Training workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for the (SADC)...

Training workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for the (SADC)

Fundamentals of Geographic Information System (GIS)

WMO/FAO Training Workshop on GIS and Remote Sensing Applications in Agricultural

Meteorology for the SADC

Thelma A. Cinco

Senior Weather Specialist ,PAGASA Senior Weather Specialist ,PAGASA Resource Person Resource Person

PhilippinesPhilippines


1. Overview of GIS• Definition of GIS• Objectives and Potential of GIS

2. Components of GIS• Hardware,Software,Data,Method,Liveware

3. Functions/Task of GIS • Data Input:Data Model,• Data Management:Relational Database• Data quality,Map Scale & Accuracy/Errors• Data analysis: Queries & Spatial Analysis

4. Application of GIS

Outline


What is GIS?

• No consensus on the definition

• However, there is consensus that GIS includes the following major elements:– hardware/software– database– applications/infrastructure


What is GIS?• A GIS is a specific information system applied to

geographic data and ;• is mainly referred to as a system of hardware,

software, personnel and procedures;• designed to support capture, management,

manipulation, analysis, modeling and display of spatially referenced data for solving complex planning and management problems [Burroughs, 1986; NCGIA, 1990].


Table 1-1. Alternative Names of GIS Multipurpose geographical data system Multipurpose input land use system Computerized geographical information system System for handling natural resources inventory data Geo-information system Spatial information system Land resource information system Spatial data management and comprehensive analysis system Planning information system Resource information system Natural resource management information system Spatial data handling system Geographically referenced information system Environment information system AGIS - Automated geographical information system Multipurpose cadastre Land information system AM/FM - Automated mapping and facilities management


GIS OBJECTIVES• Maximize the efficiency of planning and decision

making• Provide efficient means for data distribution and

handling• Elimination of redundant data base - minimize

duplication• Capacity to integrate information from many

sources• Complex analysis/query involving geographical

referenced data to generate new information.


• Powerful tools for addressing geographical /environmental issues

• Allows us to arrange information about a location as a set of maps

• Displaying information about one characteristic of the region

• Needs a location reference system (such as latitude and longitude)

Geographic Information System (GIS)


Potential for GISOnce a GIS is implemented, the following benefits

are expected.• geospatial data are better maintained in a standard

format • revision and updating are easier• geospatial data and information are easier to search,

analyze and represent• more value added product• geospatial data can be shared and exchanged freely• productivity of the staff is improved and more

efficient• time and money are saved• better decisions can be made


The questions that a GIS is required to answer are mainly as follows :• What is at.....? (Locational question ; what exists at a

particular location) • Where is it.....? (Conditional question ; which locations

satisfy certain conditions) • How has it changed......? (Trendy question ; identifies

geographic occurrence or trends that have changed or in the process of changing)

• Which data are related .....? (Relational question : analyzes the spatial relationship between objects of geographic features)

• What if.......? (Model based question ; computers and displays an optimum path, a suitable land, risky area against disasters etc. based on model)


Components of GIS


Components of GIS :Hardware

• Input devices (Keyboard, digitizing tablet, scanner)

• Central Processing Unit (Pentium, AMD, Sun SPARC)

• Storage devices (Tape drives, floppy drives, hard disks)

• Output devices (Monitor, printer, plotter)


Components of GIS:Key software components

• Tools for the input and manipulation of geographic information

• A database management system (DBMS)

• Tools that support geographic query, analysis, and visualization

• A graphical user interface (GUI) for easy access to tools


manifold


Components of GIS: GIS Data

• Base Maps – include streets, highways, boundaries for census, postal, and political areas, rivers and lakes, parks and landmarks; place names

• Environmental maps - include data related to the environment, weather, environmental risk, satellite imagery, topography, and natural resources.

• Socio-economic data - include data related to census/demography, health care, real state, telecommunications, emergency preparedness, crime, business establishments, and transportation.


Base MapSocio-economic Maps

and Data

Environmental Maps and Data

Other Maps andData


Components of GIS:Liveware

• GIS Manager• GIS Specialist• GIS Technician• GIS Analyst• Computer Programmer• Data Encoder• Information Systems Analyst• Information Technology Officer• Engineer• Planning Officer


Components of GIS: Procedures/Methods

• Well-designed plan

• Business rules

• Models and operating practices unique to each organization


Functions/Tasks of GIS

• Data Input

• Data Management

• Data Analysis and Manipulation

• Data Display/Visualization


Functions/Tasks of GIS:Data Input

• The procedure of encoding data into a computer-readable form and writing the data to the GIS database.

• Data input includes three major steps (the latter two steps are also called data preprocessing):

– Data capture – Editing and cleaning – Geo-coding


Functions/Tasks of GIS: Data Input

• Keyboard entry

• Manual digitizing (e.g., tablet, on-screen)

• Scanning


Geographic Data Organized into Layers


Data Input :Data Sources for GIS

• maps

• aerial photos

• satellite images

• technical descriptions

• GPS data


Data Input : Geographic Data Characteristics

• Geographic data contains four integrated components, namely, location, attribute, spatial relationship and time.

• Geographic data include those which are spatially referenced.

• A GIS includes operations which support spatial analysis.


Data Input: Geographic Data Characteristics

• Spatial data and their attributes are linked (seamless)– By their

geographic location

– By unique identifiers


Data Input: Kinds of Data GIS Handles• Spatial data

– usually translated into simple objects: points, lines, areas and grids (pixels).

– represented as maps.– Example: a parcel of land

• Attribute data (Non-spatial or Aspatial Data)– are descriptive information about specified spatial

objects.– often have no direct information about the spatial

location but can be linked to spatial objects they describe.

– Usually organized in tables– Example: the owner of a parcel of land


Data Input: Kinds of Data GIS Handles

• Identify if spatial(graphical) or non-spatial(textual)– This building

– The color of this building

– The people within this building

– The name of this building

– Rizal Park

– Botswana Road

– Gaborone

– Population of Botswana


Data Input: Identifiers

• Enable both spatial and attribute data to be stored separately but accessed together.

• Identifiers are– Unique values - usually integers– Stored as part of the spatial data structure - as a

numeric value (i.e., system-generated ID)– Stored as part of the attribute data structure - as

a field in a table


Data Input: Data Model

Conversion of real world geographical variation into discrete objects is done through data models. It represents the linkage between the real world domain of geographic data and computer representation of these features.

• Two major categories of spatial data representation in GIS: raster and vector.– Raster approach: cells

– Vector approach: points, lines, and polygons


Raster

Vector

Real World


Raster Data

• Divides the entire study area into a regular grid of cells

• Each cell contains a single value

• Is space-filling since every location in the study area corresponds to a cell in the raster.

• Raster data can be imagined as collection of cells organized like a matrix.


Database/Internal Structure

ncols 15nrows 16xllcenter .5 yllcenter .5cellsize 11 1 1 1 1 1 2 2 2 2 2 3 3 3 31 1 1 1 1 1 2 2 2 2 3 3 3 3 31 1 1 1 1 1 2 2 2 3 3 3 3 3 31 1 1 1 1 2 2 2 2 3 3 3 3 3 31 1 1 1 1 2 2 2 2 2 3 3 3 3 31 1 1 1 2 2 2 2 2 3 3 3 3 3 31 1 1 2 2 2 2 2 3 3 3 3 3 3 31 1 1 1 1 1 2 2 2 2 3 3 3 3 31 1 6 6 6 6 2 4 4 4 3 3 3 5 56 6 6 6 6 6 4 4 4 4 4 4 5 5 56 6 6 6 6 6 4 4 4 4 4 5 5 5 56 6 6 6 6 6 4 4 4 4 4 5 5 5 56 6 6 6 6 4 4 4 4 4 4 5 5 5 56 6 6 6 6 6 4 4 4 4 5 5 5 5 56 6 6 6 6 4 4 4 4 4 5 5 5 5 56 6 6 6 4 4 4 4 4 4 5 5 5 5 5

Data SummaryVisual Representation

RASTER DATA


Vector Data Model

• Represented by lines, points, and polygons.

• Fundamental primitive is a point

• Points are stored as x,y coordinates and represent features as having no dimension.

• Objects are created by connecting points with straight lines (or arcs)

• Areas are defined by sets of lines


Database/Internal Structure

Points

1 2.4 2.82 2.7 2.9

. . .

. . .

. . .

Lines

1 (2.4 2.8),(3.1,2.7),(3.5, 1.3),....... 2 (2.7,2.9),...................

. . .

. . .

. . .

Polygons

1 (2.4 2.8),(3.1,2.7),(3.5, 1.3),.......(2.4 2.8) ..........

..........

Data Summary

Visual Representation

Vector Data


Format Issues

• Most GIS applications can utilize both vector and raster formats, and/or they can convert between the two

• Converting from vector to raster is easy;

• Converting from raster to vector is difficult


Industry-Standard Formats

• Standard vector GIS formats include:– DLG, shape files, TIGER files (preserve

topology)

• Standard raster GIS formats include:– .JPG, .TIF, GeoTIFF (georeferenced TIF

image), other digital image formats, and DEMs (which are georeferenced)


Comparison of Raster and Vector Data Models.

RASTER MODEL VECTOR MODEL Advantages: Advantages:

1.It is a simple data structure. 1.It provides a more compact data structure than the raster model.

2.Overlay operations are easily and efficiently 2.It provides efficient encoding of topology, and as a result, implemented. more efficient implementation of operations that require

topological information, such as network analysis 3.High spatial variability is efficiently represented 3.The vector model is better suited to supporting graphics. in a raster format. that closely approximate hand-drawn maps. 4.The raster format is more or less required for efficient manipulation and enhancement of digital images.

Disadvantages: Disadvantages: 1.The raster data structure is less compact. 1.It is a more complex data structure than a simple raster. 2.Topological relationships are more difficult to represent. 2.Overlay operations are more difficult to implement. 3.The output of graphics is less aesthetically pleasing 3.The representation of high spatial variability is inefficient. because boundaries tend to have a blocky appearance 4.Manipulation and enhancement of digital images cannot rather than the smooth lines of hand-drawn maps. This be effectively done in the vector domain. can be overcome by using a very large number of cells, but may result in unacceptably large files.

Source: Aronoff, S., 1989. Geographical Information Systems: A Management Perspective, WDL Publications, Ottawa.


Vector Representation of Real World Objects

• The representation of real world objects on a map as points, lines and polygons is known as abstraction.

• In abstraction, the data are structured to be amenable to computer storage/retrieval and manipulation.

• Abstraction is done based on the requirements of a specific application.


Vector Representation of Real World Objects

• Building– Represented by polygon in 1:500 cadastral map– Represented by point in 1:50,000 topographic

map

• Road– Represented by polygon in 1:500 cadastral map– Represented by line in 1:50,000 topographic

map


Layers and coverages


Geodetic Control Network

Digital Elevation Model

Orthorectified Image

Roads

Water Features

Political Boundaries


Data Management

• A collection of non-redundant data which can be shared by different application systems is known as a database.

• Several layers of geographic data covering the same location are considered a database.

• When data volumes become large, it is often best to use a database management system (DBMS) to help store, organize, and manage data


Data Management

• A DBMS is nothing more than computer software for managing a database.

• There are many different designs of DBMSs, but in GIS the relational design has been the most useful.

• In the relational design, data are stored conceptually as a collection of tables.


A DBMS contains

• Data definition language

• Data dictionary

• Data-entry module

• Data update module

• Report generator

• Query language


Data structure

• Flat file (tabular) - data in a single table (no link between tables).

• Hierarchical - keys for data retrieval are clearly defined (one-to-many relationship).

• Network - constructed based on pointers and links between data records (many-to-many relationship).

• Relational - normalized tables with common redundant fields for relational link (many-to-many relationship).


Hierarchical Data Structure

Network SystemRelational Structure

Database Structure


Relational Model

• Widely used in GIS• Commonly used relational DBMS are as follows:

– INFO - used in ARC/INFO

– EMPRESS - used in System/9

– ORACLE - used in ARC/INFO, GeoVision, etc.

– SQL & ACCESS – used in PC-based GIS - Arcview

– dBASE - used in pcARC/INFO and other PC-based GIS ARCVIEW.


Relational Model

• Each record has a set of attributes (fields or items).

• The range of possible values (domain) is defined for each attribute.

• Records of each type form a table or relation.

• In a table, each row is a record or tuple and each column is an attribute or field.


Relational Model


Relation

• The degree of a relation is the number of attributes in the table.

• A one-attribute table is a unary relation.

• A two-attribute table is a binary relation.

• A n-attribute table is an n-ary relation.


The degree of a relation.


Key

• A key of a relation is a subset of attributes with the following properties: – unique identification: the value of a key is unique for

each tuple. – non-redundancy: no attribute in the key can be

discarded without destroying the key's uniqueness – A primary key is a combination of attributes (fields)

whose values uniquely address each record in a relation.

– A foreign key is an attribute in one relation (table) which can serve as a primary key into another table.


Key


Foreign Key Primary Key


Normalization

• It is a step-by-step process for converting data structures into a standard form (relational tables)

• This standard form satisfies the ff. constraints:– Each entry in a table represents one data item (no

repeating groups).– All items within each column are of the same kind.– Each column has a unique name.– All rows are unique (no duplicates).– The order of viewing the rows and columns does not affect

the semantics of any function using the table.


Normalization

• Elimination of anomalies in data structure– Update anomalies– Deletion anomalies– Insertion anomalies


Non-normalized relation.

RepeatingGroup

What if this group is repeated in 10,000 records?



Changing theerodibility of Loamy Sand from 0.10 to0.15. What if thereare 10,000 records withLoamy Sand?

Update Anomaly



Deleting allrecords withLoamy Sand. Should thecorrespondingentries underLand Systembe also deleted?

Deletion Anomaly



Adding the Soil Type Clayey. What if thereare 10,000records havingthis Soil Type?

Insertion Anomaly


Normalized relations.

SQL

SQL – Standard Query Language


Normalization

• Major Steps– remove repeating groups of information and

move each group out into its own table– look at the information in terms of

dependencies (separating out information that is not dependent on the table's Primary Key)


Relational join

(using Standard Query Language or SQL)


Degree of Relationship

• One-to-one relationship– A division has at most one chief and that a chief

is a head of at most one division

• One-to-many relationship– A division has many staff and a staff belongs to

at most one division

• Many-to-many relationship– An employee may be assigned to many projects

and a project may have many employees assigned to it


One-to-one Relationship

1

1


One-to-many Relationship

1

N


Determine if the following tables are normalized or not.

HF_Code Health Facility Name Class

043425H0001 Marinduque Provincial Hospital

HOSPITAL

043412H0001 Sta. Cruz Provincial Hospital

HOSPITAL

043412R0001 Brgy. Morales Brgy. Clinic RHU

A. Health_Facility (HF_Code, Health Facility Name, Class)

HF_Code Health Facility Name EQUIPMENT_CODE EQUIPMENT

043425H0001 Marinduque Provincial Hospital E1 X-Ray Machine

043412H0001 Sta. Cruz Provincial Hospital E2 Computer

043425H0001 Marinduque Provincial Hospital E2 Computer

043412R0001 Brgy. Morales Brgy. Clinic E3 Air Conditioner

B. Health_Facility (HF_Code, Health Facility Name, Equipment_Code, Equipment)


Determine if the following tables are normalized or not.

HF_Code Health Facility Name Catchment Population

043425H0001 Marinduque Provincial Hospital 13,980

043412H0001 Sta. Cruz Provincial Hospital 17,490

043412R0001 Brgy. Morales Brgy. Clinic 3,459

C. Health_Facility (HF_Code, Health Facility Name, Catchment Population)

HF_Code Health Facility Name HW_ID Type_of_HW

043425H0001 Marinduque Provincial Hospital 1200459 Doctor

043412H0001 Sta. Cruz Provincial Hospital 1200460 Nurse

043412R0001 Brgy. Morales Brgy. Clinic 1200461 Medical Technologist

D. Available_HW (HF_Code, Health Facility Name, HealthWorker_ID, Type_of_HW)


Topology

• The mathematical procedure for explicitly defining relationships between spatial objects.

• Topology expresses different types of spatial relationships: (3 major topological concepts)– arcs connect to each other at nodes (connectivity)

– arcs that connect to surround an area define a polygon (area definition)

– arcs have direction and left and right sides (contiguity)


An arc in vector GIS.


Example of "built" topology (ARC/INFO)


Data Manipulation

• GIS data need to undergo transformation before they can be integrated, displayed or analyzed.– same scale, coordinate system, format, etc.

• A temporary transformation for display purposes or a permanent one required for analysis


GIS Data Quality

As a result of increased mapping capabilities using GIS, two new and very significant mapping issues arose .• Map Scale• Accuracy/Error


Map scale• The major concern in collecting/using spatial data any mapping

purpose is scale• The ratio of distance on a map over the corresponding distance

on the ground.• Scale is represented as 1: M or 1/M, where M is called the scale

denominator. The Larger the scale, the more the detail described by the map and with higher accuracy.

• Most of the available GIS data are collected at the common scale such as 1:50000 or 1:24000.

• It is possible to change the scale in GIS but not advised (important detail are missing)

• Use of multi scale/multi resolution data• US geological survey provides two dataset at two

resolution(NIMA-100 m and USGS-30 m).Using above two sources result in different maps.


Map Scale


Data Quality: Accuracy/Error• The closeness of measurements or estimates by computation to true

values.

• Accuracy is generally represented by standard deviation of errors, that is difference between measurements and the true value.

xi: error in measurements

n : number of measurements

• In GIS, errors result from the map itself, map digitizing and coordinate

transformation, which will sum up to about 0.5 mm on the map.

• Error associated with spatial information can be user errors, measurement error and processing error.


Error: User error• Age of data - Reliability decreases with age. • Map scale - Non-availability of data on a proper scale or Use of data at different scales• Density of observation - Sparsely distributed data set is less reliable• Relevance of data - results from indirect or derived data

layers as input into GIS• Data inaccuracy - Positional, elevation, minimum, mapable unit etc.• Inaccuracy of contents - Attributes are erroneously attachedAccessibility Military restrictions, inter-agency rivalry, privacy

laws, and economic factors may restrict data availability or the level of accuracy in the data


Error: Measurement Error

• Error associated with variations in data set.

• Error due to limitations and/or quality of instrument.

• Error due to limitation in collecting data in the field.(human skill)

• Error due to natural conditions


Error: Processing Error

• Processing error includes factors such as precision, interpolation,generalization, data conversion, digitization and other methodical operations.

• Error due to combining data layers

• Error due to registration


Data Analysis

• Perform queries:– Who owns the hospital on the corner?

– How far is it between two places?

– Where is the site suitable for building new hospital?

– How big is the area serviced by the hospital?

• GIS provides both simple point-and-click query capabilities and sophisticated analysis tools


Data Analysis

• Perform analysis and modeling to look for patterns and trends and to undertake "what if" scenarios.– If a new factory is built here, how will the residents’

health be affected?

– Given a series of environmental data, where will malaria most likely break out?

– If all the factories near a wetland accidentally release chemicals into the river at the same time, how long would it take for a damaging amount of pollutant to enter the wetland reserve?


GIS Queries

• Attribute Query

• Spatial Query

• Combination of Attribute Query and Spatial Query


Spatial Overlay

• An operation that merges the features of two coverage layers into a new layer and relationally joins their feature attribute table.

• When overlay occurs, spatial relationships between objects are updated for the new, combined map.

• In some circumstances, the result may be information about relationships (new attributes) for the old maps rather than the creation of new objects.


Spatial AnalysisGIS operational procedure and analytical tasks that

are particularly useful for spatial analysis include:• Single layer operations• Multi layer operations/ Topological overlay• Geometric modeling

– Calculating the distance between geographic features– Calculating area, length and perimeter– Geometric buffers.

• Network analysis• Surface analysis• Raster/Grid analysis


GIS Applications in Natural Resource Management

• Agricultural development• Land evaluation analysis• Change detection of vegetated areas• Analysis of deforestation and associated

environmental hazards• Monitoring vegetation health• Mapping percentage vegetation cover for the

management of land• Crop acreage and production estimation• Wasteland mapping


• References:– Fundamentals of GIS by P.L.N. Raju,

Geoinformatics Division Indian Institute of Remote Sensing, Dehra Dun

– Bobby Crisostomo, NAMRIA, Philippines


THANK YOU

Training workshop on GIS and Remote Sensing Applications in Agricultural Meteorology for the (SADC)...

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