Geographic Query and Analysis Reading: Longley: Ch 13 Demers: Ch 7

1. Geographic Query and Analysis Reading: Longley: Ch 13 Demers: Ch 7

2. Spatial Analysis is the means of adding value to geographic data, and of turning data into useful information. Spatial Analysis can reveal things that might otherwise be invisible- it can make what is implicit explicit. Effective spatial analysis requires an intelligent user, not just a powerful computer Spatial analysis helps us in situations when our eyes might otherwise deceive us

3. There are many ways of defining spatial analysis, but all in one way or another express the basic idea that information on locations is essential Analysis carried out without knowledge of locations is not spatial analysis. The calculation of an average income for a group of people is not spatial analysis, because it no way depends on the locations of the people. But the calculation of the center of the US population is spatial analysis, because the results depend on knowing where all US residents are located. GIS is an ideal platform for spatial analysis because its data structures accommodate the storage of object location

4. Spatial analysis can be used to further the aims of science, by revealing patterns that were not previously recognized, and that hint at undiscovered generalities and laws. INDUCTIVE USE OF SPATIAL ANALYSIS: To examine empirical evidence in the search for patterns that might support new theories or general principles, for example with regard to disease causation Patterns in the occurrence of a disease may hint at the mechanisms that cause the disease, and some of the most famous examples of spatial analysis are of this nature, including the work of Dr. John Snow in unraveling the causes of cholera

5. DEDUCTIVE SPATIAL ANALYSIS Focusing on the testing of known theories or principles against data such as hypothesis testing NORMATIVE SPATIAL ANALYSIS APPLICATIONS Using spatial analysis to develop or prescribe new or better designs, for the locations of new retail stores, or new roads, or new manufacturing plant.

6. TYPES OF SPATIAL ANALYSIS 1. Queries and Reasoning 2. Measurements 3. Transformations 4. Descriptive Summaries 5. Optimization Techniques 6. Hypothesis testing

7. QUERIES AND REASONING *The most basic of analysis operations. *No changes occur in the database, and no new data are produced *The operations vary from simple and well-defined queries like “how many houses are found within 1 km of this point” “which is the closest city to Los Angeles” *The user interrogate the system about any aspects of its contents, and obtain an immediate answer. *Interrogation might involve pointing at a map, or typing a question, or pulling down a menu and clicking on some buttons, or sending a formal SQL request to a database -SQL is a standard language for querying tables and relational databases

8. MEASUREMENTS • Simple numerical values that describe aspects of geographic data. • Include measurement of simple properties of objects, like • length, • area, • shape, • and of the relationships between pairs of objects, like • distance • direction • slope • aspect

9. TRANSFORMATIONS • Simple methods of spatial analysis that change datasets, combining them or comparing them to obtain new datasets, and eventually new insights. • Transformations use simple geometric, arithmetic, or logical rules, and they include operations that convert raster data into vector data, or vice versa. • They may also create fields from collections of objects, or detect collections of objects in fields.

10. Buffering Buffering: One of the most important transformations available to the GIS user *Given any set of objects, which may include points, lines, or areas, a buffer operation builds a new object or objects by identifying all areas that are within a certain specified distance of the original objects * Buffering is possible in both raster and vector GIS

11. Point in Polygon • It determines whether a given point lies inside or outside a given polygon • The points represent instances of a disease in a population, and the polygons represent reporting zones such as counties-the task is to determine how many instances of the disease occurred in each zone • The points represent the residential locations of voters, and the polygons represent voting districts- the task is to ensure that each voter receives the correct voting forms in the mail

12. Polygon Overlay • Similar to point in polygon transformation in the sense that two sets of objects are involved, but in this case both are polygons • How much of this proposed clearcut lies in this riparian zone? • What proportion of the land area of the USA lies in areas managed by the Bureau of Land Management? • How much of this land parcel is affected by this easement?

13. Spatial Interpolation • Pervasive operation in GIS • GIS attempt to make a reasonable estimate of the value of a field at places where the field has not actually been measured. • Applications: • In estimating rainfall, temperature, and other attributes at places that are not weather stations, and where no direct measurements of these variables are available • In estimating the elevation of the surface in between the measured locations of a DEM • In resampling rasters, the operation that must take place whenever raster data must be transformed to another grid • In contouring, when it is necessary to guess where to place contours in between measured locations

14. Two commonly used methods of spatial interpolation • Inverse Distance Weighting (IDW) • It employs the Tobler law by estimating unknown measurements as weighted averages over the known measurements at nearby points, giving the greatest weight to the nearest points. Unknown value to be interpolated

15. Kriging • The basic idea is to discover something about general properties of the surface, as revealed by the measured values, and then to apply these properties in estimating the missing parts of the surface. • Kriging is an advanced geostatistical procedure that generates an estimated surface from a scattered set of points with z values. Unlike the other interpolation methods, KRIGING involves an interactive investigation of the spatial behavior of the phenomenon represented by the z values before the user selects the best estimation method for generating the output surface. • Kriging is based on the regionalized variable theory that assumes that the spatial variation in the phenomenon represented by the z values is statistically homogeneous throughout the surface (i.e., the same pattern of variation can be observed at all locations on the surface). This hypothesis of spatial homogeneity is fundamental to the regionalized variable theory.

16. Density estimation • It begins with points and ends with surface • Applied to the estimation of point density • Examples: • Estimation of population density • Density of different kinds of diseases • Density estimation with a kernel allows the spatial resolution of a field of population density to be made explicit. • For example, if we look at the landscape of Australia in smaller pieces such as circles in 10 km in radius, and compute population density by dividing the number of people in each circle by the circle’s area, we would obtain different results depending on where the circle was centered. • Population density at a location, and at a spatial resolution of d might be defined by centering a circle at the location, and dividing the total population within the circle by its area.

17. DESCRIPTIVE SUMMARIES • Attempt to capture the essence of a dataset in one or two numbers. They are the spatial equivalent of the descriptive statistics commonly used in statistical analysis, including the mean and standard deviation.

18. OPTIMIZATION TECHNIQUES • Normative in nature • Designed to select ideal locations for objects given certain well-defined criteria. • Widely used in market research, in the package delivery industry, and etc.

19. HYPOTHESIS TESTING • Process of reasoning from the results of a limited sample to make generalizations about an entire population. • It allows to determine whether a pattern of points could have arisen by chance, based on the information from a sample. • It is the basis of inferential statistics and lies in the core of statistical analysis.

20. These six are certainly not the only ways of classifying and organizing the numerous methods of spatial analysis into a simple scheme. For example, cartographic modeling developed by Dana Tomlin. It classifies all GIS transformations of rasters into four basic classes: LOCAL FOCAL GLOBAL ZONAL

21. LOCAL operations examine rasters cell by cell, comparing the value • in each cell in one layer with the values in the same cell in other • layers. • FOCAL operations compare the value in each cell with the values in • its neighboring cells Most often eight neighbors • GLOBAL operations produce results that are true of the entire layer, • such as its mean value • ZONAL operations compute results for blocks of contagious cells • that share the same value, such as the calculation of shape for • contagious areas of the same land use, and attach their results to • all of the cells in each contagious block