Thematic Maps & GIS in Economic Geography

Domenico de Vincenzo – Mapping Complexity

• Peter Haggett highlights maps’ crucial role in geography, emphasizing that geographers produce and analyze maps, encoding and decoding them to identify themes.

Thematic Maps, GIS, and Economic Geography

• Cartography and geography share a strong relationship, as thematic maps are closely linked to economic geography.
• Cartography advanced from manual map creation with simple representations to spatial analysis using maps.
• Automatic or numerical cartography emerged with computer programs, facilitating the creation of Geographic Information Systems (GIS).
• Traditional thematic cartography is descriptive, using maps as final products, whereas automatic cartography and GIS provide tools for data analysis.
• GIS uses mathematical-statistical resources to analyze territorial phenomena.
• The process of the quantitative revolution introduced statistical analysis and predictive models into economic geography.
• Spatial analysis utilizes geographic information systems in a dynamic thematic cartography.
• The map becomes both a tool and result of spatial analysis that uses quantitative methods.
• Maps offer a synoptic representation of data, revealing spatial structures and properties not initially measured.

From Representation to Analysis

• Cartography shifted from pedagogical use to a research tool.
• Early thematic cartography focused on location and graphic representation with a key issue being the graphic quality of a map.
• Modern thematic cartography emphasizes the production of new data, making maps both output and input.
• GIS enabled autonomous technical management of statistical and cartographic data.
• Traditional thematic cartography favored caution to minimize effort.
• With automatic cartography and GIS, choices can be altered decisively during construction.
• There is a risk of distorted interpretation of results due to inadequate cartographic technique training for GIS users.
• The learning path should be: general cartography, thematic cartography, and then GIS.

Thematic Maps

• A map is a reduced, approximate, and symbolic representation of reality that employs an adequate reduction ratio, known as the scale, cartographic projections and symbols.
• Thematic maps represent phenomena differently distributed in a region, including both concrete and immaterial elements, qualitative and quantitative natures, and their changes.
• Classifying thematic maps by data quality yields maps of concrete facts/positions and maps using abstract data from averages/ratios.
• First type of maps includes representations by points, lines, and areas.
• Second type of maps combines cartodiagrams, isopleth/choropleth curves, isometric curves/isolines, synthetic maps, and synthesis maps reflecting mathematical synthesis and geometric principles.
• Maps can be categorized based on the phenomenon: distribution maps (punctual), networks maps (linear), and choro-chromatic maps (areal).
• Static maps represent homogeneous areas or point distributions as a state, while dynamic maps depict spatial flows or temporal evolution.
• Levels of Measurement:
  • Nominal: Data is labeled, but not ordered or spaced.
  • Ordinal: Data can be ordered along a scale, but spacing is undefined.
  • Interval-based: Distances are defined between categories using equal units.
• Unwin proposes a typological breakdown of maps based on the type of data used (point, line, area or surface).
• Data from the last two levels can be used in arithmetic and statistical operations

The Cartographic Scale and the Geographical Scale

• The cartographic scale is the ratio between distances on a map and real distances, expressed as a ratio.
  • For example, a 1:10,000 scale means 1 cm on the map equals 10,000 cm (100 meters) in reality.
• Graphic scales maintain constant real distance ratios even with map resizing.
• Map scales include:
  • Small-scale: Representing large territories (less than 1:150,000).
  • Large-scale: Used for smaller areas (greater than 1:150,000).
  • Very large-scale: City plans and cadastral maps (greater than 1:10,000).
• The geographical scale is the scale at which territorial phenomena are analyzed.
• The geographical scale uses terms like local or regional, impacting the meanings and intensities.
• Trans-scale analyses link all reading levels to highlight relationships.

Point Maps

• Dot maps represent discrete phenomena, using points with individual or group values; the points often mark centroids to which more widely distributed elements are associated.
• Symbols used in dot charts include:
  • Pictograms
  • Ideograms
  • Conventional signs
  • Proportional sumbols
• Symbolic signs recall something else and are placed accurately.
• Pictograms are understandable symbols recalling facts.
• Ideograms are symbols representing ideas.
• Conventional signs are diagrams that help identify objects too small to recognize.
• Point systems can be defined as point types with grain selection depending on assigned values or classes.
• Technical systems assign point types with grain selection.
• Point maps with proportional symbols use variable symbol sizes proportionate to data values.
• Geometric figures such as circles, squares, and triangles with identifiable centers are used for greater precision.
• Radius ® of a circle is found by r = square root of (S/π).
• Replacing π with the minimum unit in above equation facilitates dimension proportion to point value.
• Point symbols represent growth or decline with colors; for example, circles might represent employees in Frosinone, with red for positive and blue triangles for negative values.

Spatial Structure Through Point Maps

• Territorial organization is evaluated through element distribution and evolving spatial structures.

• The simplest way to read a spatial structure is by transforming the elements into points.

• Density and dispersion can be deduced.

• *Structure: way the individuals arrange with repsect to each other

• *Dispersion : positions of the individuals with respect to the area that is been observed

• *Density : ratio between the number of individuals and the area that is studied *

• Describing distributions based on absolute positions in space makes the operation more complex.

• The first square can have high density as comapred to the second and a comparison can describe how the structure relates to that

• Dispersion needs no comparision but looking at the image, it catches the eye that individuals have a certain concentration

• The spatial organization is verified through point maps of Apulia, Campania and Veneto.

• Municipal centroids are represented wihin area of same extension.

• Apulia, Campania and Veneto show distinct distributions.

• Density calculation appreciated via the formula D= p/s, p is the population that is the number of centroids whiles s is the surface area.

• Density varies in each of the zones 7, 44 and 65 cites per 1000 km

• Evaluation by visual density reveals density differences.

• Unique density becomes obvious between cases with similar dispersion that structure differently.

Population Distribution

• Population distribution maps use absolute population and spatial placement via proportional circles, spheres, etc.
• Precise maps distinguish dispersed from centralized populations.
• Representation precision depends on scale with dispersed vs centralised variations.
• Population Distribution Map by the CNR of the province of Milan is still useful to study.
• Interval/ratio levels are presented since each point represents the value that corresponds with the Real One.
• Spheres are used instead of circles since the volume makes correspondence closer to a real extension.
• The scattered population is known through dots.

Line Maps

• These maps depict linear phenomena such as roads, waterways, or power lines.
• Interest lies not in the lines, but rather connections between elements, quantity and direction of flows, and phenomena causing connections.
• Flows are representable schematically without considering transport routes, based on size.
• The line structure can summarize a transport network or airline destinations.
• Graphs that are geometrical figure and logical tools are often used.
• The graph can reconstruct virtual networks (web pages, mental process logical organization, electrical circuits, etc.).

The Graph

• The graph simplifies a transport/communication network.
• Topology involves assessing network connectivity.
• Quality can be measured based on routes and how those routes actually flow
• Vertices and Nodes in a graph can be an edge or arc, in the transit it can be town, city, railways.
• The Nodes are what are connecting each transport
• Types of graphs:
  • Null
  • Linear
  • Tree-like
  • Polarised
• Tree Graphs in particular has the path branched that allows multiple nodes to be connected but have no circiuit
• The Polarized on has all edges converge to a certain node.
• Regardless the length or shape all routes have accsessibility and connectivity. Which can be measured.
• Connectivity indicates nodes linked to all others (i.e., links with connections)
• For Transport Routes it is simplest to connect Nodes with Tree-Graphs
• For Communications the Polaries are used

Connectivity and Accessibility

• Cyclomatic number (µ) measures the accessibility of a network and is calculcated using the equation: (1) µ = S – V + g
  • The variables are the edges (S) vs vertices and Number of subgraphs (g)
• Measuring with S = 9 , V= 9 and G = 1 measures one circuit
• Beta Index is another way of measuring connection given ration Between number of edges and Vertices
• If we connect beta to graph its 1 and gives 11.1%
• Formula Beta Max calculates max number of 3 multiplied the function vertices -2 divided total vertices
• Measuring this with Formula Beta Max results in 1.8
• Accessibility and connectivity of entire network can be measured and indicated in the formula A:z Matrix.
• A double matrix can construct with the nodes progressively numbered.
• Presence of connections between nodes helps measure how it correlates to the double-entry table
• Final connectivity is determined by number of connections which is measured from matrix A1 which correlates to figure. For example Nodes have connectivity 2 that helps find two Edges from node
• Node 8 has 4 connections that makes it the most optimal connections to those in the Graph
• The avg connectivity helps with each individual nod and the node = 2
• With value of 2 what is been described is a the avergae graph based

Measuring edges

• Accessibility of indivdual is calculate by measured is each node connects to reach from another node.
  • E.g reaching Node 5 requires three transverses.
• Transpired number in matrix B(1).

Flow Maps

• Line use can show Flow intensity with goods flow being the top of the mind, with amount taken into consideration.
• Flows are not strictly linked to communications routes in example the technology can be the phone

How to measure the average from A and B

• Given the cars traverse highways both directions its easily to demonstrate with both the graphical representation since both flows easily can be shown
• Both flows show the cars going one or the other
• Motor vehicle can be shown using proportionally accurate dimensions to measure its flow
• The main way to look at traffic flow of the motorway involves different tell-paths , to evaluate what has happen one direction to and fro we calculate if those from the prior toll booth we see those exist toll and to make what comes close.
• So the real traffic can be measure by a certain unit that reflects flow and directional with the size.
• You can build a circuit between these roads and toll paths
• A transformation can turn a linear graph into circuit graph or Origin /Destiny metrics to show flow.
• A linear graph is turned in circuit that helps connect to area

Providing Reach

• Hierarchy or Terriroriality can use to state which factors determine importance
• An evalution for which way has the higher reach with potential
• From certain point the destiny flows has the highest percentage based the formula 2 A *

The flow of tolls can help with points 16 to 15

• Important central point for flows is easy to establish with which tools are most attractive this was
• An indicator
• Apply which territorial hierarchy with O/D metrics with data from 2003
• There three factors as a result which is the three main sectors with attraction in the province for Pesaroi ,Urbino,Fano.
• A chart help reflect where certain tolls intersect based on commuters and data from years Prior that gives the best reflection possible of a sector, by analysing which ways have the highest percentage for Commuters for that given Area.
• This was the highest points and central aspects of that given factor.
• Is the central indicator and most significant area and to a certain degree the motorways are the most essential

Area Maps

• They Represent phenomena that shows certain dimensions and are usually and simply understandable easy to measure.
• Most cases have incorrect reading and can compromise the reading.
• Two types
• Area vs Position maps
• According W classification area known has known as level because map places the map with phenomena located.
• For an region they can describe that
• Also delimits where certain languages are usually the standard and use .
• Determined by shape and what is present from data .
• At level knowns derived
• Relationship area certain area.
• Heightlight yields from harvest
• Choroplepath come shapes that come with regular mesh or irregular but subjects that the searcher knows
• Regular used because Analysing is essential because these can see in each of the area analysis.
• The territories have difference and certain variables also .But influence and change in the presentation of Data.
• By giving the shade or Screen and background this changes perspective and give each of elements a certain meaning.
• Choice depends on designer