Data Handling 3 Alter. 2010/2011 Wageningen UR

Transkript

1 Data Handling 3 Alter 2010/2011 Wageningen UR

2 What functions to alter geo-data? Raster processing tools / - analysis Local operations Focal operations Zonal operations Global operations Vector processing tools / - analysis Attribute calculations Buffering Overlay Types Point in polygon Line in polygon Polygon on polygon Methods Union Intersect Identity Geo-data cycle 2/37

3 Alter / process - definition Query a data handling class of operators which doesn t change the thematic and geometric meaning of the original geo-data which doesn t change the (geo-)reference or data structure it only selects a subset out of the whole data set Transform a data handling class of operators which doesn t change the thematic and geometric meaning of the original geo-data which changes the (geo-)reference or data structure Alter/Process data handling class of operators which changes the thematic and geometric meaning of the original geo-data which doesn t change the (geo-)reference and data structure 3/37

4 DATA HANDLING RASTER OPERATIONS History Steinitz (Harvard), McHarg (Pennsylvania) analytical tools for landscape analysis Dana Tomlin (Yale) cartographic modelling > Map Algebra Map algebra Professor Dana Tomlin originator of Map algebra. formalized rules to process raster structured geo data new map = f (old map 1, old map 2,..) new raster set = f (old raster set 1, old raster set 2,..) operation based on a local, focal, zonal or global function 4/37

5 Local operations new cell value is based on the old cell value on the same location in the old raster(s) One / More input raster Mathematical functions Arithmetic operators Logical operators Cell statistics 5/37

6 Local operations: mathematical function 6/37

7 Local operations - add Contingency tables 7/37

8 Focal operations (neighborhood operations) new cell value is based on the old cell values on the same and neighbouring locations in old raster(s) Defined window or neighborhood Neighborhood statistic function Examples: Lines of change terrain analysis: slope and aspect calculations 8/37

9 Focal Operation raster cell neighborhood cell altered cell 9/37

10 Zonal operations new cell value is based on a collection of old cell values of old rasters based on a clustering by old cell values Input grid is zone or region! grid a non-contiguous zone in a raster are all cells with the same value a contiguous zone in a raster are spatially connected cells or region zonal statistics functions (minimum, mean, majority, etc.) Output as dbf-table Example: Size of public area within urban quarters of the same construction data or the same housing density or the same population density 10/37

11 Exercise 1 A A B B A is the result of a zonal operation. Write down the function for this operation. 11/37

12 Exercise 2 A A B A is the result of a zonal operation based on an - majority OR B minimal value function. Note the values of A. 12/37

13 Global operations new cell value is based on all old cell values of old rasters Cost or weighted distance Eucledian distance or proximity analysis 13/37

14 Euclidean distance 1 Top view study area 14/37

15 Euclidean distance 2 What s wrong with the final result? 15/37

16 Exercise: Extrapolation by Euclidean distance , , ,4 1-1, ,4 1 1,4 1,4 1 1, ,2 2 2,2 2,2 2 2,2 16/37

17 Examples BelevingsGIS, Roos, /37

18 Raster operations: comparison 18/37

19 Types of vector operations Overlay - geometrically Neighbourhood, like Buffering - geometrically Attribute thematically 19/37

20 Overlay operations Foo Create an adapted geometry (G) and a combination of attributes (T) based upon the original geometry and attributes of two or more super-positioned data sets in a shared extent and the same geo-reference Types Point in polygon Line in polygon Polygon on polygon 20/37

21 Optical / graphic overlay: example Optical/graphic overlay No new topology Only transparency Topological overlay New topology calculated New objects and new tables 21/37

22 Topological overlay: example 22/37

23 Example Thesis DJ Bulsink, /37

24 Neighbourhood operations Fon Create a new geometry (G) out of an original geometry and related attributes within the given extent and same geo-reference 24/37

25 Buffering around points, lines and areas from object into it s surrounding neighbourhood 25/37

26 Buffering: different size A = Fpnb (A) distance is constant A =Fpnb (A) distance is variable 26/37

27 Example 27/37

28 Tsunami, /37

29 Visibility 29/37

30 Extrapolation by Thiessen polygons 30/37

31 Thiessen applied 31/37

32 Thiessen polygons - example 32/37

33 Attribute operation Foa calculate values for new attributes out of existing attribute value domains. Eg: classification, simple maths, statistics 33/37

34 Example: shape SHAPE is a ratio AREA : LENGTH Shape index = Circumference / Area 34/37

35 Summary: Raster operations / - analysis Local mathematical functions Focal neighbourhood statistics, filters Zonal zonal statistics Global Euclidean distance Vector operations / - analysis Attribute (mainly thematically) Neighbourhood (ao buffering, thiessen polygon) Overlay Types Point in polygon Line in polygon Polygon on polygon Methods Union Intersect Identity 35/37

36 Summary - Data Handling Query Transform Alter/Process Thematically Vector - Vector Attribute Geometrically map projection classification Location Vector Vector Neighbourhood Orientation similarity/affine from object Size Raster - Vector between objects Shape topology, attribute Overlay Topology Vector - Raster graphic rules, order, (over)size, frequency topologic 36/37

37 Geo Information Tools : GRS /37

38 Study materials: Theory Chang, /5th Chapter 12: Vector data analysis (NOT 12.4) Chapter 13: Raster data analysis Practical: GRS practical manual, 2008 Wageningen UR Module 7: Raster operations Module 8: Vector operations

39 Classification 1 Functions available (natural break is ArcGIS default) percentile/quantile: same number of objects by class equal area: equal surface of objects by class equal interval: equal ranges within an attribute domain standard deviation: variance with respect to the average source: esri arcgis manual 39/37

40 Attribute calculation Object Cover GWT Calc. Abund. Lutum 1grass grass grass maize water fruit grass residential grass maize grass water grass grass residential Cover gwt lutum Grass 4 9, ,32 40/37