Spatio-temporal pattern of ecological droughts and their impacts on health of vegetation in Northwestern China

2022 ◽  
Vol 305 ◽  
pp. 114356
Author(s):  
Tianliang Jiang ◽  
Xiaoling Su ◽  
Vijay P. Singh ◽  
Gengxi Zhang
Keyword(s):  
Temporal Pattern ◽  
Northwestern China ◽  
Spatio Temporal

Recursive Incremental Gaussian Mixture Network For Spatio-Temporal Pattern Processing

2016 ◽  
Author(s):  
Rafael C. Pinto ◽  
Paulo M. Engel ◽  
Milton R. Heinen
Keyword(s):  
Temporal Pattern ◽  
Gaussian Mixture ◽  
Pattern Processing ◽  
Spatio Temporal

scholarly journals Exploring short term spatio-temporal pattern of PM2.5 and PM10 and their relationship with meteorological parameters during COVID-19 in Delhi

Urban Climate ◽  
2021 ◽  
pp. 100944
Author(s):  
Manob Das ◽  
Arijit Das ◽  
Raju Sarkar ◽  
Papiya Mandal ◽  
Sunil Saha ◽  
...  
Keyword(s):  
Temporal Pattern ◽  
Meteorological Parameters ◽  
Short Term ◽  
Spatio Temporal ◽  
Pm2.5 And Pm10

scholarly journals Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behzad Kiani ◽  
Amene Raouf Rahmati ◽  
Robert Bergquist ◽  
Soheil Hashtarkhani ◽  
Neda Firouraghi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Policy Development ◽  
Temporal Pattern ◽  
Temporal Analysis ◽  
High Rate ◽  
Spatial Scan Statistic ◽  
Cross Sectional ◽  
Risk Areas ◽  
Spatio Temporal

Abstract Background Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. Methods This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. Results The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. Conclusion The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

A geographical analysis of the first wave of Covid-19 with reference to highland and lowland regions of India

2021 ◽  
Vol 67 (3) ◽  
pp. 263-281
Author(s):  
Bindhy Wasini Pandey ◽  
◽  
Yuvraj Singh ◽  
Usha Rani ◽  
Roosen Kumar ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Temporal Pattern ◽  
Regional Disparity ◽  
Healthcare Facilities ◽  
Indian Himalayan Region ◽  
Pollution Levels ◽  
Extensive Coverage ◽  
The World ◽  
Spatio Temporal

The issue of health has become a major concern in recent years as a result of extensive coverage of media reporting outbreaks of diseases and the spread of deadly infectious diseases around the world. There has been a growing concern over the accessibility and affordability of healthcare facilities. The spread of the ongoing pandemic COVID-19 has been felt all over the world. However, the rate of infection varies across certain regions of the world. There exists intra-regional disparity as well. Recent research shows that there are latitudinal and altitudinal variations in the spread of the COVID-19. This paper studies variation of infection COVID-19 across the highlands of the Indian Himalayan Region (IHR) and the lowland areas in India. The paper also examines the role of geographical spaces in the spread of coronavirus in these regions. The study indicates that place-based effects (altitude, temperature, pollution levels, etc.) on health can be seen in a variety of ways; therefore, locational issues are very important for addressing health questions. The paper also analyses the Spatio-temporal pattern of the COVID-19 pandemic in the study area to understand the nature of the disease in different locations.

Evaluation of the spatio-temporal pattern of urban ecological security using remote sensing and GIS

2012 ◽  
Vol 34 (3) ◽  
pp. 848-863 ◽  
Author(s):  
Peijun Du ◽  
Junshi Xia ◽  
Qian Du ◽  
Yan Luo ◽  
Kun Tan
Keyword(s):  
Remote Sensing ◽  
Temporal Pattern ◽  
Remote Sensing And Gis ◽  
Ecological Security ◽  
Spatio Temporal
Sign in / Sign up

Export Citation Format

Share Document