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Environmental Data Types. Spatiotemporal Analysis.

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Presentation on theme: "Environmental Data Types. Spatiotemporal Analysis."— Presentation transcript:

1 Environmental Data Types

2 Spatiotemporal Analysis

3 Discrete Objects or Entities Objects with well-defined boundaries Points, lines, polygons and areas Objects or entities have attributes Can be mobile Biological organisms –Animals, trees Human-made objects –Vehicles, houses, fire hydrants Monitoring/Sensor Networks

4 Fields Properties that vary continuously over space –Value is a function of location –Property can be of any attribute type, including direction Elevation as the archetype –A single value at every point on the Earth’s surface –Any field can have slope, gradient, peaks, pits Grids Soil properties, e.g. pH, soil moisture Population density –But at fine enough scale the concept breaks down Identity of land owner –A single value of a nominal property at any point Name of county or state or nation Atmospheric temperature, pressure

5 Vector vs. Raster

6 Vector – Advantages and Disadvantages Advantages –Good representation of reality –Relatively compact data structure –Accurate graphics Disadvantages –Complex data structures –Some spatial analysis is difficult or impossible to perform

7 Raster – Advantages and Disadvantages Advantages –Simple data structure –Uniform size and shape –Computationally cheaper to process and store Disadvantages –Large amount of data –Less visually pleasing (“blocky”) –May lose information due to generalization –Projection transformation is difficult –Different scales between grids can make comparison difficult

8 Landcover Raster Grid Legend Mixed conifer Douglas fir Oak savannah Grassland (1-5) (6-10) (11-15) (16-20) 2 17 16 15 1411 1315 13 12 16 10 8 8 8 7 7 65 5 5 5 5 5 4 4 3 3 4

9 Raster = Grid columns rows The bounding box defines the geographic extent of the grid in terms of its coordinates Abbreviation for PICTURE ELEMENT, which is the smallest unit in an image. In raster based GIS systems, attribute information can be assigned to each pixel. Pixel Matrix of Equal-Area Cells 2 17 16 15 1411 1315 13 12 16 10 8 8 8 7 7 65 5 5 5 5 5 4 4 3 3 4

10 Grid File Format (ASCII) ncols 6 nrows 6 xllcorner 210 yllcorner 370 cellsize 20 nodata_value 0 5, 6, 7, 8, 10, 13 5, 7, 8, 10, 12, 13 4, 5, 8, 12, 15, 15 3, 4, 5, 13, 15, 16 3, 5, 11, 14, 15, 17 2, 4, 5, 16, 16, 17 2 17 16 15 1411 1315 13 12 16 10 8 8 8 7 7 65 5 5 5 5 5 4 4 3 3 4

11 Table Format XYValue 2203802 2204003 2204203 2204404 2204605 2204805 2403804 2404005 2404204 2404405 2404607 2404806

12 Triangulated Irregular Network (TIN) In a TIN, the world is represented as a network of linked triangles drawn between irregularly spaced points. TINs are an efficient way to store and analyze surfaces. Heterogeneous surfaces that vary sharply in some areas and less in others can be modeled more accurately, in a given volume of data, with a triangulated surfaces than with a raster because many points can be placed where the surface is highly variable, and fewer points can be placed where the surface is less variable.

13 Contoured Plots 2 17 16 15 1411 1315 13 12 16 10 8 8 8 7 7 65 5 5 5 5 5 4 4 3 3 4 Also known as an Isopleth Plot

14 Map Scale Map scale is based on the representative fraction, the ratio of a distance on the map to the same distance on the ground. Most maps used in GIS fall between 1:1 million and 1:1000. A GIS is scaleless because maps can be enlarged and reduced and plotted at many scales other than that of the original data. To meaningfully compare maps in a GIS, both maps MUST be at the same scale

15 Scale of a baseball earth Baseball circumference = 226 mm Earth circumference approx 40 million meters Scale is 1:177 million

16 Population Density County LevelCensus Tract Level

17 Resolution 25 meter5 meter 1 meter

18 Resolution 1 meter5 meter 25 meter

19 Dimensions 0-dimensional points and nodes 1-dimensional lines 2-dimensional (x,y) areas, polygons 3-dimensional (x, y, z) volumes 4-dimensional (x, y, z, t) 3-D and time

20 2.5 Dimensions

21 Types of Attributes Nominal – Simply identifies or labels an entity so that it can be distinguished from another. e.g. sensor ID, building name (Lopata House vs. Lopata Hall) –Cannot be manipulated using mathematical operations. However, frequency distributions are meaningful. Ordinal – Values based on an order or ranking, e.g. agricultural potential classes –Cannot be manipulated using mathematical operations. However, frequency distributions are meaningful. Interval – Differences between entities are defined using fixed equal units, e.g. Celsius temperature –Can be manipulated using addition and subtraction Ratio - Differences between entities can be defined using ratios, e.g. distance –Can be manipulated using multiplication and division Cyclic - differences between entities depend on direction, e.g. wind direction A common approach to classifying attributes is based on their level of measurement

22 Environmental Sensor Data Types In situ –Monitor or sensor makes measurements in the media being measured Air pollution or water quality networks Meteorological networks Field observations Remote sensing –Monitor or sensor makes measurements at a distance from the parameter being measured doppler radar aircraft imagery (orthophotos) satellite sensors

23 Thematic Data Commonly referred to as ‘Base layers’ Roads Rivers Political Boundaries Elevation (Topography) Land Cover Land Use

24 Principles of GIS

25 GIS Traditional definition is that GIS is a set of computer tools for accessing, processing, visualizing, analyzing, interpreting, and presenting spatial data. ‘GIS’ is Geographical Information System OR IS IT Geographical Information Science? GISystems: Emphasis on technology and tools GIScience: Fundamental issues raised by the use of GIS, such as Spatial analysis Map projections Accuracy Scientific visualization Implementation and application of GIS covers a wide spectrum: Simple maps Overlaying multiple map “layers” Conducting proximity or cluster analysis based on distance Comparing data sets (simple spatial statistics) Complex statistical analysis

26 Views to a GIS Map view: Focus on cartographic (mapping) aspects of GIS Thematic GIS layers Input map => Output map Database view: Focus on database management system Simple queries to retrieve and overlay data Spatial analysis view: Focuses on analysis and modelling Views GIS more as information science Organizational view: Focuses on decision support systems An approach to managing an organization’s data, information, and knowledge

27 GIS as Toolbox "a powerful set of tools for collecting, storing, retrieving at will, transforming and displaying spatial data from the real world for a particular set of purposes" (Burrough and McDonnell, 1998) "automated systems for the capture, storage, retrieval, analysis, and display of spatial data" (Clarke, 1995) “an information technology which stores, analyses, and displays both spatial and non-spatial data” (Parker 1988)

28 GIS as Database “a database system in which most of the data are spatially indexed, and upon which a set of procedures operated in order to answer queries about spatial entities in the database” (Smith et al., 1987) "A geographic information system is a special case of information systems where the database consists of observations on spatially distributed features, activities or events, which are definable in space as points, lines, or areas. A geographic information system manipulates data about these points, lines, and areas to retrieve data for ad hoc queries and analyses" (Dueker, 1979)

29 GIS as Spatial Analysis "An information system that is designed to work with data referenced by spatial or geographic coordinates. In other words, a GIS is both a database system with specific capabilities for spatially-referenced data, as well as a set of operations for working with the data" (Star and Estes, 1990) “The true potenital value of Geographical Information Systems lies in their ability to analyse spatial data using the techniques of spatial analysis" (Goodchild, 1988)

30 GIS as Organization “ an institutional entity, reflecting an organizational structure that integrates technology with a database, expertise and continuing financial support over time” (Carter, 1989) “organized activity by which people measure and represent geographic phenomena, and then transform these representations into other forms while interacting with social structures.” (Chrisman, 1999) “ a decision support system involving the integration of spatially referenced data in a problem-solving environment” (Cowen, 1988)

31 GIS as Science Geographic Information Science is research both on and with GIS. "the generic issues that surround the use of GIS technology, impede its successful implementation, or emerge from an understanding of its potential capabilities." (Goodchild, 1992)

32 Components of a GIS Organized collection of –Hardware –Software –Network –Data –People –Procedures People Software Data Procedures Hardware Network “GIS should be viewed as a process rather than as merely software or hardware.” (Malczewski, 1999)

33 A Brief History of GIS GIS’s origins lie in thematic cartography Many planners used the method of map overlay using manual techniques Manual map overlay as a method was first described comprehensively by Jacqueline Tyrwhitt in a 1950 planning textbook

34 A Brief History of GIS The 1960s saw many new forms of geographic data and mapping software Computer cartography developed the first basic GIS concepts during the late 1950s and 1960s Linked software modules, rather than stand-alone programs, preceded GISs The Harvard University ODYSSEY system was influential due to its topological arc-node (vector) data structure

35 User Interface Applications Geographic Tools Data Access Spatial Reference Vector Data Manager Raster Output Editing Analysis Customization Display Translation Functionality Architecture

36 Map Overlay

37 Definition 4: GIS is a multi-billion dollar business. “The growth of GIS has been a marketing phenomenon of amazing breadth and depth and will remain so for many years to come. Clearly, GIS will integrate its way into our everyday life to such an extent that it will soon be impossible to imagine how we functioned before”


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