Attribute data input and data display :
Attribute data in GIS, Relational model, Data entry, Manipulation of fields
and attribute data, cartographic symbolization, types of maps, typography,
map design, map production
Spatial Data Concepts:
Introduction to GIS, Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane coordinate systems,
Vector data model, Raster data model
Data Input and Geometric transformation:
Existing GIS data, Metadata, Conversion of existing data, Creating new
data, Geometric transformation, RMS error and its interpretation,
Resampling of pixel values.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.
Spatial Data Concepts: Introduction to GIS,
Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane
coordinate systems, Vector data model, Raster data
model
Data Input and Geometric transformation: Existing
GIS data, Metadata, Conversion of existing data,
Creating new data, Geometric transformation, RMS
error and its interpretation, Resampling of pixel
values.
Attribute data input and data display : Attribute data in
GIS, Relational model, Data entry, Manipulation of
fields and attribute data, cartographic symbolization,
types of maps, typography, map design, map
production
Data exploration: Exploration, attribute data query,
spatial data query, raster data query, geographic
visualization
Vector data analysis: Introduction, buffering, map
overlay, Distance measurement and map manipulation.
Raster data analysis: Data analysis environment, local
operations, neighbourhood operations, zonal
operations, Distance measure operations.
Spatial Interpolation: Elements, Global methods, local
methods, Kriging, Comparisons of different methods
Spatial Data Concepts:
Introduction to GIS, Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane coordinate systems,
Vector data model, Raster data model
Data Input and Geometric transformation:
Existing GIS data, Metadata, Conversion of existing data, Creating new
data, Geometric transformation, RMS error and its interpretation,
Resampling of pixel values.
DEFINITION :
GIS is a powerful set of tools for collecting, storing , retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes
APPLICATION AREAS OF GIS
Agriculture
Business
Electric/Gas utilities
Environment
Forestry
Geology
Hydrology
Land-use planning
Local government
Mapping
11. Military
12. Risk management
13. Site planning
14. Transportation
15. Water / Waste water industry
COMPONENTS OF GIS
DATA INPUT
SPATIAL DATA MODEL
Data Model:
It describes in an abstract way how the data is represented in an information system or in DBMS
Spatial Data Model :
The models or abstractions of reality that are intended to have some similarity with selected aspects of the real world
Creation of analogue and digital spatial data sets involves seven levels of model development and abstraction
SPATIAL DATA MODEL
Conceptual model : A view of reality
Analog model : Human conceptualization leads to analogue abstraction
Spatial data models : Formalization of analogue abstractions without any conventions
Database model : How the data are recorded in the computer
Physical computational model : Particular representation of the data structures in computer memory
Data manipulation model : Accepted axioms and rules for handling the data
SPATIAL DATA MODEL
SPATIAL DATA MODEL
Objects on the earth surface are shown as continuous and discrete objects in spatial data models
Types of data models
Raster data model
vector data models
RASTER DATA MODEL
Basic Elements :
Extent
Rows
Columns
Origin
Orientation
Resolution: pixel = grain = grid cell
Ex: Bit Map Image (BMP),Joint Photographic Expert Group (JPEG), Portable Network Graphics(PNG) etc
RASTER DATA MODEL
VECTOR DATA MODEL
Basic Elements:
Location (x,y) or (x,y,z)
Explicit, i.e. pegged to a coordinate system
Different coordinate system (and precision) require different values
o e.g. UTM as integer (but large)
o Lat, long as two floating point numbers +/-
Points are used to build more complex features
Ex: Auto CAD Drawing File(DWG), Data Interchange(exchange) File(DXF), Vector Product Format (VPF) etc
VECTOR DATA MODEL
RASTER vs VECTORRaster is faster but Vector is corrector
TESSELLATIONS OF CONTINUOUS FIELDS
Triangular Irregular Network: (TIN)
TIN is a vector data structure for representing geographical information that is continuous
Digital elevation model
TIN is generally used to create Digital Elevation Model (DEM)
DIGITAL ELEVATION MODEL
DATA STRUCTURES
Data structure tells about how the data is stored
Data organization in raster data structures
Each cell is referenced directly
Each overlay Is referenced directly
Each mapping unit is referenced directly
Each overlay is separate file with general header
An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.
Spatial Data Concepts: Introduction to GIS,
Geographically referenced data, Geographic, projected
and planer coordinate system, Map projections, Plane
coordinate systems, Vector data model, Raster data
model
Data Input and Geometric transformation: Existing
GIS data, Metadata, Conversion of existing data,
Creating new data, Geometric transformation, RMS
error and its interpretation, Resampling of pixel
values.
Attribute data input and data display : Attribute data in
GIS, Relational model, Data entry, Manipulation of
fields and attribute data, cartographic symbolization,
types of maps, typography, map design, map
production
Data exploration: Exploration, attribute data query,
spatial data query, raster data query, geographic
visualization
Vector data analysis: Introduction, buffering, map
overlay, Distance measurement and map manipulation.
Raster data analysis: Data analysis environment, local
operations, neighbourhood operations, zonal
operations, Distance measure operations.
Spatial Interpolation: Elements, Global methods, local
methods, Kriging, Comparisons of different methods
Also known as geospatial data or geographic information it is the data or information that identifies the geographic location of features and boundaries on Earth, such as natural or constructed features, oceans, and more. Spatial data is usually stored as coordinates and topology, and is data that can be mapped.
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
basic concept of geographic data,GIS and its component,data acquisition ,raster, vector formats,spatial data,topology and data model data output ,GIS applications
Also known as geospatial data or geographic information it is the data or information that identifies the geographic location of features and boundaries on Earth, such as natural or constructed features, oceans, and more. Spatial data is usually stored as coordinates and topology, and is data that can be mapped.
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
basic concept of geographic data,GIS and its component,data acquisition ,raster, vector formats,spatial data,topology and data model data output ,GIS applications
TYBSC IT PGIS Unit II Chapter I Data Management and Processing SystemsArti Parab Academics
Data Management and Processing Systems Hardware and Software Trends Geographic Information Systems: GIS Software, GIS Architecture and functionality, Spatial Data Infrastructure (SDI) Stages of Spatial Data handling: Spatial data handling and preparation, Spatial Data Storage and maintenance, Spatial Query and Analysis, Spatial Data Presentation. Database management Systems: Reasons for using a DBMS, Alternatives for data management, The relational data model, Querying the relational database. GIS and Spatial Databases: Linking GIS and DBMS, Spatial database functionality.
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
Modeling a geo spatial database for managing travelers demandijdms
The geo-spatial database is a new technology in database systems which allow storing, retrieving and
maintaining the spatial data. In this paper, we seek to design and implement a geo-spatial database for
managing the traveler’s demand with the aid of open-source tools and object-relational database package.
The building of geo-spatial database starts with the design of data model in terms of conceptual, logical
and physical data model and then the design has been implemented into an object-relational database. The
geo-spatial database is developed to facilitate the storage of geographic information (where things are)
with descriptive information (what things are like) into the vector model. The developed vector geo-spatial
data can be accessed and rendered in the form of map to create the awareness of existence of various
services and facilities for prospective travelers and visitors.
Similar to Geographical information system unit 3 (20)
Web services basics : What Are Web Services? Types of Web Services Distributed computing infrastructure, overview of XML, SOAP, Building Web Services with JAX-WS, Registering and Discovering Web Services, Service Oriented Architecture, Web Services Development Life Cycle, Developing and consuming simple Web Services across platform
The REST Architectural style : Introducing HTTP, The core architectural elements of a RESTful system, Description and discovery of RESTful web services, Java tools and frameworks for building RESTful web services, JSON message format and tools and frameworks around JSON, Build RESTful web services with JAX-RS APIs, The Description and Discovery of RESTful Web Services, Design guidelines for building RESTful web services, Secure RESTful web services
Developing Service-Oriented Applications with WCF : What Is Windows Communication Foundation, Fundamental Windows Communication Foundation Concepts, Windows Communication Foundation Architecture, WCF and .NET Framework Client Profile, Basic WCF Programming, WCF Feature Details. Web Service QoS
What Is AI: Foundations, History and State of the Art of AI.
Intelligent Agents: Agents and Environments, Nature of Environments, Structure of Agents.
Problem Solving by searching: Problem-Solving Agents, Example Problems,Searching for Solutions, Uninformed Search Strategies, Informed (Heuristic) Search Strategies, Heuristic Functions.
Learning from Examples: Forms of Learning, Supervised Learning, Learning Decision Trees, Evaluating and Choosing the Best Hypothesis, Theory of Learning, Regression and Classification with Linear Models, Artificial Neural Networks, Nonparametric Models, Support Vector Machines, Ensemble Learning, Practical Machine Learning
Learning probabilistic models: Statistical Learning, Learning with Complete Data, Learning with Hidden Variables: The EM Algorithm. Reinforcement learning: Passive Reinforcement Learning, Active Reinforcement Learning, Generalization in Reinforcement Learning, Policy Search, Applications of Reinforcement Learning.
Unit-I Conventional Software Management: The waterfall model, conventional
software Management performance.
Evolution of Software Economics: Software Economics, pragmatic software
cost estimation.
Improving Software Economics: Reducing Software product size, improving
software processes, improving team effectiveness, improving automation,
Achieving required quality, peer inspections.
10
Lectures
Unit-II The old way and the new: The principles of conventional software
Engineering, principles of modern software management, transitioning to an
iterative process.
Life cycle phases: Engineering and production stages, inception, Elaboration,
construction, transition phases.
Artifacts of the process: The artifact sets, Management artifacts, Engineering
artifacts, programmatic artifacts.
Model based software architectures: A Management perspective and technical
perspective.
10
Lectures
Unit-III Work Flows of the process: Software process workflows, Iteration workflows.
Checkpoints of the process: Major mile stones, Minor Milestones, Periodic
status assessments.
Iterative Process Planning: Work breakdown structures, planning guidelines,
cost and schedule estimating, Iteration planning process, Pragmatic planning.
10
Lectures
Unit-IV Project Organizations and Responsibilities: Line-of-Business Organizations,
Project Organizations, evolution of Organizations.
Process Automation: Automation Building blocks, The Project Environment.
10
Lectures
Unit-V Project Control and Process instrumentation: The seven core Metrics,
Management indicators, quality indicators, life cycle expectations, pragmatic
Software Metrics, Metrics automation.
Tailoring the Process: Process discriminants.
10
Lectures
Unit-VI Future Software Project Management: Modern Project Profiles, Next
generation Software economics, modern process transitions.
10
Lectures
An Introduction to Oracle Warehouse Builder: Installation of the
database and OWB, About hardware and operating systems, Installing
Oracle database software, Configuring the listener, Creating the database,
Installing the OWB standalone software, OWB components and
architecture, Configuring the repository and workspaces.
Defining and Importing Source Data Structures: An overview of
Warehouse Builder Design Center, Importing/defining source metadata,
Creating a project, Creating a module, Creating an Oracle Database module,
Creating a SQL Server database module, Importing source metadata from a
database, Defining source metadata manually with the Data Object Editor,
Importing source metadata from files.
Validating, Generating, Deploying, and Executing Objects: Validating,
Validating in the Design Center, Validating from the editors, Validating in
the Data Object Editor, Validating in the Mapping, Editor, Generating,
Generating in the Design Center, Generating from the editors, Generating in
the Data Object Editor, Generating in the Mapping Editor, Deploying, The
Control Center Service, Deploying in the Design Center and Data Object
Editor, The Control Center Manager, The Control Center Manager window
overview, Deploying in the Control Center ,Manager, Executing, Deploying
and executing remaining objects, Deployment Order, Execution order.
ETL: Transformations and Other Operators: STORE mapping, Adding
source and target operators, Adding Transformation Operators, Using a Key
Lookup operator, Creating an external table, Creating and loading a lookup
table, Retrieving the key to use for a Lookup Operator, Adding a Key
Lookup operator, PRODUCT mapping, SALES cube mapping, Dimension
attributes in the cube, Measures and other attributes in the cube, Mapping
values to cube attributes, Mapping measures' values to a cube, Mapping
PRODUCT and STORE dimension values to the cube, Mapping
DATE_DIM values to the cube, Features and benefits of OWB.
Validating, Generating, Deploying, and Executing Objects:
Designing and building an ETL mapping: Designing our staging area,
Designing the staging area contents, Building the staging area table with the
Data Object Editor, Designing our mapping, Review of the Mapping Editor,
Creating a mapping.
Extract, Transform, and Load Basics: ETL, Manual ETL processes,
Staging, To stage or not to stage, Configuration of a staging area, Mappings
and operators in OWB, The canvas layout, OWB operators, Source and
target operators, Data flow operators, Pre/post-processing operators.
Creating the Target Structure in OWB: Creating dimensions in OWB,
The Time dimension, Creating a Time dimension with the Time Dimension
Wizard, The Product dimension, Product Attributes (attribute type),Product
Levels, Product Hierarchy (highest to lowest),Creating the Product
dimension with the New Dimension Wizard, The Store dimension, Store
Attributes (attribute type), data type and size, and (Identifier),Store Levels,
Store Hierarchy (highest to lowest),Creating the Store dimension with the
New Dimension Wizard, Creating a cube in OWB, Creating a cube with the
wizard, Using the Data Object Editor
Designing the Target Structure: Data warehouse design, Dimensional
design, Cube and dimensions, Implementation of a dimensional model in a
database, Relational implementation (star schema),Multidimensional
implementation (OLAP),Designing the ACME data warehouse, Identifying
the dimensions, Designing the cube, Data warehouse design in OWB,
Creating a target user and module, Create a target user, Create a target
module, OWB design objects.
Introduction to Data Warehousing: Introduction, Necessity, Framework
of the datawarehouse, options, developing datawarehouses, end points.
Data Warehousing Design Consideration and Dimensional Modeling:
Defining Dimensional Model, Granularity of Facts, Additivity of Facts,
Functional dependency of the Data, Helper Tables, Implementation manyto-
many relationships between fact and dimensional modelling.
ETL: Transformations and Other Operators: STORE mapping, Adding
source and target operators, Adding Transformation Operators, Using a Key
Lookup operator, Creating an external table, Creating and loading a lookup
table, Retrieving the key to use for a Lookup Operator, Adding a Key
Lookup operator, PRODUCT mapping, SALES cube mapping, Dimension
attributes in the cube, Measures and other attributes in the cube, Mapping
values to cube attributes, Mapping measures' values to a cube, Mapping
PRODUCT and STORE dimension values to the cube, Mapping
DATE_DIM values to the cube, Features and benefits of OWB.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
3. Attribute Data in GIS
Attribute data are stored in tables.
An attribute table is organized by row and column.
Each row represents a spatial feature,
each column describes a characteristics,
and the intersection of a column and a row shows the value of
particular characteristic for a particular feature
WE-IT TUTORIALS (PH:8097071144/55)
LabelID pH Depth Fertility
1 6.8 12 High Row
2 4.5 4.8 Low
Column
4. Relation Model
A database is a collection of interrelated tables in digital format.
There are at least four types of database designs that have been
proposed in the literature:
flat file,
hierarchical,
network, and
relational.
GIS vendors typically use the relational model for database
management. A relational database is a collection of tables, also
called relations, which can be connected to each other by keys.
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5. SSURGO
The Natural Resources Conservation Service (NRCS)
produces the Soil Survey Geographic (SSURGO)
database nationwide
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6. what is meant by
Normalization
Normalization is a process of decomposition, taking a
table with all the attribute data and breaking it down into
small tables while maintaining the necessary linkages
between them
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7. types of relationships among
database tables
onetoone,
onetomany,
manytoone, and
manytomany.
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8. how to Manipulate fields of
Attribute Data in GIS
Manipulation of Fields and Attribute Data
Adding and Deleting Fields
Classification of Attribute Data(grouped)
Computation of Attribute Data(formula)
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9. Cartographic Symbolization
with its various aspects.
use a map symbol to indicate the feature’s location
example, a thick line in red may represent an interstate highway and a
thin line in black may represent a state highway
Use of Color
If maps are black and white (lighter and darker shade is used)
Data Classification(aggregating data and map features)
Equal interval(0110, 1120, 2130, etc)
Equal frequency(class contains the same number of data values)
Mean and standard deviation(above or below the mean)
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10. types of maps in GIS Packages
The general reference map is used for general purposes
The thematic map is also called the special purpose map, because its main
objective is to show the distribution pattern of a theme, such as the
distribution of population densities by county in a state.
A qualitative map uses visual variables that are appropriate for portraying
qualitative data
dot map
choropleth map
graduated symbol map
pie charts
flow map
isarithmic map
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11. role of Typography in GIS?
Map Design with reference to : (a) Layout (b) Visual
Hierarchy?
process of Map Production?
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12. END OF UNIT 3
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