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GES673 Spring 2013 UMBC MPS in GIS: Lecture from Week 2

GES673 Spring 2013 UMBC MPS in GIS: Lecture from Week 2

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    Spatial Analysis; The Primitives at UMBC Spatial Analysis; The Primitives at UMBC Presentation Transcript

    • Geoprocessing & Spatial Analysis GES673 at Shady Grove Richard Heimann Richard Heimann © 2013Thursday, February 21, 13
    • ReviewLocational Invariance (Goodchild et al): Fundamental property of spatial analysis Results change when location changes.Two Data Models: Raster Model & Vector ModelComponents of Spatial Analysis: -Visualization Showing Interesting Patterns. -Exploratory Spatial Data Analysis Finding Interesting Patterns. -Spatial Modeling, Regression Explaining Interesting Patterns. Richard Heimann © 2013Thursday, February 21, 13
    • ReviewDescription versus Analysis: Process, Pattern and AnalysisFour levels of Spatial Analysis: Spatial Data Description Exploratory Spatial Data Analysis - ESDA Spatial statistical analysis and hypothesis testing Spatial modeling and predictionWhy is Spatial Data Special; Potentials and Pitfalls. Spatial Autocorrelation, MAUP (scale & zone), Scale effects, Ecological Fallacy, Non-uniformity of space, Edge Effects.Big Data Geographic Knowledge Discovery Experimentation Richard Heimann © 2013Thursday, February 21, 13
    • What will we discuss…? Laws of Spatial Science - the primitives of spatial analysis!! …what are they and why are they important? …how do we begin to measure and quantify the existence of such laws? Contemporary Examples... Spatial is Special -- The Potentials & Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • The value of Laws Teaching Laws allow courses to be structured from first principles Laws provide the basis for predicting performance, making design choices An asset of a strong, robust discipline Richard Heimann © 2013Thursday, February 21, 13
    • Are Laws of Spatial Science… Deterministic? Does a counterexample defeat a law? Empirical statements? Verifiable with respect to the real world? Do the Social Sciences have Physics Envy? Richard Heimann © 2013Thursday, February 21, 13
    • Candidate for the First Law of Social Science Can there be laws in the social sciences? Ernest Rutherford: “The only result that can possibly be obtained in the social sciences is: some do, and some don’t” Richard Heimann © 2013Thursday, February 21, 13
    • Social Science Laws can be: Anyon (1982): social science should be empirically grounded, theoretically explanatory and socially critical. Richard Heimann © 2013Thursday, February 21, 13
    • Social Science Laws ought to be empirically grounded... Anyon (1982): [T]hat one collects data and uses it to build ones explanations. Ideally ones explanations are related to the data in that they emerge from it. Yet, they attempt to explain it by recourse to categorically different types of constructs: not by other data [...] (p. 35) It is not sufficient to explain patterns in data using a method that was designed to define patterns in data. Richard Heimann © 2013Thursday, February 21, 13
    • Social Science Laws ought to be theoretically explanatory : Anyon (1982): [T]hat one does not rely, for ones reasons for things, on empirically descriptive regularities or generalizations, or on deductions or inferences there from ones theory must be socially explanatory. It must situate social data in a theory of society. (p. 35) ...still theory-poor Richard Heimann © 2013Thursday, February 21, 13
    • Social Science Laws ought to be socially critical: Anyon (1982): To be critical will mean, then, to go beyond the dominant ideology or ideologies, in ones attempt to explain the world. To be critical is to challenge social legitimations, and fundamental structures [...] to seek to explicate, and to seek to eliminate structurally induced exploitation and social pain. (pp. 35-6) Richard Heimann © 2013Thursday, February 21, 13
    • Social Science Laws can be: Based on empirical observation Observed to be generally true Sufficient generality to be useful as a norm Deviations from the law should be interesting Dealing with geographic process rather than form Understanding of social process in context …the Nomothetic & Idiographic debate in geography is solved!! Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography (TFLG) TFLG: “All things are related, but nearby things are more related than distant things” W.R.Tobler, 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography 46: 234-240 Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Teenage Birth Rates – US. Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • If TFLG weren’t true… GIS would be impossible Life would be impossible Richard Heimann © 2013Thursday, February 21, 13
    • Tobler’s First Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • TFLG S-ZAR RAN-VAR Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first?) Law of Geography TFLG describes a second-order effect (Properties of places taken two at a time) …is there a law of places taken one at a time? Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first?) Law of Geography TFLG describes a second-order effect (Properties of places taken two at a time) …is there a law of places taken one at a time? Yes, its named Spatial heterogeneity Richard Heimann © 2013Thursday, February 21, 13
    • A (Unofficial) Second (first) Law of Geography LISA MAP | Crime Columbus, OH BOX MAP | Crime Columbus, OH Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first) Law of Geography The geography of the 2004 US presidential election results (48 contiguous states) Spatial heterogeneity Non-stationarity / Regional Variation Uncontrolled variance / Equilibrium Richard Heimann © 2013Thursday, February 21, 13
    • Implications of Second (first) Law Stationarity Extreme Heterogeneity Single Equilibria: A Multiple Equilibrium: One singular process over process for every space and across observation over space. study area. Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first) Law of Geography Total Fertility Rate – US. Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first) Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first) Law of Geography Richard Heimann © 2013Thursday, February 21, 13
    • A Second (first) Law of Geography Globalization is thought of a homogenizing the world, but it cannot and will not happen. The underlying processes that drive these systems both look for unevenness and produce unevenness. Homogeneous processes cannot happen, which necessitate the development of methods to describe the unevenness and account for it when describing process. Richard Heimann © 2013Thursday, February 21, 13
    • Practical implications of Second (first) Law …a state is not a sample of the nation …a country is not a sample of the world Richard Heimann © 2013Thursday, February 21, 13
    • Practical implications of Second (first) Law …no average person or place. With the global population distribution being ~50% male and ~50% female would the average be a person with one uterus and one testis? Richard Heimann © 2013Thursday, February 21, 13
    • Practical implications of Second (first) Law Spatial Simpson’s Paradox; Small Theory & Stylized Facts Global standards will always compete with local social phenomenon. Violence in the Violence in the north north Violence Violence in the south Violence in the south Global models average regionally variant Local models account for regional variation. phenomenon. Richard Heimann © 2013Thursday, February 21, 13
    • Candidate Laws By adding demographics to Tobler’s law we can define as the first law of Spatial Demographics: “…people who live in the same neighborhood are more similar than those who live in a different neighborhood, but they may be just as similar to people in another neighborhood in a different place.” Richard Heimann © 2013Thursday, February 21, 13
    • Candidate Laws Montello and Fabrikant, “The First Law of Cognitive Geography” “People think closer things are more similar” Richard Heimann © 2013Thursday, February 21, 13
    • Cognitive Geography [Ethnocentrisms]… Richard Heimann © 2013Thursday, February 21, 13
    • Cognitive Geography [Ethnocentrisms]… Richard Heimann © 2013Thursday, February 21, 13
    • Cognitive Geography [Ethnocentrisms]… Richard Heimann © 2013Thursday, February 21, 13
    • Cognitive Geography [Ethnocentrisms]… Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis Fuller (1974) argues that political decisions regarding the location of clinics is decided on the basis of aspatial analysis, and therefore family planning programsmay not have the expected impact on fertility levels. The results of his study could be used as a guidance to optimize the number and location of clinics in communities. http://scholarspace.manoa.hawaii.edu/bitstream/handle/10125/22661/PapersOfTheEastWestPopulationInstituteNo.056SpatialFertilityAnalysisInALimitedDataSituation1978%5Bpdfa%5D.PDF?sequence=1 Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial AnalysisPaul Krugman loosely defines economic geography as thestudy of economic issues in which location matters. Economictheory usually assumes away distance. Krugman argues thatit is time to put it back - that the location of production inspace is a key issue both within and between nations. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial AnalysisPaul Krugman loosely defines economic geography as thestudy of economic issues in which location matters. Economictheory usually assumes away distance. Krugman argues thatit is time to put it back - that the location of production inspace is a key issue both within and between nations. New Economic Geography implies that instead of spreading out evenly around the world, production will tend to concentrate in a few countries, regions, or cities, which will become densely populated but will also have higher levels of income. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial AnalysisPaul Collier in his book The Bottom Billion argues that being landlocked in a poorgeographic neighborhood is one of four major development "traps" that a countrycan be held back by. In general, he found that when a neighboring countryexperiences better growth, it tends to spill over into favorable development forthe country itself. For landlocked countries, the effect is particularly strong, asthey are limited from their trading activity with the rest of the world. "If you arecoastal, you serve the world; if you are landlocked, you serve your neighbors.” Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis The Social Disorganization Theory: An ecological perspective on crime, dealing with places, not people, as the reason crime happens: where one lives is causal to criminality; the physical and social conditions a person is surrounded by create crime. The assumption of this theory is that people are inherently good, but are changed by their environment. According to this theory, five types of change are most responsible for criminality. They are: urbanization, migration, immigration,industrialization, and technological change. If any one of these aspects occurs rapidly, it breaks down social control and social bonds, creating disorganization. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial AnalysisIn The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy(1987), William Julius Wilson was an early exponent, one of the first toenunciate at length the spatial mismatch theory for the development of a ghettounderclass in the United States. Spatial mismatch is the sociological, economicand political phenomenon associated with economic restructuring in whichemployment opportunities for low-income people are located far away from theareas where they live. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis Schelling Tipping Model was first developed by Thomas C. Schelling (Micromotives and Macrobehavior, 1978) … and represents one of the first constructive models explicitly designed to explore social issues. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis Proximate casualty hypothesis; (Gartner, Segura, and Wilkening 1997)Time and space provide new insight on the multiple processes underlying opinion change in today’s complex information environment. A case study of the “proximate casualties” hypothesis (Gartner and Segura 2000; Gartner, Segura, andWilkening 1997), the idea that popular support for Americanwars is undermined at the individual level more by the deathsof American personnel from nearby areas than by the deaths of those from far away.  Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis Harvey developed the idea of spatial fix and the second the idea of accumulation by dispossession. The spatial fix is something much more flexible, consisting in the geographical expansions and restructurings used as temporary solutions to over accumulation crises. As Harvey points out, spatial fixes are available even in a world that is more or less fully incorporated in capitalism. Spatial fixes make use of geographical unevenness, but unevenness is not simply a product of "underdevelopment". Capitalism produces its own unevenness, often plunging already “developed” regions into destructive devaluations. The idea implied here is that processes of primitive accumulation are turned not only against the remaining few non-capitalist formations but also against parts of capitalism itself. Richard Heimann © 2013Thursday, February 21, 13
    • Contemporary Examples of Spatial Analysis The Easterlin Theory (Easterlin 1987) suggests a link between cohort sizes and fertility, was tested in a multiregional context using Italy as a case study (Waldorfand Franklin 2002). An elaborated spatial autoregressive model (Anselin 1988) was formulated, showing that: (i) the space-time components are highly significant and therefore cannot be neglected in studies to assess Easterlin’s theory, (ii) diffusion does play a major role and cannot be neglected either, and (iii) the link betweencohort sizes and fertility varies across regions and time (some southern regions, for example, do not substantiate Easterlin’s theory). Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other• Scale effects and measurement pitfalls – Cities may be represented as points or polygons – Results depend on the scale at which the analysis is conducted: province or county – MAUP—scale effect Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other• Scale effects and measurement pitfalls – Cities may be represented as points or polygons – Results depend on the scale at which the analysis is conducted: province or county – MAUP—scale effect• Non-uniformity of Space – Phenomena are not distributed evenly in space – Be careful how you interpret results! Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other• Scale effects and measurement pitfalls – Cities may be represented as points or polygons – Results depend on the scale at which the analysis is conducted: province or county – MAUP—scale effect• Non-uniformity of Space – Phenomena are not distributed evenly in space – Be careful how you interpret results!• Edge issues – Edges of the map, beyond which there is no data, can significantly affect results Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other• Scale effects and measurement pitfalls – Cities may be represented as points or polygons – Results depend on the scale at which the analysis is conducted: province or county – MAUP—scale effect• Non-uniformity of Space – Phenomena are not distributed evenly in space – Be careful how you interpret results!• Edge issues – Edges of the map, beyond which there is no data, can significantly affect results• Modifiable areal unit problem (MAUP-zone ) – Results may depend on the specific geographic unit used in the study – Province or county; county or city Richard Heimann © 2013Thursday, February 21, 13
    • Critical Issues in Spatial Analysis• Spatial autocorrelation – Data from locations near to each other are usually more similar than data from locations far away from each other• Scale effects and measurement pitfalls – Cities may be represented as points or polygons – Results depend on the scale at which the analysis is conducted: province or county – MAUP—scale effect• Non-uniformity of Space – Phenomena are not distributed evenly in space – Be careful how you interpret results!• Edge issues – Edges of the map, beyond which there is no data, can significantly affect results• Modifiable areal unit problem (MAUP-zone ) – Results may depend on the specific geographic unit used in the study – Province or county; county or city• Ecological fallacy – Results obtained from aggregated data (e.g. provinces) cannot be assumed to apply to individual people – MAUP—individual effect Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Potentials: Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Potentials: …it teaches us more about what we are studying. [1] Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Potentials: …it teaches us more about what we are studying. [1] …to avoid misspecification in our models; build better models. (missing variables, better marginal effects, measurement error) [2] Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Potentials: …it teaches us more about what we are studying. [1] …to avoid misspecification in our models; build better models. (missing variables, better marginal effects, measurement error) [2] …to adhere to statistical assumptions. [3] Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Potentials: …it teaches us more about what we are studying. [1] …to avoid misspecification in our models; build better models. (missing variables, better marginal effects, measurement error) [2] …to adhere to statistical assumptions. [3] To be hip! To be quantitative! …and learn more about spatial data analysis. [4] Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials and pitfalls.Pitfalls: Many of the standard techniques and methods documented in standard statistics textbookshave significant problems when we try to applythem to the analysis of the spatial distributions. Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? …the potentials. TFLG: “All things are related, but nearby things are more related than distant things” W.R.Tobler, 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography 46: 234-240 Richard Heimann © 2013Thursday, February 21, 13
    • What is Special about Spatial??? Pitfalls: Paradoxically Spatial autocorrelation (TFLG) Many of the standard techniques and methods documented in standard statistics textbooks have significant problems when we try to apply them to the analysis of the spatial distributions. Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation It DOES violate the assumptions traditional statistics… Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation It DOES violate the assumptions traditional statistics… Units of analysis might not be independent Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation It DOES violate the assumptions traditional statistics… Units of analysis might not be independent Estimated error variance is biased, which inflates the observed R 2 values. Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation It DOES violate the assumptions traditional statistics… Units of analysis might not be independent Estimated error variance is biased, which inflates the observed R 2 values. If spatial effects are present, and you don’t account for them, your model is not accurate! Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Spatial autocorrelation (TFLG) Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Spatial autocorrelation (TFLG)The nonrandom distribution of phenomena in space has various consequences for conventional statistic analysis. Traditional statistics often assume independent and identically distributed (i.i.d.) Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Spatial autocorrelation (TFLG)The nonrandom distribution of phenomena in space has various consequences for conventional statistic analysis. Traditional statistics often assume independent and identically distributed (i.i.d.)1)Biased parameter estimates Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Spatial autocorrelation (TFLG)The nonrandom distribution of phenomena in space has various consequences for conventional statistic analysis. Traditional statistics often assume independent and identically distributed (i.i.d.)1)Biased parameter estimates2)Data redundancy (affecting the calculation of confidence intervals) Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation Spatial Heterogeneity ‘Second’ Law of Geography (Goodchild, 2003) Richard Heimann © 2013Thursday, February 21, 13
    • Simpson’s Paradox Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Simpson’s Paradox ‘Second’ Law of Geography (Goodchild, 2003)Global Models may be inconsistent with regional models (i.e. Spatial Simpson’s Paradox) Global standards will always compete with local standards Crime in the north Crime in the north Crime Crime in the south Crime in the south Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation Statistical Inference for Spatial Data An important consequence of spatial dependence is that statistical inferences on this type of data won’t be as efficient as in the case of independent samples of the same size. In other words, the spatial dependence leads to a loss of explanatory power. In general, this reflects on higher variances for the estimates, lower levels of significance in hypothesis tests and a worse adjustment for the estimated models, compared to data of the same dimension that exhibit independence. Generally lower p values are required… Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Statistical Inference for Spatial Data Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls. Statistical Inference for Spatial Data TFLG: “All things are related, but nearby things are more related than distant things” Then what is Negative Spatial Autocorrelation? / Type II Error or is it possible? Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls [scale]. …when should we accept it? Census Tracts (White Population) Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls [scale]. …when should we accept it? Census Tracts (White Population) Counties (White Population) Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Autocorrelation …the pitfalls [fractals]... …Spatial Autocorrelation is scale dependent. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Gregory Bateson, in "Form, Substance and Difference," from Steps to an Ecology of Mind (1972), elucidates the essential impossibility of knowing what the territory is, as any understanding of it is based on some representation: We say the map is different from the territory. But what is the territory? Operationally, somebody went out with a retina or a measuring stick and made representations which were then put onpaper. What is on the paper map is a representation of what was in theretinal representation of the man who made the map; and as you push the question back, what you find is an infinite regress, an infinite series of maps. The territory never gets in at all. […] Always, the process of representation will filter it out so that the mental world is only maps of maps, ad infinitum. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Another basic quandary is the problem of accuracy. In "On Exactitude in Science", Jorge Luis Borges describes the tragic uselessness of the perfectly accurate, one-to-one map: In time, those Unconscionable Maps no longer satisfied, andthe Cartographers Guild drew a Map of the Empire whose size was that of the Empire, coinciding point for point with it. The following Generations, who were not so fond of the Study of Cartography saw the vast Map to be Useless and permitted it to decay and fray under the Sun and winters. In the Deserts of the West, still today, there are Tattered Ruins of the Map,inhabited by Animals and Beggars; and in all the Land there is no other Relic of the Disciplines of Geography.http://en.wikipedia.org/wiki/On_Exactitude_in_Science Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls.http://www.theatlantic.com/technology/archive/2013/02/the-geography-of-happiness-according-to-10-million-tweets/273286/ Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. …the pitfalls [fractals]... Unit = 200 km, length = 2400 km Unit = 50 km, length = 3400 km Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Population Illiterates per capita >60 years income Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Population Illiterates per capita >60 years income Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Scale Effects and Measurement Pitfalls. Richard Heimann © 2013Thursday, February 21, 13
    • Non-Uniformity of SpaceCranshaw, J., Schwartz, R., Hong, J., & Sadeh, N. (2012). The livehoods project: Utilizing social media to understand the dynamics of a city. … the Advancement of Artificial …. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM12/paper/download/4682/4967 Richard Heimann © 2013Thursday, February 21, 13
    • Non-Uniformity of Space AKA: Intrinsic heterogeneity Richard Heimann © 2013Thursday, February 21, 13
    • Non-Uniformity of Space Richard Heimann © 2013Thursday, February 21, 13
    • Non-Uniformity of Space http://www.hss.caltech.edu/~camerer/Ec101/JudgementUncertainty.pdf Richard Heimann © 2013Thursday, February 21, 13
    • Edge Effects. Edge effects arise where an artificial boundary is imposed on a study, often just to keep it manageable. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit ProblemA classic early paper is Gehlke and Biehl (1934) who found that the magnitude of the correlation between two variables tended to increase as districts formed from Census tracts increased in size. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem Waller & Gotway (2004) describe it as a "geographic manifestation of the ecological fallacy in which conclusions based on data aggregated to a particular set of districts may change if one aggregates the same underlying data to a different set of districts". Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem (on Robinson 1950)  ...for each of the 48 states in the US as of the 1930 census, he computed the literacy rate and the proportion of the population born outside the US. He showed that these two figures were associated with a positive correlation of 0.53 — in other words, the greater the proportion of immigrants in a state, the higher its average literacy. However, when individuals are considered, the correlation was 0.11 — immigrants were on average less literate than native citizens. Robinson showed that the positive correlation at the level of state populations was because immigrants tended to settle in states where the native population was more literate. He cautioned against deducing conclusions about individuals on the basis of population-level, or ecological data Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem The paper by Openshaw and Taylor (1979) described howthey had constructed all possible groupings of the 99 Countiesin Iowa into larger districts. When considering the correlation between %Republican voters and %elderly voters, they could produce "a million or so" correlation coefficients. A set of 12 districts could be contrived to produce correlations that ranged from -0.97 to +0.99. 99 counties of Iowa % Republican voters, % over 65 48 regions: -.548 to +.886 12 regions: -.97 to +.99 Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem x y Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit ProblemOpenshaw and Taylor (1979) showed that with the same underlying data it is possible to aggregate units together in ways that can produce correlations anywhere between -1.0 to +1.0. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem Scale issue: involves the aggregation of smaller units into larger ones. Generally speaking, the larger the spatial units, the stronger the relationship among variables or often a reverse in autocorrelation. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem Modifiable Area (aka Zonal Problem): Units are arbitrary defined and different organization of the units may create different analytical results. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem The choice of an appropriate scale for the study of spatial processes is an extremely important one because mechanisms vital to the spatial dynamics of a process at one scale may be unimportant or inoperative at another. Moreover, relationships between variables at one scale may be obscured or distorted when viewed from another scale. This is particularly true in the study of human, animal, and plant populations and has led many researchers in agriculture, geography, sociology, statistics, ecology, and the earth and environmental sciences to consider scale issues in detail Richard Heimann © 2013Thursday, February 21, 13
    • Ecological Fallacy The Ecological Fallacy is a situation that can occur when a researcher or analyst makes an inference about an individual based on aggregate data for a group. (Reference: http://jratcliffe.net/research/ecolfallacy.htm) Richard Heimann © 2013Thursday, February 21, 13
    • Ecological Fallacy Example: We might observe a strong relationship between income and crime at the county level, with lower-income areas being associated with higher crime rate.Conclusion:1) Lower-income persons are more likely to commit crime2) Lower-income areas are associated with higher crime rates3) Lower-income counties tend to experience higher crime rates Richard Heimann © 2013Thursday, February 21, 13
    • Ecological Fallacy Is there a relationship between Ecological Fallacy & MAUP? Richard Heimann © 2013Thursday, February 21, 13
    • Ecological Fallacy Is there a relationship between Ecological Fallacy & MAUP?The smoothing effect that results from averaging is the underlying cause of both the scale problem in the MAUP and aggregation bias in ecological studies. As heterogeneity among units is reduced through aggregation, the uniqueness of each unit and the dissimilarity among units is also reduced. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem In the 2000 U.S. presidential election, Al Gore, with more of the population vote than George Bush, but failed to become president. Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem http://press.princeton.edu/titles/9030.html Richard Heimann © 2013Thursday, February 21, 13
    • Modifiable Areal Unit Problem Richard Heimann © 2013Thursday, February 21, 13
    • Ecological Fallacy Is there a converse to Ecological Fallacy? Conclusions regarding spatial grouped data being sought based on the measured characteristics of sampled individuals? If so, the sample must be entirely or highly representative of the grouping in order to avoid the so-called atomistic fallacy — ascribing characteristics to members of a group based on a potentially unrepresentative sample of members Richard Heimann © 2013Thursday, February 21, 13
    • Observational Studies Richard Heimann © 2013Thursday, February 21, 13
    • Observational Studies Richard Heimann © 2013Thursday, February 21, 13
    • Observational Studies Richard Heimann © 2013Thursday, February 21, 13
    • …the pitfalls(ish). Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Analysis is harder than SabermetricsThiel, J., & Hogan, J. (2011). The Statistical Irrelevance of American SIGACT Data: Iraq Surge Analysis Reveals Reality. Retrieved from http://oai.dtic.mil/oai/oai?verb=getRecord&metadataPrefix=html&identifier=ADA546546 Richard Heimann © 2013Thursday, February 21, 13
    • Spatial Analysis - The Primitives. Questions? Richard Heimann © 2013Thursday, February 21, 13
    • Personal Notes Richard Heimann Office: UMBC Common Faculty Area 3rd Floor Phone: 571-403-0119 (C) Office hours: Tues. 6:30-7:00 (Virtual); or by appointment (send e-mail) I promptly respond to emails. Phone calls are another matter. Email: rheimann@umbc.edu or heimann.richard@gmail.com Richard Heimann © 2013Thursday, February 21, 13
    • Thank you… Data Tactics Corporation https://www.data-tactics-corp.com/ http://datatactics.blogspot.com/ Twitter: @DataTactics Rich Heimann Twitter: @rheimann Richard Heimann © 2013Thursday, February 21, 13