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CE 250 - Introduction to Surveying and Geographic Information Systems eLearning Version Donald J. Leone, Ph.D., P.E. Lecture 3 Introduction What are databases and database management systems (DBMS)? What is a relational data base model? How are databases linked with GIS? How do we get paper maps into the computer? How can we edit and convert data? Databases Spatial Data – “Where things are” Attribute Data – “What things are” Attribute Data – Stored in databases Def: Database – “A set of structured data – usually in table form”, or “ A Collection of related data” Traditional Database Example Traditional Databases Some Problems Duplication of Data High Maintenance Costs Data Sharing Difficulties Lack of Security and Standards Computer Based Databases Different data access methods will be available. Are independent of application. Unnecessary duplication of data – minimized. Access controlled and centralized. Maintaining and Updating relatively easy. Can ask questions - “query” Database Approach Database Data DBMS Database Management System Hotel Ski School Travel Booking Booking Arrangements Application Database Management Systems Functions File Handling/management Adding/deleting/updating records Extraction of data (sorting, querying) Maintenance (security, backup) Application building Data Base Table PIN Owner Address Sale Date Acres Zone Zoning Code P101 Wang 101 Oak St. 1-10-98 1.0 1 Res. P101 Chang 200 Maple St. 1-10-98 1.0 1 Res. P102 Smith 300 Spruce Rd. 10-6-68 3.0 2 Com. P102 Jones 100 Ash St. 10-6-68 3.0 2 Com. P103 Costello 206 Elm St. 3-7-97 2.5 2 Com. P104 300 Spruce St. 7-30-78 1.0 1 Res. Smith Separate Data Tables – A Relational Database PIN Zone Code PIN Owner name Owner name Zone Code Creating a New Table Key Field Joined Table PIN Owner Address P101 Wang 101 Oak St. P101 Chang 200 Maple St. P102 Smith 300 Spruce Rd. P102 Jones 100 Ash St. P103 Costello 206 Elm St. P104 300 Spruce St. Smith Creating New Tables – “The Query” Standard Query Language – SQL Generate New tables Advantages: Completeness, Simplicity Style, Wide Application Disadvantages: Slow, Difficult to implement Can’t Handle geographic concepts, i.e. “near to” Parcel Table PIN Sale Date P101 1-10-98 1.0 1 P102 10-6-68 3.0 2 P103 3-7-97 2.5 2 P104 7-30-78 1.0 1 Acres Zone Code “Which Parcels (PINS) have 2 or more acres?” Create a New Table Using SQL “Acres” =>2.0 Query: Result: PIN Sale Date Acres Zone Code P102 10-6-68 3.0 2 P103 3-7-97 2.5 2 Creating a Database 1. Data Investigation – Fact finding. 2. Data Modeling – Relationships between entities and attributes – Define Tables. 3. Database Design – Fit data modeling to software at hand. 4. Database Implementation – Filling in the actual data. Data Modeling Entity Attribute Modeling (EAM) 1. Identification of Entities 2. Identification of the Relationship between entities (1:1, 1:M, M:1, M:N) 3. Identification of the Attributes of the entities 4. Development of the Tables EAM for Ski Resort 1. Entitles – Hotels, Travel Companies, Ski Schools, Visitors 2. Relationships a) Many visitors stay at One hotel (M:1) b) One Travel Co, organizes for Many visitors (1:M) c) One Ski School teaches Many visitors (1:M) d) Different Travel Co.s may use Different Ski Schools (M:N) EAM Diagram N d b a) Many visitors stay at One hotel (M:1) b) One Travel Co, organizes for Many visitors (1:M) c) One Ski School teaches Many visitors (1:M) d) Different Travel Co.s may use Different Ski Schools (M:N) c a Attributes of the Entities HOTEL (Hotel ID, Name, Other Attributes) TRAVEL CO. (Travel Co. ID, Travel Co. Name, Other Attributes) SKI SCHOOL (Ski School ID, Ski School Name, Other Attributes) VISITOR (Visitor ID, Visitor Name, Hotel ID, Travel Co. ID, Ski School ID, Other Attributes) LINK (Travel Co. ID, Ski School ID) Ski Resort Tables Linking Spatial and Attribute Data Database Applications Single User/PC Simple Software Large Computers Large Corporate Databases Control Access Manage Data Security Different Sites Little Grey Cells Quiz SQL stands for standard question link. T or F One of the functions of a DBMS is to allow several applications access to the data. T or F Give one advantage of a computer database over a “traditional” database. Break! Getting the Data Into The Computer Data Input (Encoding) and Editing ANALOG What is data encoding? DIGITAL How are paper maps digitized? How are paper maps scanned? Methods of Data Editing and Conversion Maps Satellite Data Digitizing Digital Data Scanning Data Encoding Tabular Data Data Transfer Soft Ideas Key Coding Data Capture Methods Editing/Cleaning Re-Projection Data Editing Generalization Edge Matching and Rubber Sheeting Layering Integrated GIS Database Data Encoding Methods Digitizing Tracing over a map with a cursor. Mechanical Device with a Human Operator. Most errors operator induced. Produces A Vector Map. Data Encoding Methods Scanning Some problems with scanning (automatic digitizing) Distortion. Automatic scanning of unwanted images. Produces a raster image- can be vectorized with some problems. Amount of editing required to produce suitable spatial data. University of Hartford Aerial Photo Sports Center HJG Center UT Hall Ground Truthing Points Scanning Original Paper Map Scanned Image Data Encoding Methods Electronic Data Transfer What data exist? How much they cost? What format will it be in? Pay off – Considerable time and effort saved! Data Editing Methods Detecting and Correcting Errors Missing or Duplicate Features Mislocated Features Missing or Duplicated Labels Unwanted Results of Digitizing or Scanning Noise Errors in Vector Data Errors in Raster Data Noise Original “noisy” data 3 x 3 Mean Filter 9 x 9 Mean Filter Producing a Common Reference Re-Projection Transformation Generalization Producing a Common Reference Re-Projection All data needs to be referenced to the same projection. Trying to Overlay Different Projections Cylindrical Conic Producing a Common Reference Re-Projection All data needs to be referenced to the same projection. Transformation All data needs to have the same origin. Producing a Common Reference Re-Projection All data needs to be referenced to the same projection. Transformation All data needs to have the same origin. Generalization All data needs to be set to the same scale. Remaining Problems After Re-Projection, Transformation, and Generalization Edge Matching Remaining Problems After Re-Projection, Transformation, and Generalization Rubber Sheeting An Integrated Database Ski Resort Example Layer Name Source Data Model Infrastructure Scanned – 1:5000 Raster Hotels Survey Data Vector Ski Schools Survey Data Vector Weather Stations GPS Data Vector An Integrated Database Ski Valley Example Layer Name Source Data Model Roads Digitized 1:25000 Vector Ski Trails Digitized Aerial Photos Vector Ski Resort Boundary Digitized 1:25000 Vector Topography File Transfer 1:25000 DTM Vector/Raster Land Use Satellite Image Raster Summary What are databases and data base management systems (DBMS)? What is a relational data base model? How are databases linked with GIS? How do we get paper maps into the computer? How can we edit and convert data? What’s Next Up to now – Data Formation Data Analysis – Decision Making