Spatial and Temporal Analysis of Air Pollution Index and its Timescale-dependent Relationship with Meteorological Factors in Guangzhou, China, 2001–2011

Environmental PollutionEnvironmental Pollution, Volume 190, July 2014, Pages 75–81

By Li Lia, Jun Qianb, Chun-Quan Oua, Ying-Xue Zhoua, Cui Guoa, and Yuming Guoc


  • Air pollution is still serious in Guangzhou, China.
  • Air Pollution Index was associated with a variety of meteorological parameters.
  • The temporal relationships were timescale-dependent.
  • The findings should be taken into account in air quality forecasts and pollution control.

MATLAB Handle Graphics“There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001–2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures.”

Spatio-temporal Analysis of Abundances of Three Malaria Vector Species in Southern Benin using Zero-truncated Models

pnvParasites & Vectors 2014, 7:103 , Published Online 12 March 2014

By Nicolas Moiroux, Armel Djènontin, Abdul S Bio-Bangana, Fabrice Chandre, Vincent Corbel, and Hélène Guis


A better understanding of the ecology and spatial-temporal distribution of malaria vectors is essential to design more effective and sustainable strategies for malaria control and elimination. In a previous study, we analyzed presence-absence data of An. funestus, An. coluzzii, and An. gambiae s.s. in an area of southern Benin with high coverage of vector control measures. Here, we further extend the work by analysing the positive values of the dataset to assess the determinants of the abundance of these three vectors and to produce predictive maps of vector abundance.


Positive counts of the three vectors were assessed using negative-binomial zero-truncated (NBZT) mixed-effect models according to vector control measures and environmental covariates derived from field and remote sensing data. After 8-fold cross-validation of the models, predictive maps of abundance of the sympatric An. funestus, An. coluzzii, and An. gambiae s.s. were produced.


Cross-validation of the NBZT models showed a satisfactory predictive accuracy. Almost all changes in abundance between two surveys in the same village were well predicted by the models but abundances for An. gambiae s.s. were slightly underestimated. During the dry season, predictive maps showed that abundance greater than 1 bite per person per night were observed only for An. funestus and An. coluzzii. During the rainy season, we observed both increase and decrease in abundance of An. funestus, which are dependent on the ecological setting. Abundances of both An. coluzzii and An. gambiae s.s. increased during the rainy season but not in the same areas.



Our models helped characterize the ecological preferences of three major African malaria vectors. This works highlighted the importance to study independently the binomial and the zero-truncated count processes when evaluating vector control strategies. The study of the bio-ecology of malaria vector species in time and space is critical for the implementation of timely and efficient vector control strategies.”

Spatio-temporal Analysis on Enterovirus Cases through Integrated Surveillance in Taiwan

BMC Public HealthBMC Public Health, 2014 (14:11), Published 08 January 2014

By Ta-Chien Chan, Jing-Shiang Hwang, Rung-Hung Chen, Chwan-Chuen King, and Po-Huang Chiang


Spatio-temporal clusters of mild and severe EV cases from July 1999 to December 2008. Top: Severe EV cases aged from 0 to 14; Bottom: Mild EV cases from all ages.

Severe epidemics of enterovirus have occurred frequently in Malaysia, Singapore, Taiwan, Cambodia, and China, involving cases of pulmonary edema, hemorrhage and encephalitis, and an effective vaccine has not been available. The specific aim of this study was to understand the epidemiological characteristics of mild and severe enterovirus cases through integrated surveillance data.

All enterovirus cases in Taiwan over almost ten years from three main databases, including national notifiable diseases surveillance, sentinel physician surveillance and laboratory surveillance programs from July 1, 1999 to December 31, 2008 were analyzed. The Pearson’s correlation coefficient was applied for measuring the consistency of the trends in the cases between different surveillance systems. Cross correlation analysis in a time series model was applied for examining the capability to predict severe enterovirus infections. Poisson temporal, spatial and space-time scan statistics were used for identifying the most likely clusters of severe enterovirus outbreaks. The directional distribution method with two standard deviations of ellipse was applied to measure the size and the movement of the epidemic.

The secular trend showed that the number of severe EV cases peaked in 2008, and the number of mild EV cases was significantly correlated with that of severe ones occurring in the same week [r = 0.553, p < 0.01]. These severe EV cases showed significantly higher association with the weekly positive isolation rates of EV-71 than the mild cases [severe: 0.498, p < 0.01 vs. mild: 0.278, p < 0.01]. In a time series model, the increase of mild EV cases was the significant predictor for the occurrence of severe EV cases. The directional distribution showed that both the mild and severe EV cases spread extensively during the peak. Before the detected spatio-temporal clusters in June 2008, the mild cases had begun to rise since May 2008, and the outbreak spread from south to north.

Local public health professionals can monitor the temporal and spatial trends plus spatio-temporal clusters and isolation rate of EV-71 in mild and severe EV cases in a community when virus transmission is high, to provide early warning signals and to prevent subsequent severe epidemics.

Spatial and Temporal Analysis of Human Infection with Avian Influenza A(H7N9) Virus in China, 2013

Eurosurveillance, Volume 18, Issue 47, 21 November 2013

By W. Liu, K. Yang, X. Qi, K. Xu, H. Ji, J. Ai, A. Ge, Y. Wu, Y. Li, Q Dai, Q. Liang, C. Bao, R. Bergquist, F. Tang, and Y. Zhu

“Descriptive and geographic information system methods were used to depict the spatial and temporal characteristics of the outbreak of human infection with a novel avian influenza A(H7N9) virus in mainland China, the peak of which appeared between 28 March and 18 April 2013. As of 31 May 2013, there was a total of 131 reported human infections in China, with a cumulative mortality of 29% (38/131). The outbreak affected 10 provinces, with 106 of the cases being concentrated in the eastern coastal provinces of Zhejiang, Shanghai and Jiangsu.


“Statistically significant spatial clustering of cumulative human cases was identified by the Cuzick–Edwards’ k-nearest neighbour method. Three spatio-temporal clusters of cases were detected by space–time scan analysis. The principal cluster covered 18 counties in Zhejiang during 3 to 18 April (relative risk (RR): 26.39;p<0.0001), while two secondary clusters in March and April covered 21 counties along the provincial boundary between Shanghai and Jiangsu (RR: 6.35;p<0.0001) and two counties in Jiangsu (RR: 72.48;p=0.0025). The peak of the outbreak was in the eastern coastal provinces of Zhejiang, Shanghai and Jiangsu that was characterised by statistically significant spatio-temporal aggregation, with a particularly high incidence in March and April 2013.”

Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices

Atmosphere 2013, 4, 94-112

Alireza Shahabfar and Josef Eitzinger

“Six meteorological drought indices including percent of normal (PN), standardized precipitation index (SPI), China-Z index (CZI), modified CZI (MCZI), Z-Score (Z), the aridity index of E. de Martonne (I) are compared and evaluated for assessing spatio-temporal dynamics of droughts in six climatic regions in Iran.

Spatial distribution of monthly drought indices with the best correlation to standardized precipitation index (SPI) for January, February, March and April.

Spatial distribution of monthly drought indices with the best correlation to standardized precipitation index (SPI) for January, February, March and April.

“Results indicated that by consideration of the advantages and disadvantages of the mentioned drought predictors in Iran, the Z-Score, CZI and MCZI could be used as a good meteorological drought predictor. Depending on the month, the length of drought and climatic conditions of the region, they are an alternative to the SPI that has limitations both because of only a few available long term data series in Iran and its complex structure.”

Multimodal Accessibility Modeling from Coarse Transportation Networks in Africa

International Journal of Geographical Information ScienceInternational Journal of Geographical Information Science, published online 20 November 2012

Jean-Paul Kibambe Lubamba, Julien Radoux, and Pierre Defourny

“Accessibility is a key driving factor for economic development, social welfare, resources management, and land use planning. In many studies, modeling accessibility relies on proxy variables such as estimated travel time to selected destinations. In developing countries, estimating the travel time is hindered by scarce information about the transportation network, making it necessary to take into account off-network travel coupled with considerations of multimodal options available within the existing network. This research proposes such a hybrid approach that computes the travel time to selected destinations by optimizing together a fully modeled multimodal network and off-network travel. The model was applied in a region around Kisangani located in northeastern Democratic Republic of the Congo. Travel times to Kisangani from the hybrid approach were found to be in close agreement with field-based information (R 2 = 0.98). The developed approach also proved to better support real-world transportation constraints (such as transfer points between travel modes or barriers) than cost-distance-based travel-time modeling. Demonstration results from the hybrid approach highlight the potential for impact assessment of road construction or rehabilitation, development of secondary towns or markets, and for land use planning in general.”

Typhoid Fever and Its Association with Environmental Factors in the Dhaka Metropolitan Area of Bangladesh: A Spatial and Time-Series Approach

PLoS Negl Trop Dis PLOS Neglected Tropical Diseases, 24 January 2013

Ashraf M. Dewan, Robert Corner, Masahiro Hashizume, and Emmanuel T. Ongee

“Typhoid fever is a major cause of death worldwide with a major part of the disease burden in developing regions such as the Indian sub-continent. Bangladesh is part of this highly endemic region, yet little is known about the spatial and temporal distribution of the disease at a regional scale. This research used a Geographic Information System to explore, spatially and temporally, the prevalence of typhoid in Dhaka Metropolitan Area (DMA) of Bangladesh over the period 2005–9. This paper provides the first study of the spatio-temporal epidemiology of typhoid for this region. The aims of the study were: (i) to analyse the epidemiology of cases from 2005 to 2009; (ii) to identify spatial patterns of infection based on two spatial hypotheses; and (iii) to determine the hydro-climatological factors associated with typhoid prevalence. Case occurrences data were collected from 11 major hospitals in DMA, geocoded to census tract level, and used in a spatio-temporal analysis with a range of demographic, environmental and meteorological variables. Analyses revealed distinct seasonality as well as age and gender differences, with males and very young children being disproportionately infected. The male-female ratio of typhoid cases was found to be 1.36, and the median age of the cases was 14 years. Typhoid incidence was higher in male population than female (χ2 = 5.88, p<0.05). The age-specific incidence rate was highest for the 0–4 years age group (277 cases), followed by the 60+ years age group (51 cases), then there were 45 cases for 15–17 years, 37 cases for 18–34 years, 34 cases for 35–39 years and 11 cases for 10–14 years per 100,000 people. Monsoon months had the highest disease occurrences (44.62%) followed by the pre-monsoon (30.54%) and post-monsoon (24.85%) season.

Spatial regression between typhoid incidence (per 100,000 people) and distance to water bodies.

Spatial regression between typhoid incidence (per 100,000 people) and distance to water bodies. A) Shows spatial distribution of the t-value, B) shows the parameter estimates.

“The Student’s t test revealed that there is no significant difference on the occurrence of typhoid between urban and rural environments (p>0.05). A statistically significant inverse association was found between typhoid incidence and distance to major waterbodies. Spatial pattern analysis showed that there was a significant clustering of typhoid distribution in the study area. Moran’s I was highest (0.879; p<0.01) in 2008 and lowest (0.075; p<0.05) in 2009. Incidence rates were found to form three large, multi-centred, spatial clusters with no significant difference between urban and rural rates. Temporally, typhoid incidence was seen to increase with temperature, rainfall and river level at time lags ranging from three to five weeks. For example, for a 0.1 metre rise in river levels, the number of typhoid cases increased by 4.6% (95% CI: 2.4–2.8) above the threshold of 4.0 metres (95% CI: 2.4–4.3). On the other hand, with a 1°C rise in temperature, the number of typhoid cases could increase by 14.2% (95% CI: 4.4–25.0).”

Mapping the Evolution of Racially Mixed and Segregated Neighborhoods in Chicago

Journal of MapsJournal of Maps, Volume 8, Issue 4, December 2012

Jonathan Chipman, Richard Wright, Mark Ellis & Steven R. Holloway

“The Chicago metropolitan region consists of a spatially complex mosaic of neighborhoods, in which measures of racial and ethnic composition vary dramatically. Understanding these patterns and their evolution has been hindered by ambiguities in the use of terms like ‘diverse’ or ‘segregated’, which are often posited as opposite ends of a one-dimensional scale. Using a new taxonomy of neighborhood composition, we have mapped the evolving patterns of Chicago’s neighborhoods in 1990, 2000, and 2010, and tabulated census tracts that have undergone transitions or remained stable. Looking beyond the Chicago metropolitan area, we have developed an interactive atlas of similar maps for states and metropolitan areas across the United States.”

Schistosomiasis Transmission and Environmental Change: A Spatio-temporal Analysis in Porto de Galinhas, Pernambuco – Brazil

International Journal of Health GeographicsInternational Journal of Health Geographics 11:51, 20 November 2012

Elainne Christine Gomes, Onicio Batista Leal-Neto, Jones Albuquerque, Hernande Pereira Silva and Constança Simões Barbosa

“Background: In Brazil, schistosomiasis mansoni infection is an endemic disease that mainly affects the country’s rural populations who carry out domestic and social activities in rivers and water accumulations that provide shelter for the snails of the disease. The process of rural migration to urban centers and the disorderly occupation of natural environments by these populations from endemic areas have favored expansion of schistosomiasis to locations that had been considered to be disease-free. Based on environmental changes that have occurred in consequent to an occupation and urbanization process in the locality of Porto de Galinhas, the present study sought to identify the relationship between those chances, measure by remote-sensing techniques, and establish a new endemic area for schistosomiasis on the coast of Pernambuco State – Brazil.

Kernel maps show that the risk of disease occurrence and transmission were concentrated in the locality of Salinas in 2010.

Kernel maps show that the risk of disease occurrence and transmission were concentrated in the locality of Salinas in 2010.

“Methods: To gather prevalence data, two parasitological census surveys were conducted (2000 and 2010) using the Kato-Katz technique. Two malacological surveys were also conducted in the same years in order to define the density and infection rate of the intermediate host. Based on these data, spatial analyses were done, resulting in maps of the risk of disease transmission. To ascertain the environmental changes that have occurred at the locality, images from the QuickBird satellite were analyzed, thus resulting in land use maps.

“Results: Over this 10-year period, the foci of schistosomiasis became more concentrated in the Salinas district. This area was considered to be at the greatest risk of schistosomiasis transmission and had the highest prevalence rates over this period. The study illustrated that this was the area most affected by the environmental changes resulting from the disorderly urbanization process, which gave rise to unsanitary environments that favored the establishment and maintenance of foci of schistosomiasis transmission, thereby consolidating the process of expansion and endemization of this parasitosis. ”

Automatic Spatio-temporal Analysis of Construction Site Equipment Operations using GPS Data

Automation in ConstructionAutomation in Construction, Volume 29, January 2013, Pages 107–122

Nipesh Pradhananga and Jochen Teizer


  • Continuous data collection in construction equipment operation is lacking detail.
  • GPS data loggers can collect reliable location tracking data for further analysis.
  • A software user interface allows detection and visualization of active job site areas.
  • Information to equipment cycles, hours of operation, and proximity can be collected.
  • Data can be used in application, e.g., construction equipment simulation and safety.

“A literature review revealed several major shortcomings in the analysis of construction equipment operations data, for example, the lack of using realistic or real-time positioning data that can feed into an equipment operations analysis or simulation model. This paper presents technology and algorithms that have the potential in aiding the automated assessment of construction site equipment operations. Utilizing commercially available low-cost global positioning system (GPS) devices enables the continuous data logging of equipment location in addition to simultaneously recording timestamps. However, before any such spatio-temporal equipment data can be reliably collected on construction sites, the error rate of the GPS devices had to be evaluated. Data analysis methods and rules for monitoring construction site equipment operations and activity were then defined. A detailed software interface was finally created that allows a user to set, analyze, and visualize several important equipment parameters towards achieving the goal of creating more realistic equipment operation analysis and potential for inclusion in simulation models. Results from field experiments show that the developed technology is able to identify and track equipment activity- and safety-related information automatically for job site performance and layout decision making, respectively. The presented work will aid construction project managers in making better decisions to plan, manage, and control equipment-related work tasks on construction sites.”