn Eide ◽  
Aurelia Paraschiv ◽  
Dickon Bonvik-Stone
Keyword(s):  
Doppler Radar ◽  
Risk Mitigation ◽  
Weather Conditions ◽  
Data Access ◽  
Environmental Data ◽  
Data Sets ◽  
Wave Measurements ◽  
Current Profiler ◽  
Pulse Doppler ◽  
Calm Weather

Abstract High quality environmental data are critical for any offshore activity relying on data insights to form appropriate planning and risk mitigation routines under challenging weather conditions. Such data are the most significant driver of future footprint reduction in offshore industries, in terms of costs savings, as well as operational safety and efficiency, enabled through ease of data access for all relevant stakeholders. This paper describes recent advancements in methods used by a dual-footprint Pulse-Doppler radar to provide accurate and reliable ocean wave height measurements. Achieved improvements during low wind weather conditions are presented and compared to data collected from other sources such as buoys and acoustic doppler wave and current profiler (ADCP) or legacy. The study is based on comparisons of recently developed algorithms applied to different data sets recorded at various sites, mostly covering calm weather conditions.

Mining Environmental Data in the ADMIRE Project Using New Advanced Methods and Tools

2012 ◽  
pp. 296-308
Author(s):  
Ondrej Habala ◽  
Martin Šeleng ◽  
Viet Tran ◽  
Branislav Šimo ◽  
Ladislav Hluchý
Keyword(s):  
Data Mining ◽  
Environmental Data ◽  
Environmental Applications ◽  
Data Sets ◽  
Distributed Data ◽  
New Methods ◽  
Prospective Application ◽  
Using Data ◽  
Computer Power

The project Advanced Data Mining and Integration Research for Europe (ADMIRE) is designing new methods and tools for comfortable mining and integration of large, distributed data sets. One of the prospective application domains for such methods and tools is the environmental applications domain, which often uses various data sets from different vendors where data mining is becoming increasingly popular and more computer power becomes available. The authors present a set of experimental environmental scenarios, and the application of ADMIRE technology in these scenarios. The scenarios try to predict meteorological and hydrological phenomena which currently cannot or are not predicted by using data mining of distributed data sets from several providers in Slovakia. The scenarios have been designed by environmental experts and apart from being used as the testing grounds for the ADMIRE technology; results are of particular interest to experts who have designed them.

Contexts of Cultural Change in Insular California

1997 ◽  
Vol 62 (2) ◽  
pp. 300-318 ◽  
Author(s):  
Jeanne E. Arnold ◽  
Roger H. Colten ◽  
Scott Pletka
Keyword(s):  
Cultural Change ◽  
Terrestrial Ecosystems ◽  
Environmental Data ◽  
Data Sets ◽  
American Antiquity ◽  
New Information ◽  
The Status ◽  
Status Differentiation ◽  
Animal Resources ◽  
Climatic Disturbances

Archaeological and ethnohistorical researchers in California are reaping the rewards from a wealth of new information about precontact and early historical cultural diversity, technologies, and marine and terrestrial ecosystems. Our recent investigations into the later prehistory of the island groups of southern California have centered on processes of sociopolitical evolution, including the emergence of status differentiation, evidence for intensification of craft production, and associated changes in human uses of animal resources as societies became more complex. We have linked some specific changes in diet, labor organization, and exchange to documented climatic disturbances, suggesting that opportunities created by such disruptions may have accounted in part for the timing of changes, but were not their cause in any mechanistic or simplistic sense. A recent American Antiquity report overlooks the primary results of this research and isolates the environmental data from a broad multidimensional model of cultural change in coastal California. We provide an update on the status of Channel Islands archaeology and identify the fundamental problems with approaches that extract and decontextualize environmental processes from cultural processes by assessing limited faunal data sets.

scholarly journals Potential contributions of remote sensing to ecosystem service assessments

2014 ◽  
Vol 38 (3) ◽  
pp. 328-353 ◽  
Author(s):  
Margaret E. Andrew ◽  
Michael A. Wulder ◽  
Trisalyn A. Nelson
Keyword(s):  
Remote Sensing ◽  
Ecosystem Services ◽  
Land Use Planning ◽  
Ecosystem Service ◽  
Service Providers ◽  
Plant Traits ◽  
Environmental Data ◽  
Data Sets ◽  
Biophysical Parameters ◽  
Ecological Processes

Ecological and conservation research has provided a strong scientific underpinning to the modeling of ecosystem services (ESs) over space and time, by identifying the ecological processes and components of biodiversity (ecosystem service providers, functional traits) that drive ES supply. Despite this knowledge, efforts to map the distribution of ESs often rely on simple spatial surrogates that provide incomplete and non-mechanistic representations of the biophysical variables they are intended to proxy. However, alternative data sets are available that allow for more direct, spatially nuanced inputs to ES mapping efforts. Many spatially explicit, quantitative estimates of biophysical parameters are currently supported by remote sensing, with great relevance to ES mapping. Additional parameters that are not amenable to direct detection by remote sensing may be indirectly modeled with spatial environmental data layers. We review the capabilities of modern remote sensing for describing biodiversity, plant traits, vegetation condition, ecological processes, soil properties, and hydrological variables and highlight how these products may contribute to ES assessments. Because these products often provide more direct estimates of the ecological properties controlling ESs than the spatial proxies currently in use, they can support greater mechanistic realism in models of ESs. By drawing on the increasing range of remote sensing instruments and measurements, data sets appropriate to the estimation of a given ES can be selected or developed. In so doing, we anticipate rapid progress to the spatial characterization of ecosystem services, in turn supporting ecological conservation, management, and integrated land use planning.

scholarly journals Challenges in Assembling and Managing Environmental Data Sets

Eos ◽  
2016 ◽  
Vol 97 ◽  
Author(s):  
Catherine O'Reilly ◽  
Stephanie Hampton ◽  
Sapna Sharma ◽  
Derek Gray ◽  
Jordan Read ◽  
...  
Keyword(s):  
Environmental Changes ◽  
Environmental Data ◽  
Data Sets ◽  
Term Data

Pulling together long-term data is increasingly important in assessing environmental changes, whether regionally or globally.

scholarly journals CartograTree: Enabling Landscape Genomics for Forest Trees

2016 ◽  
Author(s):  
Nic Herndon ◽  
Emily S Grau ◽  
Iman Batra ◽  
Steven A Demurjian Jr. ◽  
Hans A Vasquez-Gross ◽  
...  
Keyword(s):  
Population Structure ◽  
Economic Value ◽  
Genomic Data ◽  
Environmental Data ◽  
Geospatial Data ◽  
Data Sets ◽  
Forest Trees ◽  
Analytic Framework ◽  
Landscape Genomics ◽  
The World

Forest trees cover just over 30% of the earth's surface and are studied by researchers around the world for both their conservation and economic value. With the onset of high throughput technologies, tremendous phenotypic and genomic data sets have been generated for hundreds of species. These long-lived and immobile individuals serve as ideal models to assess population structure and adaptation to environment. Despite the availability of comprehensive data, researchers are challenged to integrate genotype, phenotype, and environment in one place. Towards this goal, CartograTree was designed and implemented as a repository and analytic framework for genomic, phenotypic, and environmental data for forest trees. One of key components, the integration of geospatial data, allows the display of environmental layers and acquisition of environmental metrics relative to the positions of georeferenced individuals.

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