標(biāo)題: Titlebook: Geospatial Technology for Human Well-Being and Health; Fazlay S. Faruque Book 2022 Springer Nature Switzerland AG 2022 Spatial analytics.G [打印本頁(yè)] 作者: hedonist 時(shí)間: 2025-3-21 19:38
書目名稱Geospatial Technology for Human Well-Being and Health影響因子(影響力)
書目名稱Geospatial Technology for Human Well-Being and Health影響因子(影響力)學(xué)科排名
書目名稱Geospatial Technology for Human Well-Being and Health網(wǎng)絡(luò)公開(kāi)度
書目名稱Geospatial Technology for Human Well-Being and Health網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Geospatial Technology for Human Well-Being and Health被引頻次
書目名稱Geospatial Technology for Human Well-Being and Health被引頻次學(xué)科排名
書目名稱Geospatial Technology for Human Well-Being and Health年度引用
書目名稱Geospatial Technology for Human Well-Being and Health年度引用學(xué)科排名
書目名稱Geospatial Technology for Human Well-Being and Health讀者反饋
書目名稱Geospatial Technology for Human Well-Being and Health讀者反饋學(xué)科排名
作者: 掙扎 時(shí)間: 2025-3-21 22:29
Building the Analytic Toolbox: From Spatial Analytics to Spatial Statistical Inference with Geospat Their intersection provides great opportunity for new insights in measuring health and well-being. Health analysts seek quantitative, decision-based outputs, but rapid advances in the volume and linkage of distributed data of multiple types have outpaced the development of detailed analytical and s作者: 責(zé)怪 時(shí)間: 2025-3-22 01:10 作者: DEAWL 時(shí)間: 2025-3-22 08:32 作者: 案發(fā)地點(diǎn) 時(shí)間: 2025-3-22 09:42
Understanding Health Data by Mobility Analytics,ognizing various mobility patterns for analyzing massive data. Data featuring both the dimensions of space and time is called spatiotemporal data. Spatiotemporal data have been recorded in studies such as climate science, neuroscience, social sciences, mobile health, epidemiology, transportation, cr作者: 散步 時(shí)間: 2025-3-22 15:09 作者: 散步 時(shí)間: 2025-3-22 21:07 作者: Radiculopathy 時(shí)間: 2025-3-23 00:14 作者: DEAF 時(shí)間: 2025-3-23 02:07 作者: Vldl379 時(shí)間: 2025-3-23 05:37
Geospatial Tools for Social Medicine: Understanding Rural-Urban Divide,es. The field of social medicine, in particular, seeks to understand how social, demographic, and economic conditions impact the practice of medicine and how public health policies can lead to a healthier society. Geospatial models in conjunction with geographic information systems (GIS) serve as ke作者: 違法事實(shí) 時(shí)間: 2025-3-23 12:56 作者: 欺騙世家 時(shí)間: 2025-3-23 14:58 作者: machination 時(shí)間: 2025-3-23 20:02 作者: 溺愛(ài) 時(shí)間: 2025-3-23 22:26
Linking Disease Outcomes to Environmental Risks: The Effects of Changing Spatial Scale,pacity to accumulate large amounts of data on individual behaviors, their movements in space and time, and exposure to various environmental risks. The ability to improve assessments of disease outcomes and environmental exposures is greatly enhanced when such data are combined with electronic healt作者: 指派 時(shí)間: 2025-3-24 02:40 作者: 極少 時(shí)間: 2025-3-24 09:50 作者: Cacophonous 時(shí)間: 2025-3-24 11:47
Challenges of Assessing Spatiotemporal Patterns of Environmentally Driven Infectious Diseases in Relinks between health outcomes and environmental exposures, as well as to guide national, local, and global environmental and health policies to achieve the Sustainable Development Goals (SDGs). The SDGs, under the 2030 Agenda for Sustainable Development, call for improving health and education, redu作者: sulcus 時(shí)間: 2025-3-24 15:51 作者: Epithelium 時(shí)間: 2025-3-24 20:46 作者: Alopecia-Areata 時(shí)間: 2025-3-25 01:42
Book 2022ceived as much attention as they should have received. These are a) limitations of different spatial analytical tools and b) progress in making geospatial environmental exposure data available for advanced health science research and for medical practice. This edited volume addresses those two less 作者: 宇宙你 時(shí)間: 2025-3-25 06:19
heories, uses and limitations of geospatial technologies in .Over the last thirty years or so, there have been tremendous advancements in the area of geospatial health; however, somehow, two aspects have not received as much attention as they should have received. These are a) limitations of differe作者: 尋找 時(shí)間: 2025-3-25 10:57 作者: 比目魚(yú) 時(shí)間: 2025-3-25 14:40 作者: figment 時(shí)間: 2025-3-25 16:57
https://doi.org/10.1007/978-3-642-14019-8ssociations with the local health status. In addition, this research discusses the techniques used in the study and the selection of additional socioeconomic and environmental variables for building the model.作者: opportune 時(shí)間: 2025-3-25 23:52
Using the NASA Giovanni System to Assess and Evaluate Remotely-Sensed and Model Data Variables Relealso present a discussion in which public health application fields will be matched with data variables and analysis options suitable for research in each field. A case history example will demonstrate how Giovanni allows rapid and skillful assessment and evaluation of connections between Earth observation data and the public health realm.作者: Negotiate 時(shí)間: 2025-3-26 01:43
Advancement in Airborne Particulate Estimation Using Machine Learning, calibrate lower-cost optical particle counters. For this calibration, it is critical that measurements of atmospheric pressure, humidity, and temperature are also made. We show that machine learning can be used to estimate the spatial distribution of airborne particulates from weather radar data.作者: lambaste 時(shí)間: 2025-3-26 06:07 作者: HARD 時(shí)間: 2025-3-26 12:32 作者: 大包裹 時(shí)間: 2025-3-26 12:59
https://doi.org/10.1007/978-1-4020-5483-9isease clusters or spreads are just a few of the types of analyses conducted to help guide policy-makers, health experts, and public officials in improving health outcomes, reducing inequity, and mitigating vulnerability. These techniques and methods will be reviewed in this chapter.作者: Nucleate 時(shí)間: 2025-3-26 17:36 作者: Adherent 時(shí)間: 2025-3-27 00:37 作者: finite 時(shí)間: 2025-3-27 04:36
Geospatial Analysis of the Urban Health Environment,isease clusters or spreads are just a few of the types of analyses conducted to help guide policy-makers, health experts, and public officials in improving health outcomes, reducing inequity, and mitigating vulnerability. These techniques and methods will be reviewed in this chapter.作者: 領(lǐng)巾 時(shí)間: 2025-3-27 05:33
Machine Learning, Big Data, and Spatial Tools: A Combination to Reveal Complex Facts That Impact Enonsiderable progress in developing a machine learning methodology for a variety of Environmental Health and Earth Science applications. In this chapter, we will review some examples of how machine learning has already been useful in environmental studies and some likely future applications.作者: abject 時(shí)間: 2025-3-27 11:26
Logarithmic and Exponential Functions,iminology, and earth science (Liu and Qu 2016; Atluri et al. 2017), to generate useful information. In fact, these fields experience a rapid transformation with the proliferation of vast amount of available spatiotemporal data.作者: 痛苦一下 時(shí)間: 2025-3-27 15:28 作者: 過(guò)時(shí) 時(shí)間: 2025-3-27 17:56 作者: dandruff 時(shí)間: 2025-3-28 01:31
978-3-030-71379-9Springer Nature Switzerland AG 2022作者: 克制 時(shí)間: 2025-3-28 02:52
https://doi.org/10.1007/978-3-030-71377-5Spatial analytics; Geospatial data; GIS; Public health; Environmental health; Machine learning; Seasonalit作者: 重力 時(shí)間: 2025-3-28 07:51
Thermally Activated Reactions and Diffusion,data, geospatial technology as a whole has become enormously powerful and functional. Complex concepts like human well-being and health require robust analytical capability, which modern-day geospatial tools can provide. While human well-being and health can be defined only conceptually, both medici作者: Reservation 時(shí)間: 2025-3-28 13:57
Mohammed Zahedul Islam Nizami,Yuta Nishina Their intersection provides great opportunity for new insights in measuring health and well-being. Health analysts seek quantitative, decision-based outputs, but rapid advances in the volume and linkage of distributed data of multiple types have outpaced the development of detailed analytical and s作者: 遺傳 時(shí)間: 2025-3-28 17:06
Partial Differentiation Part 2,spatially sparse, preferentially located, and temporally incomplete. The past decade has seen increasing interests in developing methods to estimate ambient air pollution levels at fine spatial scales and with complete spatial-temporal coverage. This is often accomplished by combining measurements f作者: Exterior 時(shí)間: 2025-3-28 20:57 作者: 歌唱隊(duì) 時(shí)間: 2025-3-29 01:12 作者: 下級(jí) 時(shí)間: 2025-3-29 06:12
Linear Equations and Inequalitieso rationalize the use of existing resources by directing users to the most appropriate institutions of the national public health services. This study describes and analyses the use of S24. For S24 data, the location attribute is an important source of information to describe its use. Consequently, 作者: patriot 時(shí)間: 2025-3-29 08:50
https://doi.org/10.1007/978-3-031-41203-5B. Worldwide, it infects 35% of the populations and brings on 0.3?M or more deaths each year. Vaccination is the primary method for protection against influenza. Because of the high viral mutation rate, vaccine selection and production cannot start early. Vaccines and antivirals are therefore often 作者: cogent 時(shí)間: 2025-3-29 15:14
https://doi.org/10.1007/978-1-4020-5763-2h science missions and related Earth system modeling projects since 2003. Over this period of time, numerous published research articles have cited the use of Giovanni for investigations of public health topics. These papers allow classification of the variables in the system which have proven usefu作者: Orthodontics 時(shí)間: 2025-3-29 17:51
https://doi.org/10.1007/978-1-4020-5483-9obal public health and environmental challenges of the twenty-first century occur in urban areas, and there are some issues that are unique to, or greatly exacerbated in, cities. Geospatial analysis and technology can help address these issues in a number of ways. For instance, calculating the geogr作者: 舔食 時(shí)間: 2025-3-29 23:20
Forces with a Common Point of Application,es. The field of social medicine, in particular, seeks to understand how social, demographic, and economic conditions impact the practice of medicine and how public health policies can lead to a healthier society. Geospatial models in conjunction with geographic information systems (GIS) serve as ke作者: Curmudgeon 時(shí)間: 2025-3-30 03:00 作者: Interstellar 時(shí)間: 2025-3-30 07:59 作者: NIB 時(shí)間: 2025-3-30 10:32 作者: 過(guò)濾 時(shí)間: 2025-3-30 13:40
Introduction to linear elasticity,pacity to accumulate large amounts of data on individual behaviors, their movements in space and time, and exposure to various environmental risks. The ability to improve assessments of disease outcomes and environmental exposures is greatly enhanced when such data are combined with electronic healt作者: Incorporate 時(shí)間: 2025-3-30 19:36
Dietmar Gross,Werner Hauger,Sanjay Govindjee Accurately portraying the spatial and temporal patterns of things such as diseases is crucial in disease control. However, one of the challenging issues embedded in spatiotemporal research is the modifiable areal and temporal unit problem (MATUP) which introduced inconsistent results among differen作者: resistant 時(shí)間: 2025-3-30 22:44
https://doi.org/10.1007/978-3-642-14019-8 assumption of spatial stationarity. This article reports a study that builds geographically weighted regression models to explore these associations further by using crime data of Akron, Ohio, which is a typical post-industrial city that has been experiencing problems of crime and public health. Vi作者: 暴露他抗議 時(shí)間: 2025-3-31 03:18 作者: 大喘氣 時(shí)間: 2025-3-31 06:19
Frictional Behaviours and Mechanismssmission cycle. This chapter provides a conceptual framework for the ecological niche modeling (ENM) and epidemiological modeling (EM) to offer diverse applications for the two approaches in anticipating disease risk. The two modeling approaches present a methodological suite of geospatial, ecologic作者: 名字 時(shí)間: 2025-3-31 13:09 作者: crockery 時(shí)間: 2025-3-31 15:07
Geospatial Technology for Human Well-Being and Health: An Overview,aking Geospatial Individual Environmental Exposure (GIEE) available for advanced health research and also for clinical practice in a usable format. Most of the chapters in this book volume address the first issue. This chapter focuses on discussing how geospatial technology can contribute to (a) eme作者: 嚙齒動(dòng)物 時(shí)間: 2025-3-31 20:43 作者: ESO 時(shí)間: 2025-4-1 01:37
Spatial Epidemiology and Public Health, and places that merit further attention from a public health perspective. In this chapter, we will provide an overview of spatial health and its many variations. We will present three overarching domains that encapsulate applications for GIS and spatial analyses focused on public health. And, we wi作者: scrape 時(shí)間: 2025-4-1 02:55
Health Line ,: An Econometric Spatial Analysis of Its Use,: demographic and socioeconomic information, characteristics of the Portuguese health system, and development indicators. In order to explain model spatial variability, the data autocorrelation can be explained in a Bayesian setting through different hierarchical log-Poisson regression models. A dif作者: 泥瓦匠 時(shí)間: 2025-4-1 07:24
Modeling and Predicting Influenza Circulations Using Earth Observing Data,le-to-people contact rates and also affects virus survivability and host’s susceptibility. Quite a few types of mathematical techniques can model the association between influenza circulation and meteorological condition. An example of using air temperature and specific humidity to model influenza c作者: Fester 時(shí)間: 2025-4-1 11:04
Geospatial Tools for Social Medicine: Understanding Rural-Urban Divide, most appropriately and accurately explore and quantify the associations between place-based factors and health outcomes, how to detect the potential associations that may be masked due to the selected geospatial models used, and how to deal with the uncertainties, biases, and errors involved in geo作者: 自愛(ài) 時(shí)間: 2025-4-1 18:09 作者: Generalize 時(shí)間: 2025-4-1 20:41
