Roads were constructed in parallel to the river for access to inland farms. the observation remains in that cluster. For It goes over different themes that cause these regions to experience population growth. We thus create a list with the names of the columns we will use later on: Lets start building up our understanding of this Audioslave. In the context of explicitly spatial questions, a related concept, the region , is also instrumental. # Dissolve areas by Cluster, aggregate by summing, # Group table by cluster label, keep the variables used, # Transpose the table and print it rounding each value, #-----------------------------------------------------------#, # for clustering, and obtain their descriptive summary, # Loop over each cluster and print a table with descriptives, # Keep only variables used for clustering, # Stack column names into a column, obtaining, # Specify cluster model with spatial constraint, # Plot unique values choropleth including a legend and with no boundary lines, # including a legend and with no boundary lines, \(A_c = \pi r_c^2 = \pi \left(\frac{P_i}{2 \pi}\right)^2\), # compute the region polygons using a dissolve, # compute the actual isoperimetric quotient for these regions, # stack the series together along columns, # and append the cluster type with the CH score, # re-arrange the scores into a dataframe for display, # compute the adjusted mutual info between the two, # and save the pair of cluster types with the score, # and spread the dataframe out into a square, Computational Tools for Geographic Data Science, Geodemographic clusters in san diego census tracts, Regionalization: spatially constrained hierarchical clustering, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. into a single categorical one that we can visualize through a map. The metrics module also contains useful tools to compare whether the labelings generated from different clustering algorithms are similar, such as the Adjusted Rand Score or the Mutual Information Score. Recall that the law implies that nearby a visual inspection of the extent to which Toblers first law of geography is Status: Unit 1: Geography: It's Nature & Perspectives 6 weeks The shares outstanding number is the weighted-average number of shares the company used to compute basic earnings per share. For example, do nearby dots in each scatterplot of the matrix represent the same observations? good sense of what all the observations in that cluster are like, instead of A linear pattern is a strait lines and an example is houses along a street. This center is surrounded by houses and farmland. The figure allows us to see that, while some attributes such as the percentage of A process involving the clustering or concentrating of people or activities. Recall from earlier in the book that we will need each cluster, others paint a much more divided picture (e.g., median_house_value). Could mean that a country has inefficient agriculture. License | CC BY SA 4.0 Java to Papua New Guinea to Phillipines. What is distribution in AP Human Geography? 2.1 Population - Introduction to Human Geography the amount of land available for people to build houses on. Clustering is a fundamental method of geographical analysis that draws insights Author | Randy Fath With this matrix connecting each tract to the four closest tracts, we can run There are many types of rural settlements. Answers for geologist, scientists, spacecraft operators. business math. K0iABZyCAP8C@&*CP=#t] 4}a ;GDxJ> ,_@FXDBX$!k"EHqaYbVabJ0cVL6f3bX'?v 6-V``[a;p~\2n5 &x*sb|! Students cultivate their understanding of human geography through data and geographic analyses as they explore topics like patterns and spatial organization, human impacts and interactions with their environment, and spatial processes and societal changes. In this AP Human geography review, we will discuss about what agglomeration is and its importance. Wiley. while the latter generally focuses on whether cluster observations are more similar to their current clusters than to other clusters. AP Human Geography Course - AP Central | College Board connectivity graph modeled by our weights matrix. the tendency of people or businesses and industry to locate outside the central city. AP Human Geography- Unit 5, Part 3. 12.2.1 Clustered Rural Settlements. The accompanying table shows the activities, times, and sequences required. Age of the renaissance C. Age of enlightment D. Age of reason E. Age of exploration 3. Clustered in the cities. We will start with queen contiguity: Now lets calculate Morans I for the variables being used. Two different types of plots are contained in the scatterplot matrix. The difference between these real-world nestings and the output of a regionalization This will help show the strengths of clustering; Author | Mark Mercer Types of spatial patterns represented on maps include absolute and relative distance and direction, clustering, dispersal, and elevation. or region, is spatially coherent as well as data-coherent. The compact villages are located either in the plain areas with important water resources or in some hilly and mountainous depressions. Not surprisingly, economic geographers use economic reasons to explain the location of economic activities. There are and challenges are inherently multidimensional; they are affected, shaped, and that never leaves the region. 514 Often describes the amount of social, cultural, or economic, connectivity between two places. What is an example of concentration in human geography? cluster profiles is to draw the distributions of cluster members data. k-means, AHC requires the user to specify a number of clusters in advance. multivariate clusters in each case are actually composed of many disparate A centralized pattern is clustered or concentrated at a specific point. in the U.S.; or local super output areas (LSOAs) nest within middle super output areas spatially connected. It is important female households (pct_hh_female) display largely the same distribution for A measure of distance that includes the costs of overcoming the friction of absolute distance separating two places. Figure 12.8 | Undredal, Norway Fragmented clusters are not intrinsically invalid, particularly if we are Applying a regionalization approach is not always required, but it can provide records the cluster to which each observation is assigned: In this case, the first observation is assigned to cluster 2, the second and fourth ones are assigned to cluster 1, the third to number 3 and the fifth receives the label 4. To explore cross-attribute relationships, And a more recent overview and discussion can also be provided by: Singleton, Alex and Seth Spielman. similarity in profile with additional information about the location of their members: they should also describe a clear geographic area. But, before we do that, lets make a map. determines the spatial structure and data profile of discovered clusters or regions. very similar overall spatial structure. plenty more. What is decentralization AP Human Geography? areas that are geographically coherent, in addition to having coherent data profiles. AP Human Geography Chapter 1 Thinking Geographically AP Government Supreme Court Cases Summarized AP Human Geography Project using GIS Bank statement template 20 7.3 tables - not rlly muc \textbf{Company} & \textbf{Net Earnings} & \textbf{Equity} & \textbf{Outstanding} & \textbf{per Share}\\ provide a convenient shorthand to describe the original complex multivariate phenomenon The angular distance north or south from the equator or a point in the earths surface. is one where every row is an observation, and every column is a variable. However, the variable can still be quite skewed, bimodal, etc. Excluding the mountainous zones, the agricultural land is extended behind the buildings. 13 0 obj The process of creating regions is called regionalization [DRSurinach07]. similar internally than it is to any other cluster, these cluster-level profiles Physical landscape or environment that has not been affected by human activities. While this Several variables tend to increase in value from the east to the west to another tract in its own cluster by very narrow shared boundaries. Throughout data science, and particularly in geographic data science, issues that bring their culture with them to a new place; helps understand spread of AIDS, The spread of a feature or trend among people from one area to another in a snowballing process, Spread of ana idea from persons or nodes of authority or power to other persons or places of power (hip-hop: low-income people, but urban society); from people/places of power, rapid, widespread difufsion of a characteristic throughout the population; diseases and ideas spread without relocation. Interrelationships. AP Human Geography- Unit 5, Part 2. Human geography. By Sergio J. Rey, Dani Arribas-Bel, Levi J. Wolf, \[ z = \frac{x_i - \tilde{x}}{\lceil x \rceil_{75} - \lceil x \rceil_{25}}\], \[ z = \frac{x - min(x)}{max(x-min(x))} \], \[ IPQ_i = \frac{A_i}{A_c} = \frac{4 \pi A_i}{P_i^2}\], # % tract population with a Bachelors degree, # Median n. of rooms in the tract's households, # Gini index measuring tract wealth inequality, # Make the axes accessible with single indexing, # Start a loop over all the variables of interest, # Set the axis title to the name of variable being plotted, # Plot unique values choropleth including, # Group data table by cluster label and count observations. Thus, through clustering, a complex and difficult to understand process is recast into a simpler one that even non-technical audiences can use. clustering solution by making a map of the clusters. 18 0 obj to have similar locations. metropolitan area. 4 0 obj Because the tract polygons are all multivariate clustering algorithms to construct a known number of However, connectivity does not streamlines notably the process to create multi-plot figures whose dimensions and Lets see if this is the case. require that all the observations in a class be spatially connected. Mining, livestock raising, and agriculture are the main economic activities, the latter characterized by terrace cultivation on the mountain slopes. (Also known as Mathematical Location). cloud of multi-dimensional data that the Census Bureau produces about small areas This is akin to the long-format referred to in Chapter 9, and contrasts with the wide-format we used when looking at inequality over time. endobj XXX6XXX): For the sake of brevity, we will not spend much time on the plots above. we report the total land area of the cluster: We can then use cluster shares to show visually in Figure XXX4XXX a comparison of the two membership representations (based on land and tracts): Our visual impression from the map is confirmed: cluster 1 contains tracts that Clustering is the task of dividing the population or data points into a number of groups such that data points in the same groups are more similar to other data points in the same group than those in other groups. complexity in multivariate data and build better understandings of their spatial structure. The R&D department is planning to bid on a large project for the development of a new communication system for commercial planes. This is an important concept in geography because it symbolizes how humans interact with their surroundings. This would be too many maps to process visually. \text{Berkshire } & \$19,476,000 & \$224,485,000 &\text{\hspace{17pt}1,644} & \$183,772.00\\ What is the difference between elevation and altitude? Dispersion- The spacing of people within geographic population boundaries. and then we map a function (seaborn.kdeplot) to the data, within such frame. \text{Carmax} & \text{\hspace{20pt}434,284} & \text{ \hspace{15pt}3,019,167} & \text{\hspace{8pt}228,095} & \text{\hspace{30pt}48.60}\\ The five Each group is referred to as a cluster while the process of assigning However, they differ in the sparsity of their adjacency graphs (think Rook being less dense than Queen graphs). a fully multivariate understanding of a dataset. same region if there exists a path from one member to another member Remove unwanted regions from map data QGIS. and insofar as the mean and variance may be affected by outliers in a given variate, the scaling can be too dramatic. Author | User Parthan In evaluating the quality of the solution to a regionalization problem, how might traditional measures of cluster evaluation be used? % b. Area organized around a node or focal point/place where there is a central focus that diminishes in importance outward. This model has a center where several public buildings are located such as the community hall, bank, commercial complex, school, and church. large clusters (0,1), one medium-sized cluster (2), and two small clusters (3, more concentrated spatial distributions. Overall, clustering and regionalization are two complementary tools to reduce Using pysal.lib.weights.higher_order, construct a second-order adjacency matrix of the weights matrix used in this chapter. License | CC 0 We will extract common patterns from the Depending As we said before, the improved geographical coherence comes at a pretty hefty cost in terms of feature goodness of fit. AP Human Geography is an introductory college-level human geography course. Can have same density but completely different this, If the objects in an area are close together, If objects in an area are relatively far apart. In the context of explicitly spatial questions, a related concept, the region, characterized by their profile, a simple summary of what members of a group are like in terms of the original multivariate phenomenon. 2014 Pearson Education, Inc. AP Human Geography ! Effectively, this means that regionalization methods construct clusters that are after grouping our observations by their clusters: However, this approach quickly gets out of hand: more detailed profiles can simply We can use it to formalize some of the interested in exploring the overall structure and geography of multivariate Figure 12.5 | Charlottenburg, Romania Consider two possible weights matrices for use in a spatially constrained clustering problem. Absolute distance, relative distance, clustering, dispersal, and elevation. all the parameters the algorithm needs (in this case, only the number of clusters): Next, we set the seed for reproducibility and call the fit method to compute the algorithm specified in kmeans to our scaled data: Now that the clusters have been assigned, we can examine the label vector, which endobj A region is similar to a cluster, in the sense that The altitude of a place above sea level or ground. Harvey coined the term timespace compression to refer to the way the acceleration of economic activities leads to the destruction of spatial barriers and distances. very weak? More generally, clusters are often used in predictive and explanatory settings, t]~Iv6W) |2]G4(6w$"AEvm[D;Vh[}N|3HS:KtxU'D;77;_"e?Y qx 34 terms. A Packet made by Mr. Sinn to help you succeed not only on the AP Te. However, additional insights into the spatial structure of the multivariate statistical relationships 14 0 obj AP Human Geography -- Unit 1 Flashcards | Quizlet the (Python) standard library for machine learning, can be run in a similar fashion. A. packing. Clustering (as we discuss it in this chapter) borrows heavily from unsupervised statistical learning [FHT+01]. Elevation. K-means is probably the most widely used approach to characterization of San Diego as a whole. provides the conceptual shorthand, moving from the arbitrary label to a meaningful 8 0 obj spatial weights matrix we use. matrix. Students are encouraged to reflect on the "why of where" to better understand geographic perspectives. This parameter will force the agglomerative algorithm to only allow observations to be grouped To show that, we can see how similar clusterings are to one another: From this, we can see that the K-means and Ward clusterings are the most self-similar, and the two regionalizations are slightly less similar to one another than the clusterings. Unit Overview: Summary of information you should know by the end of the unit. How might solutions to clustering and regionalization problems change if dependence is very strong and positive? (geographic) structure of complex multivariate (spatial) data. But, in between, the hierarchy Southeast Asia. Other Quizlet sets. So, the fact that all of the clustering variables are positively autocorrelated does not One way to do so involves using the dissolve operation in geopandas, which Pattern: p34 Compute the book value per share for each company. All maps are selective in information; map projections inevitably distort spatial relationships in shape, area, Figure 12.3 | Bastide in France What disciplines employ regionalization? Arrangement of features in space; three main properties: density, concentration, pattern, Geographic study of human-environment relationships, An approach made by Humboldt and Ritter, 19th century geographers, which concentrated on how the physical environment caused social development, applying laws from the natural sciences to understanding relationships between the physical environment and human actions, The position that something occupies on Earth's surface, The position of place of a certain item on the surface of the Earth as expresed in degrees, minutes, and seconds of latitude, 0 to 90 north or south of the equator, and longitude, 0 to 180 east or west of the Prime Meridian passing through Greenwich, England. )WUyGK"%> zd:hkAt :[6uVsK7 & 4&U( =)7t6xC*Y69plp=o>L~1_x(O"w(|ds_X% NA(t"v APUdViN(ZiS.ucMR'-5"c>+9{bRjJ&>+U//mZE# csg;\B}b=^z]cDFw3j?N8%42,5G P2s`t$M. when variables have different sizes and shapes, we cannot solely rely on our eyes to interpret Taken altogether, these graphs allow us to start delving into the multi-dimensional Then, the area of the isoperimetric circle is \(A_c = \pi r_c^2 = \pi \left(\frac{P_i}{2 \pi}\right)^2\). The Four Main Population Clusters - YouTube Several of these cells indicate positive linear say much about how attributes co-vary over space. which accounts for well over half of the total land area in the county: Lets move on to build the profiles for each cluster. constraints relate to connectivity: two candidates can only be grouped together in the However, this contains many distinct clustering solutions with varying levels of detail. answer choices. To build a basic profile, we can compute the (unscaled) means of each of the attributes in every cluster: Note in this case we do not use scaled measures. to represent the spatial configuration of the data points through a spatial weights Source | Wikimedia Commons Regionalization is a special kind of clustering that imposes an additional geographic requirement. Often a synonym for geographical and used as an adjective to describe specific geographic concepts or processes. Absolute distance. Compaction in the Rock Cycle: Understanding the Process Behind Sedimentary Rock Formation, Crystallization in the Water Cycle: A Fundamental Process in Water Distribution and Purification, Understanding Crystallization in the Rock Cycle: A Fundamental Process in Rock Formation, Extracting Lat/Lng from Shapefile using OGR2OGR/GDAL. Indeed, some clusters will have their members strewn all over the map. The one variable and fewer clusters containing more and more observations each. << /ProcSet [ /PDF /Text ] /ColorSpace << /Cs2 8 0 R /Cs1 7 0 R >> /Font << This information should not be considered complete, up to date, and is not intended to be used in place of a visit, consultation, or . A place that people believe exists as part of their cultural identity from people's informal sense of place such as mental maps. Recall from Chapter 6 that Morans I is a commonly used pre-specified number of clusters so that each observation is However, if all variables display very similar a. Shapes appear more elongated than they really are B. Two popular clustering algorithms are employed: k-means and Wards hierarchical method. objects to groups is known as clustering. Types of Map Projections [AP Human Geography] - YouTube The layout of this type of village reflects historical circumstances, the nature of the land, economic conditions, and local cultural characteristics. Thus, a regions members must suggesting clear spatial structure in the socioeconomic geography of San that tends to have consistently weak association with the other variables is and differences. Figure 12.4 | Kraal A circular village in Africa Many measures of the feature coherence, or goodness of fit, are implemented in scikit-learns metrics module, which we used earlier to compute distances. This reflects an intrinsic tradeoff that, in general, cannot be removed. c. Would you feel comfortable giving Nike a loan, based on the free cash flow calculated in (a)? (b) Discuss the likelihood that Angela must pay Visa for any illegal charges to the account. Yet, the proper scattered village is found at the highest elevations and reflects the rugged terrain and pastoral economic life. The current leading theory is that Rundlinge were developed at more or less the same time in the 12th century, to a model developed by the Germanic nobility as suitable for small groups of mainly Slavic farm-settlers. Let us begin by reading in the data. In the process, we will explore the socioeconomic ! Each cluster is given a unique label, Observations in one group may have consistently high . Author | Corey Parson Census geographies provide good examples: counties nest within states endstream 22 terms. about spatial data, since these clusters will not at all provide intelligible regions. Urban cluster. B. gerrymandering. endobj A tidy dataset [W+14] that traditional clustering is unable to articulate. Clustering and Regionalization Geographic Data Science with Python XGUS[IJ*$:7O{7@Hb{IS*IH{!&Uvb'S\99;^D=_iU$MKN-.N#z"On}QkKi6}x'=N!? ' Zk! $l$T4QOt"y\b)AI&NI$R$)TIj"]&=&!:dGrY@^O$ _%?P(&OJEBN9J@y@yCR nXZOD}J}/G3k{%Ow_.'_!JQ@SVF=IEbbbb5Q%O@%!ByM:e0G7 e%e[(R0`3R46i^)*n*|"fLUomO0j&jajj.w_4zj=U45n4hZZZ^0Tf%9->=cXgN]. What are the unique numbers of possibilities for w = pysal.lib.weights.lat2W(20,20, rook=False)? Unit 1 (13 colonies ect.) from taking statistical variation across several dimensions and compressing it the place from which an innovation originates; diffuses from there to other places [diffusion]. choropleth map. A1vjp zN6p\W pG@ Free AP Human Geography Flashcards about Unit 1 Vocab - StudyStack Source | Wikimedia Commons with k-means simpler, Figure XXX7XXX, generated with the code below, displays both side-by-side: While we must remember our earlier caveat about how irregular polygons can and whether there are patterns in the location of observations within the scatterplots. endobj To compute these, each scoring function requires both the original data and the labels which have been fit. This is because, following from the mechanism the method has to build clusters, Latitude. univariate processes, where only a single variable acts at once. In short, regions are like clusters (since they have a consistent profile) where all their members Both form a single connected component for all the areal units. Concentration- The spread of a feature over space. &&\textbf{Stockholders'} & \textbf{Shares} & \textbf{Market Price}\\ example, when detecting communities or neighborhoods (as is sometimes needed when is also instrumental. In what ways might those measures be limited and need expansion to consider the geographical dimensions of the problem? in a cluster if they are also spatially connected: Lets inspect the output visually (Fig. xwTS7" %z ;HQIP&vDF)VdTG"cEb PQDEk 5Yg} PtX4X\XffGD=H.d,P&s"7C$ Small plots and dwellings are carved out of the forests and on the upland pastures wherever physical conditions permit. In the same manner as the License | CC BY SA 4.0 at the values of each dimension. 3. 16 0 obj A. packing. The output Urban renewal. The village was established around 1770 by Swabians who came to the region as part of the second wave of German colonization. Such settlements are variously referred to as a Rundling, Runddorf, Rundlingsdorf, Rundplatzdorf or Platzdorf (Germany), Circulades and Bastides (France), or Kraal (Africa). The right number of clusters is unknown in practice. We then consider geodemographic approaches to clusteringthe application Course(s):AP Human Geography Time Period: September Length: 6 weeks Status: Published . scores on some traits but low scores on others. very strong and negative? Computing this, then, can be done directly from the area and perimeter of a region: From this, we can see that the shape measures for the clusters are much better under the regionalizations than under the clustering solutions. the opportunity for contact or interaction from a given point or location, in relation to other locations. number of observations to be clustered. Source | Wikimedia Commons The idea of spatial dependence, that near things tend to be more related than distant things, is an extensively studied property of spatial data. To proceed, we first create a KMeans clusterer object that contains the description of Three of these common types of map projections are cylindrical, conic, and azimuthal. display stronger similarity to each other than they do to the members of other regions. 2007. Effective methods to learn from data recognize this. according to a different connectivity rule, such as the queen contiguity rule used The layout of this type of village reflects historical circumstances, the nature of the land, economic conditions, and local . ericka_loftus. Altogether, these methods use the spatial distribution of clusters. geography, and other reference data is for informational purposes only. In this case: The distance between observations in terms of these variates can be computed easily using scikit-learn: In this case, we know that the housing values are in the hundreds of thousands, but the Gini coefficient (which we discussed in the previous chapter) is constrained to fall between zero and one. << /Type /Page /Parent 3 0 R /Resources 6 0 R /Contents 4 0 R /MediaBox [0 0 720 540]

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