Temporal and Spatial Analysis of Neural Tube Defects and Detection of Geographical Factors in Shanxi Province, China

PLOS_ONEPLOS ONE, Published 21 April 2016

By Yilan Liao, Yan Zhang, Lei He, Jinfeng Wang, Xin Liu, Ningxu Zhang, and Bing Xu

Background: Neural tube defects (NTDs) are congenital birth defects that occur in the central nervous system, and they have the highest incidence among all birth defects. Shanxi Province in China has the world’s highest rate of NTDs. Since the 1990s, China’s government has worked on many birth defect prevention programs to reduce the occurrence of NTDs, such as pregnancy planning, health education, genetic counseling, antenatal ultrasonography and serological screening. However, the rate of NTDs in Shanxi Province is still higher than the world’s average morbidity rate after intervention. In addition, Shanxi Province has abundant coal reserves, and is the largest coal production province in China. The objectives of this study are to determine the temporal and spatial variation of the NTD rate in rural areas of Shanxi Province, China, and identify geographical environmental factors that were associated with NTDs in the risk area.

Methods: In this study, Heshun County and Yuanping County in Shanxi Province, which have high incidence of NTDs, were selected as the study areas. Two paired sample T test was used to analyze the changes in the risk of NTDs from the time dimension. Ripley’s k function and spatial filtering were combined with geographic information system (GIS) software to study the changes in the risk of NTDs from the spatial dimension. In addition, geographical detectors were used to identify the risk geographical environmental factors of NTDs in the study areas, especially the areas close to the coal sites and main roads.

Cluster areas of Neural Tube Defects in Heshun County and Yuanping County.

Cluster areas of Neural Tube Defects in Heshun County and Yuanping County.

Results: In both Heshun County and Yuanping County, the incidence of NTDs was significantly (P<0.05) reduced after intervention. The results from spatial analysis showed that significant spatial heterogeneity existed in both counties. NTD clusters were still identified in areas close to coal sites and main roads after interventions. This study also revealed that the elevation, fault and soil types always had a larger influence on the incidence of NTDs in our study areas. In addition, distance to the river was a risk factor of NTDs in areas close to the coal sites and main roads.

Conclusion: The existing interventions may have played an important role to reduce the incidence of NTDs. However, there is still spatial heterogeneity in both counties after using the traditional intervention methods. The government needs to take more measures to strengthen the environmental restoration to prevent the occurrence of NTDs, especially those areas close to coal sites and main roads. The outcome of this research provides an important theoretical basis and technical support for the government to prevent the occurrence of NTDs.”

Risks of developing breast and colorectal cancer in association with incomes and geographic locations in Texas: a retrospective cohort study

bmc cancerBMC Cancer 2016 16:294, Published 26 April 2016

By Zheyu Liu, Kai Zhang, and Xianglin L. Du

Background: No study has been conducted to investigate the spatial pattern and association of socioeconomic status (such as income) with breast and colorectal cancer incidence in Texas, United States. This study aimed to determine whether median household income was associated with the risk of developing breast and colorectal cancer in Texas and to identify higher cancer risks by race/ethnicity and geographic areas.

Methods:This was a retrospective cohort study with an ecological component in using aggregated measures at the county level. We identified 243,677 women with breast cancer and 155,534 men and women with colorectal cancer residing in 254 counties in Texas in 1995–2011 from the public-use dataset of Texas Cancer Registry. The denominator population and median household income at the county level was obtained from the U.S. Bureau of the Census. Cancer incidence rates were calculated as number of cases per 100,000 persons and age-adjusted using the 2000 US population data. We used the ArcGIS v10.1 (geographic information system software) to identify multiple clustered counties with high and low cancer incidences in Texas.

Geographic variations of colorectal cancer incidence adjusted for age and median household income in Texas, 1995–2011

Geographic variations of colorectal cancer incidence adjusted for age and median household income in Texas, 1995–2011

Results: Age-adjusted breast cancer incidence rate in the highest median income quintile group was 151.51 cases per 100,000 in 2008–2011 as compared to 98.95 cases per 100,000 in the lowest median income quintile group. The risk of colorectal cancer appeared to decrease with increasing median income in racial/ethnic population. Spatial analysis revealed the significant low breast cancer incidence cluster regions located in southwest US-Mexico border counties in Texas.

Conclusions: This study demonstrated that higher income was associated with an increased risk of breast cancer and a decreased risk of colorectal cancer in Texas. There were geographic variations with cancer incidence clustered in high risk areas in Texas. Future studies may need to explore more factors that might explain income and cancer risk associations and their geographic variations.”

Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China

SpringerPlus, Published 11 April 2016

By Yong Xiao, Xiaomin Gu, Shiyang YinEmail author, Jingli Shao, Yali Cui, Qiulan Zhang, and Yong Niu

“Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R2) was applied to evaluate the accuracy of different methods.

Groundwater level drawdown during 2001 and 2013.

Groundwater level drawdown during 2001 and 2013.

“The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial–proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001–2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.”

Protected areas in Borneo may fail to conserve tropical forest biodiversity under climate change

405853Biological Conservation, Volume 184, April 2015, Pages 414–423

By Sarah A. Scriven, Jenny A. Hodgson, Colin J. McClean, and Jane K. Hill

“Protected areas (PAs) are key for conserving rainforest species, but many PAs are becoming increasingly isolated within agricultural landscapes, which may have detrimental consequences for the forest biota they contain. We examined the vulnerability of PA networks to climate change by examining connectivity of PAs along elevation gradients. We used the PA network on Borneo as a model system, and examined changes in the spatial distribution of climate conditions in future. A large proportion of PAs will not contain analogous climates in future (based on temperature projections for 2061–2080), potentially requiring organisms to move to cooler PAs at higher elevation, if they are to track climate changes.

Map of Borneo showing location of refuge (n = 30) and source PAs (n = 210). Source PAs are shaded according to the minimum dispersal ability required for individuals to successfully reach target PAs (assuming 100% forest cover in PAs, a population density of 125 individuals per 250 m forest grid cell and using RCP8.5 temperature projections).

Map of Borneo showing location of refuge (n = 30) and source PAs (n = 210). Source PAs are shaded according to the minimum dispersal ability required for individuals to successfully reach target PAs (assuming 100% forest cover in PAs, a population density of 125 individuals per 250 m forest grid cell and using RCP8.5 temperature projections).

“For the highest warming scenario (RCP8.5), few (11–12.5%; 27–30/240) PAs were sufficiently topographically diverse for analogous climate conditions (present-day equivalent or cooler) to remain in situ. For the remaining 87.5–89% (210–213/240) of PAs, which were often situated at low elevation, analogous climate will only be available in higher elevation PAs. However, over half (60–82%) of all PAs on Borneo are too isolated for poor dispersers (<1 km per generation) to reach cooler PAs, because there is a lack of connecting forest habitat. Even under the lowest warming scenario (RCP2.6), analogous climate conditions will disappear from 61% (146/240) of PAs, and a large proportion of these are too isolated for poor dispersers to reach cooler PAs. Our results suggest that low elevation PAs are particularly vulnerable to climate change, and management to improve linkage of PAs along elevation gradients should be a conservation priority.”

New Book, “Python Scripting for ArcGIS,” Now Available

Python Scripting for ArcGIS is a guide for experienced users of ArcGIS Desktop to get started with Python scripting without needing previous programming experience.

Python Scripting for ArcGIS is a guide for experienced users of ArcGIS Desktop to get started with Python scripting without needing previous programming experience.

Python Scripting for ArcGISis a guide to help experienced users of ArcGIS for Desktop get started with Python scripting. The book teaches users how to write Python code that works with spatial data to automate geoprocessing tasks in ArcGIS. Experience with other scripting or programming languages is helpful but not required.

Key topics in this book include Python language fundamentals, exploring and manipulating spatial data, working with geometries and rasters, map scripting, debugging and error handling, creating functions and classes, and creating and sharing script tools. Python Scripting for ArcGIS contains 14 chapters with corresponding online data and exercises available on the Esri Press book resource page at esripress.esri.com/bookresources.

Author Paul A. Zandbergen is an associate professor of geography at the University of New Mexico in Albuquerque where he teaches classes in GIS and spatial analysis. His areas of expertise include GIS applications in criminology, economics, health, and ecology, as well as spatial and statistical analysis techniques using GIS.

Python Scripting for ArcGIS is available at online retailers worldwide, at esri.com/esripress, or by calling 1-800-447-9778. Outside the United States, visit esri.com/esripressorders for complete ordering options, or visit esri.com/distributors to contact your local Esri distributor. (Print ISBN: 978-1-58948-371-2, 358 pages, US$79.99) (E-book ISBN: 978-1-58948-362-0, 358 pages, US$79.99).

A mobile-optimized edition is available from the Esri Books app (ISBN: 978-1-58948-402-3, US$59.99).

ArcGIS 10.3 Now Certified OGC Compliant

Esri logoEsri Users Benefit from Interoperability Standard

As part of Esri’s ongoing support of GIS interoperability, the latest ArcGIS 10.3 release is now certified as Open Geospatial Consortium, Inc. (OGC), compliant.

This certification from OGC reaffirms Esri’s continued commitment to standards-based interoperability. Through its support for OGC specifications, ArcGIS users can access data and services from many different sources, regardless of the technology used by those sources. In addition, users can share their content with others, including non-Esri users, thus contributing to the larger goals of the open data movement.

“Our goal is to help our users be successful, and Esri sees technical interoperability as a key driver to successful implementations,” said Dr. Satish Sankaran, Esri product manager for interoperability and member of the OGC Architecture Board.

The OGC leads the development of geospatial interoperability standards. Esri is a long-standing, active OGC participant, helping GIS users to seamlessly work together.

Esri’s first OGC compliancy certificates were granted in 1999, and many more Esri ArcGIS platform products have met OGC compliancy since then.

See the full list of OGC-compliant products from Esri.

[Source: Esri press release]

A GIS-based Relational Data Model for Multi-dimensional Representation of River Hydrodynamics and Morphodynamics

EMS-S13648152Environmental Modelling & Software, Volume 65, March 2015, Pages 79–93

By Dongsu Kim, Marian Muste, and Venkatesh Merwade

“Highlights

  • Represent river data in a curvilinear coordinate system to support river channel oriented spatial analyses.
  • Represent multidimensional river features through points, lines, polygons, and volumes.
  • Represent simulated gridded data for river channels that can be readily coupled with observed data.
  • Represent spatio-temporal evolution of dynamic river objects using Eulerian or Lagrangian observational frameworks.
  • Efficiently store and retrieve data acquired in-situ along with the ancillary metadata.

“The emerging capabilities of the geo-based information systems to integrate spatial and temporal attributes of in-situ measurements is a long-waited solution to efficiently organize, visualize, and analyze the vast amount of data produced by the new generations of river instruments. This paper describes the construct of a river data model linked to a relational database that can be populated with both measured and simulated river data to facilitate descriptions of river features and processes using hydraulic/hydrologic terminology.

Diagram of the connectivity between multidimensional river objects in a cross-section and the river network: Relationship between the CrossSection3DPoint and CrossSection2DPoint in 3D cross-sections.

Diagram of the connectivity between multidimensional river objects in a cross-section and the river network: Relationship between the CrossSection3DPoint and CrossSection2DPoint in 3D cross-sections.

“The proposed model, labeled Arc River, is built in close connection with the existing Arc Hydro data model developed for water-related features to ensure the connection of the river characteristics with their floodplains and watersheds. This paper illustrates Arc River data model capabilities in conjunction with Acoustic Doppler Current Profiler measurements to demonstrate that essential river morphodynamics and hydrodynamics aspects can be described using data on the flow and its boundaries.”