A new trapezoidal-mesh based data model for spatial operations

This paper presents a new spatial data model based on trapezoidal-mesh for implementing spatial operations within geographical information systems(GIS).Based only on the solid foundation of spatial operations,diversified application models can be established to bridge the gap between Digital Earth models and the real world with its real-world problems(‘connecting through location’).In this paper,the involved polygon features are decomposed into a series of trapezoidalmeshes.Then,geo-processing operations are employed on these meshes rather than the original polygon features,resulting in a relatively simple spatial computation.As a kind of model designed by integrating raster with vector,the model presented here has advantages over other models when carrying out spatial operations insofar as providing a solid foundation for achieving the grand goal of Digital Earth.The concept of this data model and the two extensive examples of its application in spatial operations are elaborated upon in this article.As a result,this article and the research that supports it,proves that the adoption of the trapezoidal-mesh model greatly improves the efficiency of spatial operations in GIS.

Geomorphology-oriented theoretical framework and construction method for value-added DEM

Digital elevation model(DEM)plays a fundamental role in the study of the earth system by expressing surface configuration,understanding surface process,and revealing surface mechanism.DEM is widely used in analysis and modeling in the field of geoscience.However,traditional DEM has the defect of single attribute,which is difficult to support the research in earth system science oriented to geoscience process and mechanism mining.Hence,realizing the value-added data model on the basis of traditional DEM is necessary to serve digital elevation modeling and terrain analysis under the background of a new geomorphology research paradigm and earth observation technology.A theoretical framework for value-added DEM that mainly includes concept,connotation,content,and categories,is constructed in this study.The relationship between different types of value-added DEMs as well as the research significance and application category of this theoretical framework are also proposed.The following are different methods of value-added DEMs:(1)value-added methods of DEM space and time dimensions that emphasize the integration of the ground and underground as well as coupling of time and space,(2)attribute-based value-added methods composed of material(including underground,surface,and ground)and morphological properties,and(3)value-added methods of features and physical elements that consider geographical objects and landform features formed by natural processes and artificial effects.The digital terrace,slope,and watershed models are used as examples to illustrate application scenarios of the three kinds of value-added methods.This study aims to improve expression methods of DEMs under the background of new surveying and mapping technologies by adding value to the DEM at three levels of dimensions,attributes,and elements as well as support knowledge-driven digital geomorphological analysis in the era of big data.

Spatial transmission and meteorological determinants of tuberculosis incidence in Qinghai Province,China:a spatial clustering panel analysis

Background:Tuberculosis(TB)is the notifiable infectious disease with the second highest incidence in the Qinghai province,a province with poor primary health care infrastructure.Understanding the spatial distribution of TB and related environmental factors is necessary for developing effective strategies to control and further eliminate TB.Methods:Our TB incidence data and meteorological data were extracted from the China Information System of Disease Control and Prevention and statistical yearbooks,respectively.We calculated the global and local Moran’s I by using spatial autocorrelation analysis to detect the spatial clustering of TB incidence each year.A spatial panel data model was applied to examine the associations of meteorological factors with TB incidence after adjustment of spatial individual effects and spatial autocorrelation.Results:The Local Moran’s I method detected 11 counties with a significantly high-high spatial clustering(average annual incidence:294/100000)and 17 counties with a significantly low-low spatial clustering(average annual incidence:68/100000)of TB annual incidence within the examined five-year period;the global Moran’s I values ranged from 0.40 to 0.58(all P-values<0.05).The TB incidence was positively associated with the temperature,precipitation,and wind speed(all P-values<0.05),which were confirmed by the spatial panel data model.Each 10°C,2 cm,and 1 m/s increase in temperature,precipitation,and wind speed associated with 9%and 3%decrements and a 7%increment in the TB incidence,respectively.Conclusions:High TB incidence areas were mainly concentrated in south-western Qinghai,while low TB incidence areas clustered in eastern and north-western Qinghai.Areas with low temperature and precipitation and with strong wind speeds tended to have higher TB incidences.