SlideShare una empresa de Scribd logo
1 de 30
Fuzzy Logic and GeoMedia
            Supervisors:

                   Prof. Dr. Dietrich Schröder

                   Prof. Dr. Franz-Josef Behr




                                                 1
Agenda
   Introduction            About Me

   Objectives              Work Project on MapWindow

   Literature review         ActiveX
                            Inception of VnRPToolkit
   Study area and Data
   Scope of GeoMedia software
   Fuzzy logic approach
   Boolean logic
   Fuzzy and Boolean Comparisions
   Fuzzy Command Tool
   Conclusions


                                                    2
Introduction

   Site selection process - a screening technique


   Factors for selection of land fill (slope, river, road,
    geology, land use, etc.)


   Factors for restrictions (environmental, economic, social
    and legislative factors.)


   Boolean logic and Fuzzy logic

                                                                3
Objective

   Formulation of membership functions


   Primary goal - creation of generic Tool.


   Comparison of the results
Literature Review

   Conventional use of Fuzzy Logic - control systems

   Successful Implementation – analysis,and classification

    of RS.

   GIS software packages.

       IDRISI called FUZSIG.
   No incorporation of generic tool for process automation
   Fuzzy analysis - Extensive and laborious analysis.

                                                              5
Study area and Data




         Figure 3 : Map of Study Area

                                        6
Scope of GeoMedia Software

   GeoMedia Professional 6.1
   GeoMedia Grid 6.1 – An extension
   Single GIS environment
   Provides generic tools for manual fuzzy analysis
   Customization through VB, Visual C++ and Visual C#




                                                         7
Theory of Fuzzy Logic

   Lotfi Zadeh, Fuzzy Sets (1965).
   Fuzzy logic – Described to cope with fuzziness.
   Fuzzy sets – A superset of conventional (Boolean) logic
   MF range – 0 to 1.
   Reasoning using linguistic terms.
        If the distance is short then assign 0 membership


           0    0     0 1    1      1   0 0   0.2   0.4   0.6   0.8   1 1
               (a) Boolean Logic.         (b) Fuzzy Logic.


                                                                            8
Characteristic Function:
Let X be the universe of discourse with elements x. Then for
  Boolean logic the Characteristic function fA(x) of A

fA(x): X → {0, 1},where      fA(x) = 1       if x is totally in A;
                             fA(x) = 0       if x is not in A;

However for a Fuzzy set A we have

μA(x): X → [0, 1], where     μA(x) = 1     if x is totally in A;
                             μA(x) = 0     if x is not in A;
                             0 < μA(x) < 1 if x is partly in A.




                                                                     9
An example
The degree of Fuzzy sets is shown as follows:
Layers            Membership function
                  MF = 0,             if x < 500
Settlements       MF = 1,             if x > 1500
                  MF = ((x-500)/1000), if 500 ≤ x ≤ 1500




 Figure 1:Visual interpretation of Membership Function with respective graphs

                                                                            10
Membership Functions
Layers        Membership function


              MF = 1,                if 0 <x<5
Slope
              MF = ((x-5)/10),       if 5≤x≤15
              MF = 0,                if x>15

              MF = 0,                if 225≤x≤315
              MF = ((x-135)/90)      if 135<x<225
Aspect
              MF = ((x-315)/90)      if 315<x<45 (315<x<405)
              MF = 1,                if 45≤x≤135
              MF = 1,                if x=361(flat areas)

              MF = 0,                if x<200
Wells
              MF = ((x-400)/200),    if 400≤x≤600
              MF = 1,                if x>600

              MF = 0,                if x<250
River
              MF = ((x-250)/500),    if 250≤x≤750
              MF = 1,                if x>750

Road          MF = 0,                if x>500
              MF = ((500-x)/500),    if 0<x≤500

              MF = 0,                if x<250
settlements
              MF = ((x-500)/1000),   if 500≤x≤1500
              MF =1,                 if x>1500

              MF = 0,                if x > +125
Geology
              MF = ((125-x)/250),    if -125≤x≤+125
              MF = 1,                if x < -125
Fuzzy logic with basic analysis tool




 01Settlement
    Membarship
  0Membarship
  500 m
    Membarship
 1Void m
  1Membarship
  1500
    Membarship
   Void
Fuzzy logic Analysis

                              Rivers

                         Aquifer
                   Wells               Legend
            Settlement                    0
      Aspect                              0.1
                                          0.2
    Roads
                                          0.3
Slope                                     0.4
                                          0.5
                                          0.6
                                          0.7
                                          0.8
                                          0.9
                                          1
Fuzzy analysis results for Optimum
sites
     Addition operation withFunction value of 5
                   Product a threshold
                 Minimum operation




    Suitable areas
    0 Membarship
    1 Membarship
Boolean Analysis
                                          0<Aspect <180

                             Slope < 10 degrees

                          Minor Aquifer
     Settlement distance = 1000m
    Rivers distance = 500m

Roads distance=500m
 Wells distance
 = 500m
Boolean analysis results for optimum
sites
Fuzzy and Boolean Comparisions

                         Minimum Function




   0 Membarship
   1 Membarship
    Boolean resultant areas
Fuzzy and Boolean Comparisions

   Boolean - sharp distinction with “YES” and “NO” areas
   Fuzzy - gradual delineation for selected landfill
   Flexibility to decide on threshold for fuzzy logic
     No need for repeated analysis

     No need for change in criteria and rules

     Saves time and reduces effort

   Decisions on threshold can be supplimented by field
    work
The Fuzzy Command Tool

                    Input section


                    Process Section

                    To specify ascending or
                    descending from a layer
                    Output section

                    Context Help

                    Command buttons
Results of fuzzy command tool
                         Settlement

                 Wells


         Roads

Rivers




                                      Unsuitable
                                      Suitable
Conclusions

   Successful implementation of the generic tool

   Applicability of the tool to any layer except for complicated
    fuzzy functions.

   Illustrates the Need for customizable GIS software's.

   Demonstrates GeoMedia Grid as an example of software
    providing the framework for customizing applications
Conclusions

   Future Work – To improve upon the different functions other
    than linear.

   Future Work – customizing complicated fuzzy functions if the
    process is recurring.
About Me
   B.Sc. Maths, Physics and Geology
   M.Sc. Geology (Osmania University, Hyderabad, India)
   M.Sc. Geoinformatics (HFT, Stuttgart, Germany)

   Work
     Research Associate (Software Developer)

     Currently doing a job as a Software Engineer
Current Job Project – Integration of
MapWindowGIS
 Integration of MapWindowGIS into SAFIRA II MMS
  software
 Softwares and languages used
    MapWindowGIS Libraries
    MapWindow Active X Components
    Visual Basic 6




                                                   25
MapWindowGIS




   GIS application made using MapWindowGIS



                                             26
Possibilities on Selection




 Single selection          Multiple selection      Multiple selection




 Switch selection          Multi De-selection      Single De-selection




           Different capabilities on polygon selection                  27
Final integration of MapWinGIS project




Final Integration of MapWinGIS application into SAFIRA MMS 28
Inception of MapWindow
30

Más contenido relacionado

La actualidad más candente

Brief intro : Invariance and Equivariance
Brief intro : Invariance and EquivarianceBrief intro : Invariance and Equivariance
Brief intro : Invariance and Equivariance홍배 김
 
ELM: Extreme Learning Machine: Learning without iterative tuning
ELM: Extreme Learning Machine: Learning without iterative tuningELM: Extreme Learning Machine: Learning without iterative tuning
ELM: Extreme Learning Machine: Learning without iterative tuningzukun
 
CS 354 Global Illumination
CS 354 Global IlluminationCS 354 Global Illumination
CS 354 Global IlluminationMark Kilgard
 
Image transforms 2
Image transforms 2Image transforms 2
Image transforms 2Ali Baig
 
CS 354 Graphics Math
CS 354 Graphics MathCS 354 Graphics Math
CS 354 Graphics MathMark Kilgard
 
改进的固定点图像复原算法_英文_阎雪飞
改进的固定点图像复原算法_英文_阎雪飞改进的固定点图像复原算法_英文_阎雪飞
改进的固定点图像复原算法_英文_阎雪飞alen yan
 
CS 354 More Graphics Pipeline
CS 354 More Graphics PipelineCS 354 More Graphics Pipeline
CS 354 More Graphics PipelineMark Kilgard
 
CS 354 Texture Mapping
CS 354 Texture MappingCS 354 Texture Mapping
CS 354 Texture MappingMark Kilgard
 
CS 354 Understanding Color
CS 354 Understanding ColorCS 354 Understanding Color
CS 354 Understanding ColorMark Kilgard
 
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...남주 김
 
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...sleepy_yoshi
 
04 image transformations_ii
04 image transformations_ii04 image transformations_ii
04 image transformations_iiankit_ppt
 
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super Vector
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super VectorLec-08 Feature Aggregation II: Fisher Vector, AKULA and Super Vector
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super VectorUnited States Air Force Academy
 
Anomaly detection using deep one class classifier
Anomaly detection using deep one class classifierAnomaly detection using deep one class classifier
Anomaly detection using deep one class classifier홍배 김
 
03 image transformations_i
03 image transformations_i03 image transformations_i
03 image transformations_iankit_ppt
 
"Deep Learning" Chap.6 Convolutional Neural Net
"Deep Learning" Chap.6 Convolutional Neural Net"Deep Learning" Chap.6 Convolutional Neural Net
"Deep Learning" Chap.6 Convolutional Neural NetKen'ichi Matsui
 
Detailed Description on Cross Entropy Loss Function
Detailed Description on Cross Entropy Loss FunctionDetailed Description on Cross Entropy Loss Function
Detailed Description on Cross Entropy Loss Function범준 김
 
Iaetsd vlsi implementation of gabor filter based image edge detection
Iaetsd vlsi implementation of gabor filter based image edge detectionIaetsd vlsi implementation of gabor filter based image edge detection
Iaetsd vlsi implementation of gabor filter based image edge detectionIaetsd Iaetsd
 

La actualidad más candente (20)

Brief intro : Invariance and Equivariance
Brief intro : Invariance and EquivarianceBrief intro : Invariance and Equivariance
Brief intro : Invariance and Equivariance
 
ELM: Extreme Learning Machine: Learning without iterative tuning
ELM: Extreme Learning Machine: Learning without iterative tuningELM: Extreme Learning Machine: Learning without iterative tuning
ELM: Extreme Learning Machine: Learning without iterative tuning
 
CS 354 Global Illumination
CS 354 Global IlluminationCS 354 Global Illumination
CS 354 Global Illumination
 
Image transforms 2
Image transforms 2Image transforms 2
Image transforms 2
 
CS 354 Graphics Math
CS 354 Graphics MathCS 354 Graphics Math
CS 354 Graphics Math
 
改进的固定点图像复原算法_英文_阎雪飞
改进的固定点图像复原算法_英文_阎雪飞改进的固定点图像复原算法_英文_阎雪飞
改进的固定点图像复原算法_英文_阎雪飞
 
CS 354 More Graphics Pipeline
CS 354 More Graphics PipelineCS 354 More Graphics Pipeline
CS 354 More Graphics Pipeline
 
CS 354 Texture Mapping
CS 354 Texture MappingCS 354 Texture Mapping
CS 354 Texture Mapping
 
CS 354 Understanding Color
CS 354 Understanding ColorCS 354 Understanding Color
CS 354 Understanding Color
 
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
A pixel to-pixel segmentation method of DILD without masks using CNN and perl...
 
Logic presentation
Logic presentationLogic presentation
Logic presentation
 
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...
ICML2012読み会 Scaling Up Coordinate Descent Algorithms for Large L1 regularizat...
 
04 image transformations_ii
04 image transformations_ii04 image transformations_ii
04 image transformations_ii
 
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super Vector
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super VectorLec-08 Feature Aggregation II: Fisher Vector, AKULA and Super Vector
Lec-08 Feature Aggregation II: Fisher Vector, AKULA and Super Vector
 
Lec12 review-part-i
Lec12 review-part-iLec12 review-part-i
Lec12 review-part-i
 
Anomaly detection using deep one class classifier
Anomaly detection using deep one class classifierAnomaly detection using deep one class classifier
Anomaly detection using deep one class classifier
 
03 image transformations_i
03 image transformations_i03 image transformations_i
03 image transformations_i
 
"Deep Learning" Chap.6 Convolutional Neural Net
"Deep Learning" Chap.6 Convolutional Neural Net"Deep Learning" Chap.6 Convolutional Neural Net
"Deep Learning" Chap.6 Convolutional Neural Net
 
Detailed Description on Cross Entropy Loss Function
Detailed Description on Cross Entropy Loss FunctionDetailed Description on Cross Entropy Loss Function
Detailed Description on Cross Entropy Loss Function
 
Iaetsd vlsi implementation of gabor filter based image edge detection
Iaetsd vlsi implementation of gabor filter based image edge detectionIaetsd vlsi implementation of gabor filter based image edge detection
Iaetsd vlsi implementation of gabor filter based image edge detection
 

Similar a Fuzzy Logic Analysis using GeoMedia by Bhaskar Reddy Pulsani

Lecture 02 internet video search
Lecture 02 internet video searchLecture 02 internet video search
Lecture 02 internet video searchzukun
 
Machine learning pt.1: Artificial Neural Networks ® All Rights Reserved
Machine learning pt.1: Artificial Neural Networks ® All Rights ReservedMachine learning pt.1: Artificial Neural Networks ® All Rights Reserved
Machine learning pt.1: Artificial Neural Networks ® All Rights ReservedJonathan Mitchell
 
The Bayesian Optimization Algorithm with Substructural Local Search
The Bayesian Optimization Algorithm with Substructural Local SearchThe Bayesian Optimization Algorithm with Substructural Local Search
The Bayesian Optimization Algorithm with Substructural Local SearchMartin Pelikan
 
ujava.org Deep Learning with Convolutional Neural Network
ujava.org Deep Learning with Convolutional Neural Network ujava.org Deep Learning with Convolutional Neural Network
ujava.org Deep Learning with Convolutional Neural Network 신동 강
 
Machine Learning Explanations: LIME framework
Machine Learning Explanations: LIME framework Machine Learning Explanations: LIME framework
Machine Learning Explanations: LIME framework Deep Learning Italia
 
Optimization using soft computing
Optimization using soft computingOptimization using soft computing
Optimization using soft computingPurnima Pandit
 
Magellan FOSS4G Talk, Boston 2017
Magellan FOSS4G Talk, Boston 2017Magellan FOSS4G Talk, Boston 2017
Magellan FOSS4G Talk, Boston 2017Ram Sriharsha
 
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...grssieee
 
Programming in python
Programming in pythonProgramming in python
Programming in pythonIvan Rojas
 
Problem Understanding through Landscape Theory
Problem Understanding through Landscape TheoryProblem Understanding through Landscape Theory
Problem Understanding through Landscape Theoryjfrchicanog
 
Section5 Rbf
Section5 RbfSection5 Rbf
Section5 Rbfkylin
 
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...Magnify Analytic Solutions
 
Reading papers - survey on Non-Convex Optimization
Reading papers - survey on Non-Convex OptimizationReading papers - survey on Non-Convex Optimization
Reading papers - survey on Non-Convex OptimizationX 37
 
Programming withmatlab
Programming withmatlabProgramming withmatlab
Programming withmatlabnehanairm
 
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...Sigma web solutions pvt. ltd.
 

Similar a Fuzzy Logic Analysis using GeoMedia by Bhaskar Reddy Pulsani (20)

Lecture 02 internet video search
Lecture 02 internet video searchLecture 02 internet video search
Lecture 02 internet video search
 
Machine learning pt.1: Artificial Neural Networks ® All Rights Reserved
Machine learning pt.1: Artificial Neural Networks ® All Rights ReservedMachine learning pt.1: Artificial Neural Networks ® All Rights Reserved
Machine learning pt.1: Artificial Neural Networks ® All Rights Reserved
 
The Bayesian Optimization Algorithm with Substructural Local Search
The Bayesian Optimization Algorithm with Substructural Local SearchThe Bayesian Optimization Algorithm with Substructural Local Search
The Bayesian Optimization Algorithm with Substructural Local Search
 
Chtp405
Chtp405Chtp405
Chtp405
 
ujava.org Deep Learning with Convolutional Neural Network
ujava.org Deep Learning with Convolutional Neural Network ujava.org Deep Learning with Convolutional Neural Network
ujava.org Deep Learning with Convolutional Neural Network
 
Machine Learning Explanations: LIME framework
Machine Learning Explanations: LIME framework Machine Learning Explanations: LIME framework
Machine Learning Explanations: LIME framework
 
Optimization using soft computing
Optimization using soft computingOptimization using soft computing
Optimization using soft computing
 
Magellan FOSS4G Talk, Boston 2017
Magellan FOSS4G Talk, Boston 2017Magellan FOSS4G Talk, Boston 2017
Magellan FOSS4G Talk, Boston 2017
 
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...
FR3.L09 - MULTIBASELINE GRADIENT AMBIGUITY RESOLUTION TO SUPPORT MINIMUM COST...
 
[ML]-SVM2.ppt.pdf
[ML]-SVM2.ppt.pdf[ML]-SVM2.ppt.pdf
[ML]-SVM2.ppt.pdf
 
Programming in python
Programming in pythonProgramming in python
Programming in python
 
HalifaxNGGs
HalifaxNGGsHalifaxNGGs
HalifaxNGGs
 
Problem Understanding through Landscape Theory
Problem Understanding through Landscape TheoryProblem Understanding through Landscape Theory
Problem Understanding through Landscape Theory
 
Section5 Rbf
Section5 RbfSection5 Rbf
Section5 Rbf
 
Fuzzy logic member functions
Fuzzy logic member functionsFuzzy logic member functions
Fuzzy logic member functions
 
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...
Logistic Modeling with Applications to Marketing and Credit Risk in the Autom...
 
Reading papers - survey on Non-Convex Optimization
Reading papers - survey on Non-Convex OptimizationReading papers - survey on Non-Convex Optimization
Reading papers - survey on Non-Convex Optimization
 
Programming withmatlab
Programming withmatlabProgramming withmatlab
Programming withmatlab
 
Zoooooohaib
ZoooooohaibZoooooohaib
Zoooooohaib
 
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...
Fault tolerance in wireless sensor networks by Constrained Delaunay Triangula...
 

Más de MapWindow GIS

Python in geoinformatics
Python in geoinformaticsPython in geoinformatics
Python in geoinformaticsMapWindow GIS
 
Decision Support in Uncertain Real Estate Transactions
Decision Support in Uncertain Real Estate TransactionsDecision Support in Uncertain Real Estate Transactions
Decision Support in Uncertain Real Estate TransactionsMapWindow GIS
 
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...MapWindow GIS
 
Recent trends in the world of computers – Thought and facts
Recent trends in the world of computers – Thought and factsRecent trends in the world of computers – Thought and facts
Recent trends in the world of computers – Thought and factsMapWindow GIS
 
Hydrological investigations in the Rétköz, Hungary
Hydrological investigations in the Rétköz, HungaryHydrological investigations in the Rétköz, Hungary
Hydrological investigations in the Rétköz, HungaryMapWindow GIS
 
The multiresolution image format
The multiresolution image formatThe multiresolution image format
The multiresolution image formatMapWindow GIS
 
Guidelines for handling large amount of KML data
Guidelines for handling large amount of KML dataGuidelines for handling large amount of KML data
Guidelines for handling large amount of KML dataMapWindow GIS
 
GIS based sewer maintenance using MapWindow Open Source GIS
GIS based sewer maintenance using MapWindow Open Source GISGIS based sewer maintenance using MapWindow Open Source GIS
GIS based sewer maintenance using MapWindow Open Source GISMapWindow GIS
 
State of FOSS4G in Hungary
State of FOSS4G in HungaryState of FOSS4G in Hungary
State of FOSS4G in HungaryMapWindow GIS
 
Workshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiWorkshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiMapWindow GIS
 
Workshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiWorkshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiMapWindow GIS
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...MapWindow GIS
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...MapWindow GIS
 
What's new in MapWindow v4.8 by Paul Meems
What's new in MapWindow v4.8 by Paul MeemsWhat's new in MapWindow v4.8 by Paul Meems
What's new in MapWindow v4.8 by Paul MeemsMapWindow GIS
 
Collaborative geoprocessing with GGL by Fernando González Cortes
Collaborative geoprocessing with GGL by Fernando González CortesCollaborative geoprocessing with GGL by Fernando González Cortes
Collaborative geoprocessing with GGL by Fernando González CortesMapWindow GIS
 
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pina
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pinainp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pina
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel PinaMapWindow GIS
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...MapWindow GIS
 
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der Auwera
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der AuweraKtunaxa RMS, open source GIS for a first nation by Joachim Van der Auwera
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der AuweraMapWindow GIS
 
Introducing the Geomajas Open Source framework for building spatial web appli...
Introducing the Geomajas Open Source framework for building spatial web appli...Introducing the Geomajas Open Source framework for building spatial web appli...
Introducing the Geomajas Open Source framework for building spatial web appli...MapWindow GIS
 

Más de MapWindow GIS (20)

Python in geoinformatics
Python in geoinformaticsPython in geoinformatics
Python in geoinformatics
 
Decision Support in Uncertain Real Estate Transactions
Decision Support in Uncertain Real Estate TransactionsDecision Support in Uncertain Real Estate Transactions
Decision Support in Uncertain Real Estate Transactions
 
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...
Comparative analysis of Székesfehérvár and Veszprém based on geoinformatic me...
 
Recent trends in the world of computers – Thought and facts
Recent trends in the world of computers – Thought and factsRecent trends in the world of computers – Thought and facts
Recent trends in the world of computers – Thought and facts
 
Hydrological investigations in the Rétköz, Hungary
Hydrological investigations in the Rétköz, HungaryHydrological investigations in the Rétköz, Hungary
Hydrological investigations in the Rétköz, Hungary
 
The multiresolution image format
The multiresolution image formatThe multiresolution image format
The multiresolution image format
 
Guidelines for handling large amount of KML data
Guidelines for handling large amount of KML dataGuidelines for handling large amount of KML data
Guidelines for handling large amount of KML data
 
GIS based sewer maintenance using MapWindow Open Source GIS
GIS based sewer maintenance using MapWindow Open Source GISGIS based sewer maintenance using MapWindow Open Source GIS
GIS based sewer maintenance using MapWindow Open Source GIS
 
State of FOSS4G in Hungary
State of FOSS4G in HungaryState of FOSS4G in Hungary
State of FOSS4G in Hungary
 
Gis in Bihor
Gis in BihorGis in Bihor
Gis in Bihor
 
Workshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiWorkshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh Kolagani
 
Workshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh KolaganiWorkshop: Community mapping and empowerment by Nagesh Kolagani
Workshop: Community mapping and empowerment by Nagesh Kolagani
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
 
What's new in MapWindow v4.8 by Paul Meems
What's new in MapWindow v4.8 by Paul MeemsWhat's new in MapWindow v4.8 by Paul Meems
What's new in MapWindow v4.8 by Paul Meems
 
Collaborative geoprocessing with GGL by Fernando González Cortes
Collaborative geoprocessing with GGL by Fernando González CortesCollaborative geoprocessing with GGL by Fernando González Cortes
Collaborative geoprocessing with GGL by Fernando González Cortes
 
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pina
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pinainp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pina
inp.PINS a link between GIS and Storm Water Management Model by Rui Daniel Pina
 
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
Ease-of-use and Effectiveness of Participatory GIS in Empowering Rural Commun...
 
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der Auwera
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der AuweraKtunaxa RMS, open source GIS for a first nation by Joachim Van der Auwera
Ktunaxa RMS, open source GIS for a first nation by Joachim Van der Auwera
 
Introducing the Geomajas Open Source framework for building spatial web appli...
Introducing the Geomajas Open Source framework for building spatial web appli...Introducing the Geomajas Open Source framework for building spatial web appli...
Introducing the Geomajas Open Source framework for building spatial web appli...
 

Último

Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 

Último (20)

Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 

Fuzzy Logic Analysis using GeoMedia by Bhaskar Reddy Pulsani

  • 1. Fuzzy Logic and GeoMedia Supervisors: Prof. Dr. Dietrich Schröder Prof. Dr. Franz-Josef Behr 1
  • 2. Agenda  Introduction  About Me  Objectives  Work Project on MapWindow  Literature review ActiveX  Inception of VnRPToolkit  Study area and Data  Scope of GeoMedia software  Fuzzy logic approach  Boolean logic  Fuzzy and Boolean Comparisions  Fuzzy Command Tool  Conclusions 2
  • 3. Introduction  Site selection process - a screening technique  Factors for selection of land fill (slope, river, road, geology, land use, etc.)  Factors for restrictions (environmental, economic, social and legislative factors.)  Boolean logic and Fuzzy logic 3
  • 4. Objective  Formulation of membership functions  Primary goal - creation of generic Tool.  Comparison of the results
  • 5. Literature Review  Conventional use of Fuzzy Logic - control systems  Successful Implementation – analysis,and classification of RS.  GIS software packages.  IDRISI called FUZSIG.  No incorporation of generic tool for process automation  Fuzzy analysis - Extensive and laborious analysis. 5
  • 6. Study area and Data Figure 3 : Map of Study Area 6
  • 7. Scope of GeoMedia Software  GeoMedia Professional 6.1  GeoMedia Grid 6.1 – An extension  Single GIS environment  Provides generic tools for manual fuzzy analysis  Customization through VB, Visual C++ and Visual C# 7
  • 8. Theory of Fuzzy Logic  Lotfi Zadeh, Fuzzy Sets (1965).  Fuzzy logic – Described to cope with fuzziness.  Fuzzy sets – A superset of conventional (Boolean) logic  MF range – 0 to 1.  Reasoning using linguistic terms. If the distance is short then assign 0 membership 0 0 0 1 1 1 0 0 0.2 0.4 0.6 0.8 1 1 (a) Boolean Logic. (b) Fuzzy Logic. 8
  • 9. Characteristic Function: Let X be the universe of discourse with elements x. Then for Boolean logic the Characteristic function fA(x) of A fA(x): X → {0, 1},where fA(x) = 1 if x is totally in A; fA(x) = 0 if x is not in A; However for a Fuzzy set A we have μA(x): X → [0, 1], where μA(x) = 1 if x is totally in A; μA(x) = 0 if x is not in A; 0 < μA(x) < 1 if x is partly in A. 9
  • 10. An example The degree of Fuzzy sets is shown as follows: Layers Membership function MF = 0, if x < 500 Settlements MF = 1, if x > 1500 MF = ((x-500)/1000), if 500 ≤ x ≤ 1500 Figure 1:Visual interpretation of Membership Function with respective graphs 10
  • 11. Membership Functions Layers Membership function MF = 1, if 0 <x<5 Slope MF = ((x-5)/10), if 5≤x≤15 MF = 0, if x>15 MF = 0, if 225≤x≤315 MF = ((x-135)/90) if 135<x<225 Aspect MF = ((x-315)/90) if 315<x<45 (315<x<405) MF = 1, if 45≤x≤135 MF = 1, if x=361(flat areas) MF = 0, if x<200 Wells MF = ((x-400)/200), if 400≤x≤600 MF = 1, if x>600 MF = 0, if x<250 River MF = ((x-250)/500), if 250≤x≤750 MF = 1, if x>750 Road MF = 0, if x>500 MF = ((500-x)/500), if 0<x≤500 MF = 0, if x<250 settlements MF = ((x-500)/1000), if 500≤x≤1500 MF =1, if x>1500 MF = 0, if x > +125 Geology MF = ((125-x)/250), if -125≤x≤+125 MF = 1, if x < -125
  • 12.
  • 13. Fuzzy logic with basic analysis tool 01Settlement Membarship 0Membarship 500 m Membarship 1Void m 1Membarship 1500 Membarship Void
  • 14. Fuzzy logic Analysis Rivers Aquifer Wells Legend Settlement 0 Aspect 0.1 0.2 Roads 0.3 Slope 0.4 0.5 0.6 0.7 0.8 0.9 1
  • 15. Fuzzy analysis results for Optimum sites Addition operation withFunction value of 5 Product a threshold Minimum operation Suitable areas 0 Membarship 1 Membarship
  • 16. Boolean Analysis 0<Aspect <180 Slope < 10 degrees Minor Aquifer Settlement distance = 1000m Rivers distance = 500m Roads distance=500m Wells distance = 500m
  • 17. Boolean analysis results for optimum sites
  • 18. Fuzzy and Boolean Comparisions Minimum Function 0 Membarship 1 Membarship Boolean resultant areas
  • 19. Fuzzy and Boolean Comparisions  Boolean - sharp distinction with “YES” and “NO” areas  Fuzzy - gradual delineation for selected landfill  Flexibility to decide on threshold for fuzzy logic  No need for repeated analysis  No need for change in criteria and rules  Saves time and reduces effort  Decisions on threshold can be supplimented by field work
  • 20. The Fuzzy Command Tool Input section Process Section To specify ascending or descending from a layer Output section Context Help Command buttons
  • 21. Results of fuzzy command tool Settlement Wells Roads Rivers Unsuitable Suitable
  • 22. Conclusions  Successful implementation of the generic tool  Applicability of the tool to any layer except for complicated fuzzy functions.  Illustrates the Need for customizable GIS software's.  Demonstrates GeoMedia Grid as an example of software providing the framework for customizing applications
  • 23. Conclusions  Future Work – To improve upon the different functions other than linear.  Future Work – customizing complicated fuzzy functions if the process is recurring.
  • 24. About Me  B.Sc. Maths, Physics and Geology  M.Sc. Geology (Osmania University, Hyderabad, India)  M.Sc. Geoinformatics (HFT, Stuttgart, Germany)  Work  Research Associate (Software Developer)  Currently doing a job as a Software Engineer
  • 25. Current Job Project – Integration of MapWindowGIS  Integration of MapWindowGIS into SAFIRA II MMS software  Softwares and languages used  MapWindowGIS Libraries  MapWindow Active X Components  Visual Basic 6 25
  • 26. MapWindowGIS GIS application made using MapWindowGIS 26
  • 27. Possibilities on Selection Single selection Multiple selection Multiple selection Switch selection Multi De-selection Single De-selection Different capabilities on polygon selection 27
  • 28. Final integration of MapWinGIS project Final Integration of MapWinGIS application into SAFIRA MMS 28
  • 30. 30

Notas del editor

  1. Applai uses GeoConcept Expert software in fuzzy logic business modelling for retail stores
  2. Lotfi Zadeh , Fuzzy Sets (1965). Fuzzy logic is used to describe and cope with fuzziness. fuzzy sets are superset of conventional (Boolean) logic Membership values in fuzzy systems range from 0 to 1, with 0.0 representing absolute Falseness and 1.0 representing absolute Truth. Truth values between True and False. Not everything is either/or, true/false, black/white, on/off etc. Reasoning using linguistic terms . Natural to express expert knowledge. If the distance is short then assign 0 membership
  3. This is the current project I am working on as a researcher to support the D-Site working group (Decision-Support Integrating Technology and Economics). The group develops scientific software as part of research in EberhardKarls Universit ät Tübingen for the assessment, revitalization and optimization of contaminated sites including models for contaminant migration and risk exposure. There are always complications when a licenced software has to be distributed among the users away from scientific community. The project has been taken up to lessen the burden of scientific softwares. Opensource softwares are free to distribute and provides an ideal way for further improvements.
  4. The developed Mini GIS application has capabilities similar to ARCGIS with respect to viewing the shapefiles and its attributes. With the needs of the current project the application has been built to have zoom in, zoom out, panning, selection and zoom to extent map cursor options. It changes the attributes in the table with respect to selected polygons. Has buttons to make backup of the original shapefiles and also reverts the changes when the conditions are not met. When a landuse category (towards the left in the figure that holds four categories) is selected from the listbox, the polygons along with its respective attributes in the table are highlighted. It also gives statistics of the study area (displayed at the bottom of the fugure) which are displayed dynamically when changes are made on the shapefiles. The application is still in the building stage and can be extended to have many more capabilities. This application can be integrated into any software developed on Windows using VB6, VB.Net, C# or Visual C++.
  5. One of the diverse capability includes different selection options with single and multi selection and de-selection options. The values of the any polygons can be changed depending upon the users need to change them.