城市空间信息技术 第十章 数据探查 胡嘉骢 不动产学院 博士 副教授 城市规划系主任 手机 : 13411361496 ( 611496 ) QQ: 4519210.

Slides:



Advertisements
Similar presentations
Chapter 2 Exploring Data with Graphs and Numerical Summaries
Advertisements

Center for Modeling & Simulation.  A Map is the most effective shorthand to show locations of objects with attributes, which can be physical or cultural.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Lecture Slides Elementary Statistics Eleventh Edition and the Triola.
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Geographic Information Systems Applications in Natural Resource Management Chapter 8 Combining and Splitting Landscape Features, and Merging GIS Databases.
GIS for Environmental Science
From portions of Chapter 8, 9, 10, &11. Real world is complex. GIS is used model reality. The GIS models then enable us to ask questions of the data by.
Concepts of Database Management Sixth Edition
Data Storage and Processing GIS Topics and Applications.
Basic Statistical Concepts
Statistics Psych 231: Research Methods in Psychology.
BASIC SPATIAL ANALYSIS TOOLS IN A GIS
Measures of Central Tendency
Basics: Notation: Sum:. PARAMETERS MEAN: Sample Variance: Standard Deviation: * the statistical average * the central tendency * the spread of the values.
FOUNDATIONS OF NURSING RESEARCH Sixth Edition CHAPTER Copyright ©2012 by Pearson Education, Inc. All rights reserved. Foundations of Nursing Research,
Attribute databases. GIS Definition Diagram Output Query Results.
What Geoprocessing? Geoprocessing is the processing of geographic information. Commonly used to describe a process when geographic objects are manipulated.
Dr. David Liu Objectives  Understand what a GIS is  Understand how a GIS functions  Spatial data representation  GIS application.
Intro. To GIS Lecture 6 Spatial Analysis April 8th, 2013
@ 2007 Austin Troy. Geoprocessing Introduction to GIS Geoprocessing is the processing of geographic information. Perform spatial analysis and modeling.
Basic Spatial Analysis
How to Analyze Data? Aravinda Guntupalli. SPSS windows process Data window Variable view window Output window Chart editor window.
© 2005 The McGraw-Hill Companies, Inc., All Rights Reserved. Chapter 12 Describing Data.
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
Preparing Data for Analysis and Analyzing Spatial Data/ Geoprocessing Class 11 GISG 110.
Attribute Data in GIS Data in GIS are stored as features AND tabular info Tabular information can be associated with features OR Tabular data may NOT be.
Applied Cartography and Introduction to GIS GEOG 2017 EL
1.1 Displaying Distributions with Graphs
Applied Cartography and Introduction to GIS GEOG 2017 EL
1 1 ISyE 6203 Radical Tools Intro To GIS: MapPoint John H. Vande Vate Spring 2012.
Descriptive Statistics Descriptive Statistics describe a set of data.
Data Exploration Chapter 9. Introduction  Where to begin?  Data exploration is data-centered query and analysis  Better understand the data and provide.
Introduction to ArcGIS for Environmental Scientists Module 2 – Fundamentals Chapter 7 – Queries.
Why Is It There? Getting Started with Geographic Information Systems Chapter 6.
Business Statistics: Communicating with Numbers By Sanjiv Jaggia and Alison Kelly McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc.
Chapter 8. ATTRIBUTE DATA INPUT AND MANAGEMENT
Chapter 2 Describing Data.
Lecture 2: Data Exploration Jianfei Chen School of Geographical Sciences GuangZhou University GunagZhou, China
Data Queries Selecting features in ArcMap Data queries  Important part of a GIS project Can be a part of your data preparation or final analysis  Data.
Descriptive Statistics Descriptive Statistics describe a set of data.
Chapter 3 Data Description Section 3-3 Measures of Variation.
Queries Select by Attribute Select by Location. What is a Query? A query extracts information from a data table for further use –Once extracted you can:
Copyright © 2006 by Maribeth H. Price 6-1 Chapter 6 Queries.
CHAPTER 11 VECTOR DATA ANALYSIS 11.1 Buffering
Query and Reasoning. Types of Queries Most GIS queries will select spatial features Query by Attribute (Select by Attribute) –Structured Query Language.
MMSI – SATURDAY SESSION with Mr. Flynn. Describing patterns and departures from patterns (20%–30% of exam) Exploratory analysis of data makes use of graphical.
NR 143 Study Overview: part 1 By Austin Troy University of Vermont Using GIS-- Introduction to GIS.
Mr. Magdi Morsi Statistician Department of Research and Studies, MOH
Exploratory Spatial Data Analysis (ESDA) Analysis through Visualization.
Selecting features in ArcMap
Chapter 6: Interpreting the Measures of Variability.
Lecture 7 Basic GIS Analysis Operations
Definition of Spatial Analysis
WFM 6202: Remote Sensing and GIS in Water Management © Dr. Akm Saiful IslamDr. Akm Saiful Islam WFM 6202: Remote Sensing and GIS in Water Management Dr.
CENTENNIAL COLLEGE SCHOOL OF ENGINEERING & APPLIED SCIENCE VS 361 Introduction to GIS SPATIAL OPERATIONS COURSE NOTES 1.
1 By maintaining a good heart at every moment, every day is a good day. If we always have good thoughts, then any time, any thing or any location is auspicious.
Why Is It There? Chapter 6. Review: Dueker’s (1979) Definition “a geographic information system is a special case of information systems where the database.
Applied Cartography and Introduction to GIS GEOG 2017 EL Lecture-5 Chapters 9 and 10.
CHAPTER 10 DATA EXPLORATION 10.1 Data Exploration Box 10.1 Data Visualization Descriptive Statistics Box 10.2 Descriptive Statistics Graphs.
Exploratory Data Analysis
GIS Institute Center for Geographic Analysis
Descriptive Statistics:
Review- vector analyses
Research Statistics Objective: Students will acquire knowledge related to research Statistics in order to identify how they are used to develop research.
GIS Lecture: Geoprocessing
GIS Institute Center for Geographic Analysis
Welcome!.
Vector Geoprocessing.
GIS Institute Center for Geographic Analysis
Presentation transcript:

城市空间信息技术 第十章 数据探查 胡嘉骢 不动产学院 博士 副教授 城市规划系主任 手机 : ( ) QQ:

2 CHAPTER 11 DATA EXPLORATION 11.1 Data Exploration 数据探查 11.2 Attribute Data Query 属性数据查询 11.3 Spatial Data Query 空间数据查询 11.4 Raster Data Query 栅格数据查询 11.5 Geographic Visualization 地理可视化

3 CHAPTER 11 DATA EXPLORATION Beginning of GIS analysis What do you do with a database of dozens of layers and hundreds of attributes? Data exploration allows you to examine trends, focus on relationships Better understand data Link maps, graphs, and tables

Data Exploration Exploratory data analysis –Statistical analysis Dynamic graphics Data visualization –Finding Gestalt 完形 (finding patterns and properties in a data set) –Posing (形成) queries –Making comparisons

Descriptive Statistics Summarize values of a data set –Range –Median –Mean –Mode –Quantile analysis –Variance –Standard deviation –Z score GIS packages offer descriptive statistics

Graphs Visual display of data Numerous possibilities

7 Figure 11.1 A line graph. 折线 图

8 Figure 11.2 A histogram. 柱状图

9 Figure 11.3 A cumulative distribution graph. 累积 分布状况图

10 Figure 11.4 A scatterplot ( 散点 图 ) plotting % persons 18 years old in 2000 against % population change, 1990–2000. A weak positive relationship, with a correlation coefficient of 0.376, is present between the two variables.

11 Figure 11.5 A bubbleplot showing % population change, 1990–2000, along the x- axis; % persons under 18 years old in 2000 along the y-axis; and state population in 2000 by the bubble size Graphs

12 Figure 11.6 A boxplot based on the % population change, 1990– 2000, data set.

13 Figure 11.7 Boxplot (a) suggests that the data values follow a normal distribution. Boxplot (b) shows a positively skewed distribution with a higher concentration of data values near the high end. The x’s in (b) may represent outliers, which are more than 1.5 box lengths from the end of the box. Boxplot (c) shows a negatively skewed distribution with a higher concentration of data values near the low end.

14 Figure 11.8 A QQ plot plotting % population change, data value against the standardized value from a normal distribution Graphs

15 Figure 11.9 A 3-D plot showing annual precipitation at 105 weather stations in Idaho. A north to south decreasing trend is apparent in the plot.

Dynamic Graphics Graphs displayed in multiple and dynamically linked windows Directly manipulate data points –Pose query in one window and get response in another window Multiple linked windows optimal framework for posing queries

17 Brushing Figure The scatterplot on the left is dynamically linked to the map on the right. The “brushing” of two data points in the scatterplot highlights the corresponding states (Washington and New Mexico) on the map.

18 Other Dynamic Graphic Manipulation Methods Rotation Deletion Transformation

Data Exploration and GIS Similar to exploratory data analysis in statistics, with tow differences –In GIS it involves both spatial and attribute data –Media for data exploration in GIS involves maps and map features

Attribute Data Query Search attribute data in order to retrieve a data subset Selected subset can be examined in a table, displayed in charts, or linked to map features Expressions which must be interpretable by the GIS

SQL (Structured Query Language) Data query language designed for relational databases Designed by IBM in the 1970s and used by many commercial database management systems

22 SQL Structure (Syntax) select from where select keyword selects fields from selects tables where specifies the condition or criterion for data query

23 Figure PIN relates the owner and parcel tables and allows use of SQL with both tables SQL

24 SQL Examples Queries sale date of parcel coded P101 select Parcel.Sale_date from Parcel where Parcel.PIN = ‘P101’

25 SQL Examples Queries parcels larger than 2 acres that are zoned commercial select Parcel.PIN from Parcel where Parcel.Acres > 2 AND Parcel.Zone_code = 2

26 SQL Examples Queries sale date of parcel owned by Costello select Parcel.Sale_date from Parcel, Owner where Parcel.PIN = Owner.PIN AND Owner_name = ‘Costello’ This query involves two tables which must be joined first

Query Expressions where expression contains Boolean expressions and Boolean connectors

28 Boolean Expressions Contains two operands and a logical operator Parcel.PIN = ‘P101’ Operators include =,, >=,

29 Boolean Connectors AND, OR, XOR, NOT Used to connect two or more expressions

30 Figure The shaded portion represents the complement of data subset A (top), the union of data subsets A and B (middle), and the intersection of A and B (bottom).

Type of Operation Select a subset and divide the data into two groups –Those containing the selected records –Those containing the unselected records Three types of operations –Add more records –Subtract records –Select smaller subset

32 Figure Three types of operation may be performed on the subset of 40 records: add more records to the subset (+2), remove records from the subset (-5), or select a smaller subset (20).

Examples of Query Operations Select a data subset and add more records to it Select a data subset and switch selection Select a data subset and select a smaller subset from it

Relational Database Query Relational database often consists of many tables. A relational database query selects overlapping records from all tables Must understand the structure of the database Can either join or relate the tables

35 Figure The keys relating three dBASE files in the MUIR database and the soil attribute table.

Spatial Data Query Retrieving data subset from a layer by working directly with features Select features using cursor, graphic, or spatial relationship between features. Results can be displayed on a map, linked to records in a table, displayed in charts, or saved as a new data set for further processing

Feature Selection by Cursor Pointing and selecting or by dragging a box around the map features

Feature Selection by Graphic Uses a graphic, such as a circle, box, line or polygon to select features that fall inside or are intersected by the graphic Examples: selecting restaurants within a one- mile radius of a hotel, selecting land parcels that intersect a proposed highway, or finding owners of land parcels within a proposed nature reserve

39 Figure Select features by a circle centered at Sun Valley.

Feature Selection by Spatial Relationship Select features based on their spatial relationship to other features In same layer or in different layers Containment, intersect, proximity

41 Containment Select features that fall completely within features for selection Schools within a particular county, state parks within a particular state

42 Intersect Select features that intersect other features Selecting land parcels that intersect a proposed road, urban areas that intersect a fault line

43 Proximity Select features within a specified distance of other features State parks within ten miles of an interstate highway Adjacency - when features to be selected and selection features share common boundary

Combining Attributes and Spatial Data Queries When data exploration requires both attribute and spatial query Gas stations within one mile of freeway exits and have an annual revenue exceeding $2 million

Raster Data Query Concept and some methods same as for vector data query Practical differences

Query by Cell Value Operand (运算对象) is raster itself rather than a field, as in vector query Boolean statement to separate cells that satisfy the query statement from those that do not

47 Figure Raster data query: slope = 2 and aspect = 1. Selected cells are coded 1 and others 0 in the output raster.

Query by Select Features Query by using feature such as points, circles, boxes, or polygons

Geographic Visualization Cartographic visualization Using maps to process visual information Data classification, spatial aggregation, map comparison

Data Classification Groups based on statistics

51 Figure Two classification schemes: above or below the national average (a), and mean and standard deviation (SD) (b).

Spatial Aggregation Groups data spatially

53 Figure Two levels of spatial aggregation: by state (a), and by region (b).

Map Comparison Compare data from different layers to examine relationships

55 Figure An example of map comparison. Deer relocations tend to be concentrated along the clear-cut/old forest edge.

56 Other Options Place all layers on a screen and view them one at at time Use set of adjacent views Use map symbols to show multiple data sets

57 Figure A bivariate map: (1) rate of unemployment in 1997, either above or below the national average, and (2) rate of income change, 1996–1998, either above or below the national average.

谢 谢!