Does the form of larynx malignant neoplastic disease appear to constellate, or is it wholly random? Based on this simple map, can you see any grounds to propose that instances of larynx malignant neoplastic disease bunch around the incinerator?
Based on the map above in figure 1, the point form of the larynx malignant neoplastic disease appear non wholly random or is spacial distributed in the survey country, there is ocular grounds to propose that there is some grade of voice box malignant neoplastic disease constellating around the incinerator
Fig 2a, B and degree Celsius display 3D of meat strengths of larynx malignant neoplastic disease at different angles
Question2: Do the maps display any country of peculiar high strength? What is the strength of malignant neoplastic disease around the site of incinerator?
Obviously, the maps in figure 2, displays some countries with high strength in xanthous coloring material and the strength is in non unvarying distribution across the country. Therefore there is comparatively high strength around the site of incinerator due to constellate consequence in the area.Moreover ; the 3D rotary motion of meats strength maps ( Fig 2a, B and degree Celsius ) provides different in writing position of strengths around the survey country.
Gatrell, A. et Al ( 1995 ) pointed out the used of Kernel appraisal strength to weighs events harmonizing to their distance from the point.
Figure 3: Nearest neighbour empirical distribution of Larynx malignant neoplastic disease
Question3: Analyze the signifier of the G ( tungsten ) . What does it state you about the form of voice box malignant neoplastic diseases?
The G map is plotted against S in figure 3 shows that the event starts from ( 0, 0 ) and bit by bit moves over a distance of 200 Unit of measurements. It shows rapid addition from over a distance of 575 – 900 units or there about, bespeaking that many of the nearest distances autumn within this scope. We can subtract that the form of the larynx malignant neoplastic disease from the G map is based on constellating consequence on the nearest neighbour distance. O ‘ Silluvan 2003 stated “ When events are clustered, G increases quickly at a short distance and while separated events increases at slow rate ” .
Fig 4: K map against CSR theoretical account
Question4: Expression at the graph it shows the value of K for scope of distances ( Plotted along the X- axis ) compared along the value of K for a CSR theoretical account – is there any grounds of bunch and if so at what distances?
From the graph shown above there is grounds of constellating at distances between the scope of 500 to 3000 units because the K ( vitamin D ) secret plan is higher than the CSR theoretical account at this scope of distance. This indicates that events ( voice box ) malignant neoplastic diseases in the form are much nearer under the CSR manner.
Fig 5: L ( tungsten ) map against CSR theoretical account
Question5: Look at the consequence -how do you compare with those obtained from a graph of K ( vitamin D ) you constructed above?
Comparing the consequence of from the graph shows that ;
Both maps have some grade of about the same geographical extent
Both shows bunch of the voice box malignant neoplastic disease
The strength of constellating at different graduated tables appears best in L map than in K Function
Both do non hold important constellating from their beginnings
Question6: What premises have you made about the distribution of population and what decisions might we wrongly reach, sing the function of the of the incinerator in doing malignant neoplastic disease, if we do non account for this factor.
Well, my decisions were ;
The disease voice box malignant neoplastic disease is associated to the incinerator
On the other manus, the geographical country under survey show that, the population is unevenly distributed as such incinerator can non be entirely responsible for the larynx malignant neoplastic disease as there is some bunch far off from the incinerator.
POINT PATTERN ANALYSIS OF THE LUNG CANCER
Fig 6 Point Pattern distribution of lung malignant neoplastic disease in Lancashire
Based on the map above in figure 6 above, The point form of the lung malignant neoplastic disease appear non wholly random or is spacial distributed in the survey country, there is ocular grounds to propose that there is some grade of lung malignant neoplastic disease constellating near the incinerator
Fig 7 a, B and degree Celsius ; Point Pattern distribution of lung malignant neoplastic disease in Lancashire
Theta=50A° theta=90A° theta=180A°
Fig 8 show 3D of meat strengths of lung malignant neoplastic disease at different angles
The meat maps show in Fig 7a and b above indicate a non unvarying point pattern distribution of lung malignant neoplastic disease across the survey country. Furthermore ; the 3D rotary motion of meats strength maps ( Fig 7a, B and degree Celsius ) provides different in writing position of strengths around the survey country. However the strength of lung malignant neoplastic disease appears to be comparatively low around the site of incinerator.
Fig 8: G map against CSR theoretical account
The graph of G map plotted against s above ( Figure 8 ) revealed how instances of lung malignant neoplastic disease are spaced within the survey country. As we can see from the graph, its moves quickly at 500 – 700 units, so slows at 700- 1000 units or there about. However it shows some grade of stabilisation over a distance of 1000 – 3000 units. From the graph above it is obvious that lung malignant neoplastic disease is non wholly random in the survey country or it has some grade of spacing.
Fig 9: K map against CSR theoretical account
A graph of K-function compared to CSR theoretical account against distance ( s ) as shown above ( Figure 9 ) there is grounds of lung malignant neoplastic disease bunch in some parts of the survey country. From 100unit to greater 4000 units indicates a strong grounds of constellating. K curve ( black ) rises above the ruddy with covering distance of about 2800 Unit of measurements or there about.
Fig 10: Fifty map against CSR theoretical account
Question 5: The figure 10 above, indicate bunch of lung malignant neoplastic disease in the survey country. The consequence of the L map shows a divergence from the CRS hypothesis, as L strays above the CRS theoretical account with positive values throughout the ascertained distance and this shows contemplation of bunch.
Question 6: The disease of lung malignant neoplastic disease might non be associated to the incinerator ; as fewer instances are found around the incinerator country. As such incinerator is non responsible for the lung malignant neoplastic disease. However, the analysis show an unevenly distribution of high population over the survey country. And this might lend to it.
Question 7: from the consequence of statistical analysis how does the form of LUNG malignant neoplastic diseases compare to that of LARYNX malignant neoplastic diseases?
From the above analysis we can subtract the followerss ;
Both lungs and voice box malignant neoplastic diseases are non wholly random
Both shows important divergence from CRS theoretical account
G map shows big figure of nearest neighbour in lung malignant neoplastic diseases and on the other manus voice box malignant neoplastic diseases show little Numberss of nearest neighbour, although both have similar form across the survey country
K map shows constellating in both with higher in lung malignant neoplastic diseases
Both lungs and voice box malignant neoplastic diseases shows some high grade of constellating in certain geographical country
Fig 11 Point pattern distribution of voice box and lung malignant neoplastic diseases in Lancashire
Question 8: Assuming the lung malignant neoplastic disease is a good step of the implicit in population distribution ; are at that place any parts of the survey country which seems to hold an surplus of voice box malignant neoplastic diseases?
From the fig 11 above, we can clearly see the site near incinerator shows a comparatively higher incidence of voice box malignant neoplastic diseases as when comparison with lung malignant neoplastic diseases. But nevertheless the lung malignant neoplastic disease is more intense in geographical country
Question 9: In non more than 500 words, depict the application of point-pattern analysis in a GIS application context other than medical/health/epidemiology.
”Point Pattern Analysis involves the ability to depict forms of locations of point events and trial whether there is a important happening of bunch of points in a peculiar country ” French republics F. Burden ( 2003 )
The comparative importance of point-pattern analysis may non be over emphatic, research have shown that point-pattern analysis dramas of import function in wellness or epidemiology, forestry, urbanisation, archaeology, uranology, criminology, natural catastrophes like temblors, among others.
The point form analysis is one of most common technique for analysing spacial distribution, partially because of its simplification and partially because there are a batch of spacial informations collected as points.
In this exercising, effort will be made utilizing point form analysis to look into issues sing to criminology analysis and this is implemented utilizing nearest neighbour distance statistics.
( P. Rogerson and Y. Sun 2001 ) , in their journal spacial monitoring of geographic forms, it attempts to depict a new process for observing alterations over clip in the spacial form of point ‘s events. It combines both the cumulative amount method every bit good as the nearest neighbour. The method used consequences in the winging sensing of divergences from expected forms.
Similarly, Yongmei Lu and Xuwei Chen ( 2006 ) uses point pattern analysis on the false dismay of two-dimensional K- map when analysing urban offense distributed along streets.. the pointed the importance of K map as the common method normally used for general point form analysis every bit good as offense form survey
The importance of spacial point analysis in criminology has led to invented different package ‘s like Ned levine ‘s CrimeStat version 3.3. CrimeStat lll, which is presently being used by many constabularies sections every bit good as condemnable justness and other research workers
Today authorities and intelligent units including CIA ‘s, KGB, FBI ‘s, constabulary and other condemnable justness utilizations point pattern analysis in order to observe felons.
Therefore, point form analysis is really powerful tool in criminology and it can non be separated with GIS because, GIS gives information on every event of a spacial information.
CrimeStat III: A Spatial Statistics Program for the Analysis of Crime Incident Locations ( Version 3.3 ) hypertext transfer protocol: //www.icpsr.umich.edu/icpsrweb/ICPSR/studies/2824
French republics F. Burden 2003.Point Pattern Analysis.GIS Resource Document 03-41 ( GIS_RD_03-41 )
hypertext transfer protocol: //www.pop.psu.edu/gia-core/pdfs/gis_rd_03-41.pdf
Gatrell, C.A. et Al ( 1995 ) . Spatial point analysis and its application in geographical epidemiology. Minutess of the Institute of British Geographers, New Series Vol. 21 ( 1 ) p256 -247
O ‘ Silluvan D and Unwin D.J. ( 2003 ) . Geographic Information Analysis. New Jersey:
P. Rogersson and Y. Sun ( 2001 ) . Spatial monitoring of geographic forms: an application to offense analysis. Computers, Environment and Urban Systems. Vol. 25 ( 6 ) p539 – 556
Yongmei Lu and Xuwei Chen ( 2006 ) . On the false dismay of Planar K- map when analysis urban distributed along streets. Social scientific discipline Research Vol. 36 ( 20 p611 – 632
hypertext transfer protocol: //uregina.ca/piwowarj/geog409/Lab3.pdf