Data handling 3: Alter Process

Transcription

1 Introduction Geo information Science (GRS 10306) Data handling 3: Alter Process 2009/2010 CGI GIRS

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3 Alter / process / analysis / operations 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 Process / alter a 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

4 Overview 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 information process 4

5 DATA HANDLING RASTER OPERATIONS History Steinitz (Harvard), McHarg (Pennsylvania) analytical tools for landscape analysis Dana Tomlin (Yale) cartographic modelling > Map Algebra Professor Dana Tomlin originator of Map algebra. Map algebra formalized rules to process raster structured geo data new raster set = f (old raster set 1, old raster set 2,..) operation based on a local, focal, zonal or global function 5

6 Local operations new cell value is based on the old cell value on the same location in the old raster(s) 1 input raster Mathematical functions more input rasters Arithmetic operators Logical operators Cell statistic functions 6

7 Local operations: mathematical function 7

8 Local operations: arithmetic operator 8

9 Local operators 9

10 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: Remote Sensing: filter operations terrain analysis: slope and aspect calculations 10

11 Focal Operation raster cell neighborhood cell altered cell 11

12 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: comparison of topographic characteristics of soil zones 12

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

14 Euclidean distance 1 Top view study area 14

15 Euclidean distance 2 15

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

17 Raster operations: comparison 17

18 Exercise 1 A A A 1 1 A B B A is the result of a zonal operation. Write down the function for this operation. 18

19 Exercise 2 A A A A B A is the result of a zonal operation B based on an 1 majority OR 2 minimal value function. Write down the values of A. 19

20 Types of vector operations Attribute calculations Buffering Overlay 20

21 Overlay operations Create new attributes and combine attributes based upon original attributes of two or more superpositioned data sets in the same extent and the same georeference Types Point in polygon Line in polygon Polygon on polygon 21

22 Optical / graphic overlay: example Optical/graphic overlay No new topology Only transparency Topological overlay New topology calculated New objects and new tables 22

23 Topological overlay: example 23

24 Overlay methods 2 A, B intersect A and B AND union A or B OR difference A, not B NOT exclusive not (A and B) NAND not-exclusive not (A or B) NOR 24

25 Vector overlay: exercise A Table A obj_id soil lutum 1 peat 10 2 clay B Table B obj_id pollution 1 yes -1 no A OR 25

26 Vector overlay: result A B A Table A obj_id obj_id A obj_id B soil lutum pollution peat 10 no peat 10 yes peat 10 no yes clay 15 yes clay 15 no no 26

27 Attribute function handling classes that calculate values for existing or new attributes Eg: classification; descriptive statistics, simple maths 27

28 Attribute calculation Object Cover GWT Calc. Abund. Lutum 1 grass grass grass maize water fruit grass residential grass maize grass water grass grass residential Cover gwt lutum Grass 4 9, ,32 28

29 Classification 1 Division of thematic attribute values Examples 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 29

30 Classification 2 30

31 Neighbourhood functions handling class operates on or in the neighbourhood / proximity of objects (vector) / cell (raster) and their respective attributes (geometric and thematic) 31

32 Buffering around points, lines and areas from object into it s surrounding neighbourhood 32

33 Buffering: different size distance is constant distance is variable 33

34 Buffering: traveling time distances 34

35 Environmental quality assessment 35

36 Environmental quality assessment 2 36

37 Extrapolation by Thiessen polygons 37

38 Thiessen applied 38

39 Example: vineyard suitability analysis 1 Wageningen... a wine producing region in reality? fiction

40 Example: vineyard suitability analysis 2 Land use Ground water +soil Elevation 0A 0B 0C Towns 0D? 1? 2? Suitable Land use Suitable Ground water Suitable Soils DEM 1A 2A 3A 4A Distance <6km 5A Land use 0/ Suitable GW/Soils GW/Soils 0/1 Slope 0/1 Slope 6A 7A 8A 9A 12A 13A 14A? A Slope classes 0/1/2 16A Aspect? 17 Aspect classes 0/1/2 19 Slope and Aspect classes 0/1/2 10A 17A 19A 11A 18 Distance 0/1 18A Suitable locations 40

41 Summary: Raster operations / analysis Local Focal Zonal Global mathematical functions neighbourhood statistics zonal statistics Euclidean distance Vector operations / analysis Buffering Overlay Types Point in polygon Line in polygon Polygon on polygon Methods Union Intersect Identity 41

42 Summary Data Handling Query Transform Alter/Process Thematically Vector Vector Attribute Geometrically map projection classification Location Vector Vector Neighbourhood Orientation similarity from object Size Raster Vector between objects Shape topology, attribute Overlay Topology Vector Raster graphic rules, order, (over)size, frequency topologic 42

43 Study materials: Theory Chang, 2006 Chapter 12: Vector data analysis Chapter 13: Raster data analysis Practical: GRS practical manual, 2006 Wageningen UR Module 7: Raster operations Module 8: Vector operations

44 Types of alteration / processing attribute functions Create new (values of) attributes (T) for an entity/cell based upon the original values of the entity / cell attributes (T) at the same location neighbourhood functions Create new attributes (T and,or G) based upon original entity / cell attributes (T and, or G) at the same location and its surrounding locations overlay functions Create new attributes (G) and combine attributes (T) based upon original attributes (T & G) of two or more super-positioned data sets of the same area and with the same geo-reference 44