AUTOMATIC DIVISION OF CENSUS DISTRICT BASED ON CONSTRAINT DELAUNAY TRIANGULATION

Similar documents
A CONSISTENCY MAINTENANCE OF SHARED BOUNDARY AFTER POLYGON GENERALIZATION

Study on Delaunay Triangulation with the Islets Constraints

FACET SHIFT ALGORITHM BASED ON MINIMAL DISTANCE IN SIMPLIFICATION OF BUILDINGS WITH PARALLEL STRUCTURE

Research on Remote Sensing Image Template Processing Based on Global Subdivision Theory

A method of three-dimensional subdivision of arbitrary polyhedron by. using pyramids

Lecture 6: GIS Spatial Analysis. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

Study of Map Symbol Design Sub-System in Geostar Software

A Novel Method for Activity Place Sensing Based on Behavior Pattern Mining Using Crowdsourcing Trajectory Data

Spatial Data Models. Raster uses individual cells in a matrix, or grid, format to represent real world entities

Review of Cartographic Data Types and Data Models

The Design and Application of GIS Mathematical Model Database System with Meta-algorithm Li-Zhijiang

M. Andrea Rodríguez-Tastets. I Semester 2008

3 The standard grid. N ode(0.0001,0.0004) Longitude

SOME stereo image-matching methods require a user-selected

Hole repair algorithm in hybrid sensor networks

Study on 3D Geological Model of Highway Tunnels Modeling Method

AN INDIRECT GENERALIZATION OF CONTOUR LINES BASED ON DEM GENERALIZATION USING THE 3D DOUGLAS-PEUCKER ALGORITHM

LDAP-based IOT Object Information Management Scheme

WORKFLOW AND QUALITY CONTROL TO GENERATE DEM AND DSM BY AERIAL PHOTOGRAMMETRY

LINE SIMPLIFICATION BASED ON GEOGRAPHIC-FEATURE CONSTRAINT

Automatic Recognition and Resolution of Line Symbol Spatial Conflict in Cartography Based on Elastic Beams Model

Research Article. ISSN (Print) *Corresponding author Xue Ting

CHANGE-ONLY MODELING IN NAVIGATION GEO-DATABASES

The Application of Mathematical Morphology and Pattern Recognition to Building Polygon Simplification

Displacement Methods based on Field Analysis

A population grid for Andalusia Year Institute of Statistics and Cartography of Andalusia (IECA) Sofia (BU), 24 th October 2013

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

Representing Geography

Application of Three-dimensional Visualization Technology in Real Estate Management Jian Cui 1,a, Jiju Ma 2,b, Dongling Ma 1, c and Nana Yang 3,d

Overview of SAS/GIS Software

CONSTRUCTION OF DATABASE PLATFORM FOR INTERACTIVE GENERALIZATION ON LARGE SCALE TOPOGRAPHIC MAP

Use of GIS/GPS for supporting field enumeration

4.0 DIGITIZATION, EDITING AND STRUCTURING OF MAP DATA

Research on the allowable value of Lateral Breakthrough Error for Super long Tunnel from 20 to 50 kilometers

Computer Database Structure for Managing Data :-

Partition and Conquer: Improving WEA-Based Coastline Generalisation. Sheng Zhou

Math Geometry FAIM 2015 Form 1-A [ ]

EXTERIOR ORIENTATION OF LINE-ARRAY CCD IMAGES BASED ON QUATERNION SPHERICAL LINEAR INTERPOLATION

COMPARISON OF TWO METHODS FOR DERIVING SKELETON LINES OF TERRAIN

SLICE-ITERATION, A METHOD FOR AUTOMATIC EXTRATION OF VEHICLE LASER POINT CLOUD

Ancient Kiln Landscape Evolution Based on Particle Swarm Optimization and Cellular Automata Model

Using NHGIS: An Introduction

Chapter 7 Spatial Operation

AUTOMATIC EXTRACTION OF TERRAIN SKELETON LINES FROM DIGITAL ELEVATION MODELS

Study on Improving the Quality of Reconstructed NURBS Surfaces

A GPU-BASED ALGORITHM FOR THE GENERATION OF SPHERICAL VORONOI DIAGRAM IN QTM MODE

Lecturer 2: Spatial Concepts and Data Models

Data Models and Data processing in GIS

Application of GIS best path algorithm in Harbin Roads. Sui Min, *Wang Wei-fang

A REASONING COMPONENT S CONSTRUCTION FOR PLANNING REGIONAL AGRICULTURAL ADVANTAGEOUS INDUSTRY DEVELOPMENT

Half-edge Collapse Simplification Algorithm Based on Angle Feature

Class #2. Data Models: maps as models of reality, geographical and attribute measurement & vector and raster (and other) data structures

PLOTTING DEPTH CONTOURS BASED ON GRID DATA IN IRREGULAR PLOTTING AREAS

The Open Civil Engineering Journal

Algorithms for GIS csci3225

Research on Impact of Ground Control Point Distribution on Image Geometric Rectification Based on Voronoi Diagram

Contents of Lecture. Surface (Terrain) Data Models. Terrain Surface Representation. Sampling in Surface Model DEM

I. An Intro to ArcMap Version 9.3 and 10. 1) Arc Map is basically a build your own Google map

Efficient Path Finding Method Based Evaluation Function in Large Scene Online Games and Its Application

Map Library ArcView Version 1 02/20/03 Page 1 of 12. ArcView GIS

FOUR ADVANCES IN HANDLING UNCERTAINTIES IN SPATIAL DATA AND ANALYSIS

Maps as Numbers: Data Models

Lecture 2: GIS Data Sources, Data Types and Representation. GE 118: INTRODUCTION TO GIS Engr. Meriam M. Santillan Caraga State University

Chapter 9. Attribute joins

View-dependent fast real-time generating algorithm for large-scale terrain

Algorithms for GIS. Spatial data: Models and representation (part I) Laura Toma. Bowdoin College

CONSISTENT LINE SIMPLIFICATION BASED ON CONSTRAINT POINTS

NOWPAP. Northwest Pacific Action Plan. United Nations Environment Programme

THE STUDY FOR MATCHING ALGORITHMS AND MATCHING TACTICS ABOUT AREA VECTOR DATA BASED ON SPATIAL DIRECTIONAL SIMILARITY

Voronoi Diagrams in the Plane. Chapter 5 of O Rourke text Chapter 7 and 9 of course text

DESIGN AND IMPLEMENTATION OF TOURIST WEBGIS BASED ON J2EE

Instructor: Paul Zeitz, University of San Francisco

EDGE EXTRACTION ALGORITHM BASED ON LINEAR PERCEPTION ENHANCEMENT

PUBLIC WORKS. 1oo. DiEital Fee Schedules. Effective January 1, 2008

Advances in geographic information systems and remote sensing for fisheries and aquaculture

A Point in Non-Convex Polygon Location Problem Using the Polar Space Subdivision in E 2

4th Annual International Conference on Material Science and Engineering (ICMSE 2016)

A COMPETITION BASED ROOF DETECTION ALGORITHM FROM AIRBORNE LIDAR DATA

ORGANIZING SPATIO-TEMPORAL DATA WITH MUTI-BASE-STATES AND MULTI- CLASSES DELTA FILES

Using analytical tools in ArcGIS Online to determine where populations vulnerable to flooding and landslides exist in Boulder County, Colorado.

Week 8 Voronoi Diagrams

An Improved Frequent Pattern-growth Algorithm Based on Decomposition of the Transaction Database

INCREASING CLASSIFICATION QUALITY BY USING FUZZY LOGIC

The design and implementation of TPC encoder and decoder

3D SPATIAL DATA MODEL BASED ON QUASI TRI-PRISM VOLUME AND ITS APPLICATION IN SUBSURFACE ENGINEERING

A DATA DRIVEN METHOD FOR FLAT ROOF BUILDING RECONSTRUCTION FROM LiDAR POINT CLOUDS

An Application of Genetic Algorithm for Auto-body Panel Die-design Case Library Based on Grid

DATA MODELS IN GIS. Prachi Misra Sahoo I.A.S.R.I., New Delhi

A new grid-cell-based method for error evaluation of vector-to-raster conversion

An Improved KNN Classification Algorithm based on Sampling

Exercise 13. Accessing Census 2000 PUMS Data

Graphs Definitions. Gunnar Gotshalks. GraphDefinitions 1

An Improved Pre-classification Method for Offline Handwritten Chinese Character Using Four Corner Feature

v Scatter Data TINs SMS 12.3 Tutorial Requirements Scatter Module Map Module Time minutes Prerequisites None Objectives

SMS v D Summary Table. SRH-2D Tutorial. Prerequisites. Requirements. Time. Objectives

Working with International Census Data in GIS

Creating a Microdata Extract

Vector Data. James Frew ESM 263 Winter

Introduction to Spatial Database Systems. Outline

Image segmentation based on gray-level spatial correlation maximum between-cluster variance

Transcription:

CO-041 AUTOMATIC DIVISION OF CENSUS DISTRICT BASED ON CONSTRAINT DELAUNAY TRIANGULATION LIU D., MA W., CHENG J. Chinese Academy of surveying and Mapping, BEIJING, CHINA ABSTRACT Division of census district is an import step in population census, which costs a lot of man power, finance and resource. Based on the theory and technology of delannay triangulation dividing, the census district is automatically divided with line feature as constraint condition. The paper introduces the characteristic of delaunay triangulation, discusses the technologies, measures and processes of census district division. The application example is given finally. Key words: population census; census district; delaunay triangulation 1 INTRODUCTION Population census is held in a country in the uniform method, item, question form and time, asking everyone living and working on the country to information about their personal lives [1]. The population census is taken once every 10 years in China and the sixth nationwide census started in November 1, 2010. About 90 percent of the people will be asked to fill in an 18-item form, covering their name, sex, ethnic group, household registration, and education; the other 10 percent, chosen randomly, will be asked to fill in a longer 45-question form. In the population census, division of census district is an important step in the work flow of census. Census district is a foundation for organization and implementation of census, reliable basis to ensure the integrity of enumeration area, efficient way for establish a quality control system of census data and a data source to build a population GIS to analysis the census data[2]. Division of census district had been done manually and costs a lot of man power, finance and resource in the previous censuses in China. Because of the difference in their quality, enumerator s map sometimes is hard to accurately depict and position the responsible district for an enumerator and the data source is hard for the further geo-spatial analysis. Therefore, automatic division of census district by digital support has an important meaning in the census process and application of census material. The description and division of census district has different way in different countries. In Japan, regular grid is used to describe the census district, which has a simple structure, is easy to manage but is difficult to convert to other district system precisely, such as political area system or other management area system[3]. In United States, a Tiger(Topological Integrated Geographical Encoding Reference System)is used to match the house address and census question form, to fulfill the task of question form positioning and census district division[4]. Many developing countries is still manually depicts the census map and divides the census district. Many work related to the application of Delaunay Triangulation in the field of surveying and mapping in map generalization and construction of Delaunay Triangulation has been done. Prof. Ai presents a method which applies constrained Delaunay TIN built in street regions to retrieve center-lines and further to generate street network structure. Three kinds of triangles are distinguished and corresponding different center-line extracting ways are offered. The spatial relations among street edges, street junctions and street blocks are described by graph element edge, node and loop. The method also supports to find the matching neighbor between center-lines and street block arcs. The provided data model unified the street network and block polygon [5]. Prof. Guo discusses the algorithm of polygon automatic generalization under digital environment and takes into account the orthogonal characteristics of urban building [6]. Mr. Liu discusses the arithmetic applied Delaunay triangle networks in polygons generalization and punctate objects generalization of land data type, describes the progress and the experimentation result of the arithmetic. He also analyzes and compares the several arithmetic of applying in punctate objects and introduces the realized progress [7]. For the Delaunay triangulation dividing, Mr. Yi gives a method to improve performance of Delaunay triangulation dividing with constraint line. Firstly, it is to generate Delaunay triangulation grid without constraint by parallel algorithm. Secondly, it is to insert new points by getting intersection point of circle defined by the triangulation's three vertices and constraint line [8]. Prof. Li presents a multiple diagonal exchanging algorithm for inserting constraint boundary in constraint delaunay triangulation [9]. 2 METHODS

Based on the theory of delannay triangulation dividing, its characteristics are the area is unique, fully coverage of all area and less impact of one area modification to another area. It proves that the technology is suitable for the dividing of census district. In practice, the boundary of census district is divided by the line feature such as river, road, street, fence, etc, in order for the enumerator to distinguish his responsible enumeration area. The technology of Delaunay Triangulation with constraint condition is introduced for the dividing of census district. Based on the theory and technology of Constraint Delaunay Triangulation, GIS can play an important role in the automatic division of census district. The methods and processes are as follows: (1) Extraction of point data The data for division of census district includes building, administrative boundary, road and railway, river and fence, etc. The building has the attribute of number of household which is obtained in the pre-census. The point data from this feature are the generatrix to create the triangulation network and data form the administrative boundary, road and railway, river and fence are used as the constraint conditions. When the length of line from these points is too long, the side of triangulation will intersect with the original line feature and can not reflect the correct neighborhood relationship of the features (as shown in Figure 1a). In this case, intensification of point in the line is need and the intensified points are used to construct the triangulation network (as shown in Figure 1b). The method is as follow: Suppose the points in polygon as {Pi}, when Li,i+1 > w (w as the average width of street[5], the points in a line must be intensified. The points intensified are {Qk}: X(Qk) = X(Pi) + {[X(Pi+1) X(Pi)] * (k-1)} / (n-1) Y(Qk) = Y(Pi) + {[Y(Pi+1) Y(Pi)] * (k-1)} / (n-1) [1,n],n=2+int( PiPi+1 /w). a. Construction of networkb. Construction of network from original points from intensified points Figure 1 Construction of triangulation network (2) Construction of constraint delannay triangulation network After the point is intensified, triangulation network is constructed based on the technology of delannay triangulation. the triangulation network can be built. The steps are described as follow: 1) Define a elementary polygon contained all points; 2) Select a point from a point set, insert to elementary polygon to form a elementary triangulation network; 3) Insert the next point P, search the triangle contained the point P, join the P and the 3 vertexes of the triangle; 4) Perform the step 3) repeatedly as all points are processed. The data structure is a key issue of delannay triangulation. Considering the retrieve of boundary of census district, the paper design the data structure for the triangulation, vertex and side are as follows: 1) Data structure of triangle vertexes: class t_point { public: double x;

double y; double z; int isroad; int parented t_point(); vitual ~ t_point(); }; 2) Data structure of triangle sides: class t_line { public; long p0; long p1; int usecount; bool friend operator=(t-line line0,t_line line1) t-line(); vitual ~ t_line(); }; 3) Data structure of triangle: class t_tri { public; long lo; long l1; long l2; t_tri(); vitual ~ t_tri(); }; (3) Extraction of area boundary There are 3 situations when area boundary is extracted, which are three vertex to construct a triangle from two different buildings (A class), three vertex to construct a triangle from three different buildings (B class), three vertex to construct a triangle which two point are from the different buildings and one point is from the constraint feature (C class), as shown in Figure 2. The rules and processes are described as follows: 1) A class: join the middle point from two lines connected two buildings; 2) B class: join the center point of triangle and 3 middle points of sides of triangle; 3) C class: join the point in constraint feature and middle point of line connected other 2 points. 4) In other cases, no process is done.

A class triangleb class trianglec class triangle Figure 2 Extraction of area boundary (4) Merge of area After the above processes, the original census district is formed which contained only one building. According as the rule for the division of census district in the sixth national population census of China is about 80 households, In many cases, the original census district must be merged (as shown in Figure 3). The steps and processes are as follows: Loop the all area, for each one: 1) if number of household > 80, no process; 2) if number of household < 80, search the neighbor area and merge but must meet the conditions: (a) no intersection with constraint feature; (b) closer to the number of 80 household. a Before merging b after merging Figure 3 Merge of area 3 EXAMPLE In the test city of Panjin, Liaoning Province in northeast China, a test site for division and mapping of census district of sixth National Population Census, the technology has been processed. The platform for software development is Visual Studio 2005, C++. The program has realized the functions such as input of the vector data, editing and process of data, division of census district, display and print out of enumerator s map, etc. The example of process and result is shown in Figure 4.

(a) Extraction of point data(b) Construction of constraint delannay triangulation network (c) Extraction of area boundary (d) Merge of area Figure 4 example of census district division 4 CONCLUSIONS According to the principle of census district division of sixth National Population Census in China, the paper presents a method of automatic division of census district based on the theory of delaunay triangulation, with the line features such as administrative boundary, road, street, river, fence, etc as constraint conditions. In practice, the method can ensure the no overlay and no miss of enumeration area, as an effective mean to guarantee total coverage of enumeration. It can also eliminate the error in the drawing enumeration map made by subjective carelessness of enumerator. Therefore, it is greatly alleviate the work load of enumerator. The data source is a great help to establishment a Census Geographic Information System, which will broaden the application and elevate potential value of population data. REFERENCES [1] Qiao xiaochun. Research on China Population Census[M]. Chinese Population Publication House, 1995 [2] Cheng gang. An approach on Division of Census District[J]. Study of Population,2002,(3)

[3] Wang zhonglian. Introduction of Japanese Population Census[J]. Study of Japan,1990,(2) [4] Chen wanqing. Introduction of Population Census in the United States[J]. Study of Statistics, 2009,(10) [5] Ai Ting-hua. Extracting Center-lines and Building Street Network Based on Constrained Delaunay Triangulation[J]. ACTA GEODAETICA et CARTOGRAPHICA SINICA,2000,(11) [6] Guo renzhong. Simplification and Aggregation of Building Polygon in Automatic Map Generalization [J]. Journal of Wuhan Technical University of Surveying and Mapping, 2000,(2) [7]Liu xonglin. Delaunay Triangulation Applying in the Polygons Generalization and Punctate Objects Generalization [J]. Journal of Zhengzhou Institute of Surveying and Mapping,2007,(8) [8] Yi faling. Delaunay Triangulation Dividing Optimal Algorithm with Constraint Line[J]. Computer Engineering,2001,(6) [9] Li li-xin. Multiple Diagonal Exchanging Algorithm For Inserting Constrained Boundary In Constrained elaunay Triangulation[J]. CHINESE J.COMPUTERS,1999,(10)