I created maps on those peoples who are affected from dengue disease,and this analysis is

2. Final projectFinal project
Dengue distribution And Relation With ArsenicDengue distribution And Relation With Arsenic
SUBIMITTED TO:SUBIMITTED TO:
Mrs.Qudsia HamidMrs.Qudsia Hamid
SUBMITTED BY:SUBMITTED BY:
Muhammad Burhan KhalidMuhammad Burhan Khalid
M.Sc GISM.Sc GIS
PUNJAB UNVERSITY (COLLEGE OF INFORMATION ANDPUNJAB UNVERSITY (COLLEGE OF INFORMATION AND
TECHNOLOGY)TECHNOLOGY)

3. WhyWhy
Spatial Analysis:Spatial Analysis:
Help us ?Help us ?
 Properties of spatial features and/orProperties of spatial features and/or
relationships between them:relationships between them: size,size,
distribution, pattern, neighborhood, shape,distribution, pattern, neighborhood, shape,
scale, orientationscale, orientation

4. ObjectiveObjective
 The main objective is to:The main objective is to:
o To find out the how many people affected by theTo find out the how many people affected by the
dengue virus.dengue virus.
o And how to over come the spread of the dengueAnd how to over come the spread of the dengue
disease.disease.

5. DATA AQUISITIONDATA AQUISITION
 We have a shape file of different town in LahoreWe have a shape file of different town in Lahore
which is digitized with the help of satellite image.which is digitized with the help of satellite image.
 We have a data about dengue effected people inWe have a data about dengue effected people in
different town in Lahore ( Data is gather fromdifferent town in Lahore ( Data is gather from
TOWN HALL)TOWN HALL)
 We have a data about tube well in different townsWe have a data about tube well in different towns
in Lahore.in Lahore.
 We also have a data about arsenic contaminationWe also have a data about arsenic contamination
in tube well water.in tube well water.

6. Layers Used In This ProjectLayers Used In This Project
Infected people
Tube well water
Human settlements
... ............ .......
........ ....... ....
Adult
mosquitoes

7. Analysis are performed on patient, U.C wise and tube
well shape file
Overlay analysis
Spline
ANALYSIS
Interpolation techniques
Inverse Distance
Weighted
Kriging
Hotspot analysis

8. Task: 1Task: 1
InterpolationInterpolation
 Patients 2010(IDW)Patients 2010(IDW)
 Patients 2010 (Spline)Patients 2010 (Spline)
 Patients 2010 (Krging)Patients 2010 (Krging)
On the Basis Of AgesOn the Basis Of Ages
 Tube wells 2010 (IDW)Tube wells 2010 (IDW)
 Tube wells 2010 (Spline)Tube wells 2010 (Spline)
 Tube wells 2010 (Krging)Tube wells 2010 (Krging)
On the Basis OfOn the Basis Of
ArsenicArsenic

9. Spatial InterpolationSpatial Interpolation
 A process of using locations with known dataA process of using locations with known data
values to estimate values at other locations.values to estimate values at other locations.
 A “A “statistical surfacestatistical surface” is constructed by” is constructed by
interpolating unknown values from known values.interpolating unknown values from known values.

10. Inverse Distance weightedInverse Distance weighted
Inverse DistanceInverse Distance
Weighted enforcesWeighted enforces
that the estimatedthat the estimated
value of a point isvalue of a point is
influenced more byinfluenced more by
nearby known pointsnearby known points
than those fartherthan those farther
away.away.
We make a map ofWe make a map of
patients IDW andpatients IDW and
tubewell.tubewell.

11. SplineSpline
Splines create aSplines create a
surface that passessurface that passes
through the controlthrough the control
points and has thepoints and has the
least possibleleast possible
change in slope atchange in slope at
all points (minimumall points (minimum
curvature surface).curvature surface).

12. KRIGINGKRIGING
 Kriging a geostatisticalKriging a geostatistical
method for spatialmethod for spatial
interpolation where theinterpolation where the
mean is estimated frommean is estimated from
the best linear unbiasedthe best linear unbiased
estimator or best linearestimator or best linear
weighted movingweighted moving
average.average.
 We making a krigingWe making a kriging
map of patients and tubemap of patients and tube
well datawell data

13. Task:2Task:2
OverlayingOverlaying
 IDW (IDW (Patient and Tube wellPatient and Tube well))
 Spline (Spline (Patient and Tube wellPatient and Tube well))
 Krging (Krging (Patient and Tube wellPatient and Tube well))

14. Overlay analysisOverlay analysis
 ““Overlay is a GIS operation in which layers withOverlay is a GIS operation in which layers with
a common, registered map base are joined ona common, registered map base are joined on
the basis of their occupation.”the basis of their occupation.”
 Weighted Sum technique is used for overlayingWeighted Sum technique is used for overlaying
two raster images.two raster images.

16. Task:3Task:3
Hot Spot AnalysisHot Spot Analysis
 Analysis perform on theAnalysis perform on the
tube well data on thetube well data on the
basis of arsenic .basis of arsenic .

17. Patients in 2007Patients in 2007

18. Patients in 2008Patients in 2008

19. Patients in 2009Patients in 2009

20. Patients in Aug,2010Patients in Aug,2010

21. Patients in Oct,2010Patients in Oct,2010

22. Patients in Nov,2010Patients in Nov,2010

23. Graph of 2009 PatientsGraph of 2009 Patients

24. Graph of Patients 2010Graph of Patients 2010

25. Comparison between 2009 andComparison between 2009 and
20102010

26. Comparison AnalysisComparison Analysis

27. ConclusionConclusion
We concluded that where the tube well isWe concluded that where the tube well is
in greater amount the patient is less andin greater amount the patient is less and
where the tube well is in less amount thewhere the tube well is in less amount the
patient is greater.patient is greater.

28. THANKSTHANKS