Introduction Image Processing Thematic Map Manipulation Digital Terrain Modeling

1. Introduction Image Processing Thematic Map Manipulation Digital Terrain Modeling Cadastral Mapping and Queries Networks Data and Spatial Analyses Statistics of World Wide Utilization News about the 5.0 Version Conclusions Sistema de Processamento de Informações Georeferenciadas

2. General Characteristics Web Page for download Help online browser Data Modeling SPRING Modules SPRINGIntroduction

3. General Characteristics • Geographic Information System - GIS • Developed at Image Processing Division – DPI – INPE • Freeware Software – Download via Web (www.dpi.inpe.br/spring) • Windows and Linux Version 5.0 • 3 Languages: Portuguese, English and Spanish • Mirror Sites in Argentina (RUSHH) and Spain • Online Manual – Web style browser • Functionalities: Digital Image Processing, Thematic Map Manipulation, Digital Terrain Modeling,Storage and Queries for Cadastral Data, Modeling and Use of Networks and Data and Spatial Analyses.

4. Download via Webwww.dpi.inpe.br/spring

5. HELP OnLineGeneral Characteristics

6. DATA MODEL General Characteristics • Image • Numérical • Cadastral • Network • Object • Thematic • Cl-1 • Cl-2 • Name • Directory • DBMS DataBase Category • Name • Projection • Bounding Box Project A Project B IL - 1 IL - 2 IL - 3 IL - 4 IL - 1 IL - 2 • Name • Category • Resolution • Scale Numerical Map County PIB US$(bn) Popul. Milhões Thematic Map Thematic Map 350 159 Brasil Argentina 295 34 Objetos Image Data Cadastral Map Dbase, Access, MySQL,Oracle

7. SPRING MODULES • Spring – data input and edition, analysis, manipulation and integration of spatial data • Impima – image reader and format converter • Scarta– editor of cartographic products (charts) • Iplot – a plotter for cartographic maps • Testmesa – a test program to verify the communication between spring and a digitizer table.

8. SPRINGThe Main Module

9. IMPIMAMódulo: Importing Images Input formats • TIFF/GeoTiff • RAW • SITIM • DAT • GRIB Output • GRIB

10. SCARTAModule: Spring Carta Input • InfoLayers (DataBase /Project Created in SPRING) Output • Chart File • Template File • IPL file

11. Raster Representations Vector Representations Tables CBERS Wizard SPRING Import and Export Formats

12. Import / Export – General View Raster Representations: Tiff, GeoTiff, Gif, Sitim, RAW….. Vectorial Representations: ASCII-Spring, Dxf, ShapeFile, UNG, Surfer-ASCII, … Table Representations: Spatial and NoSpatial Tables Wizard CBERS

13. Image Registration Contrast Enhancement Color Composition Filtering Segmentation Classification SPRING Image Processing Module

14. Image Processing – General View

15. Image Processing

16. Image Registration • Image Registration • Based in Control Points (CP) specification • The real coordinates of each CP must be defined • It uses a polynomial mapping in order to register the image with a specific cartographic reference system.

17. Image Registration • Image Registration • The system provides statistical information in order to control the final quality of the registration.

18. Contrast Enhancement

19. Color Composition (RGB) TM 3 B TM 4 R TM 5 G

20. Low-Pass Filtering Noise reduction

21. High-Pass Filtering Edge Detection

22. Example: Mean and Median Filters A 3x3 Mean Value Filter Example of an image with a noisy line A 3x3 Median Value Filter

23. Segmentation • Segmentation: Identify homogeneous regions inside an image • Region: a set of contiguous pixels that are considered spectrally similar • It uses statistical attributes to determine similar regions. • The user controls the similarity criterions.

24. Classification • It is based on pattern recognition procedures (objects) • The resulting image contains pixels that are mapped to classes of interest of the system user.

25. Input/Edition of vectorial maps Matrix Edition - Areas of Classes - Buffering Maps Vector to Matrix Conversion Matrix to Vector Conversion SPRING Manipulation of Thematic Maps

26. Manipulation of Thematic Maps

27. Vectorial Edition Parameters • Option : Graphical Edition or Verification • Edit: Lines, Points (thematic/cadastral) Break lines, contour lines (DTM) • Mode : Continuous or Step • Topology : Automatic or Manual • Factor of Digitalization (mm) : 0,00 a 4,00 • Edit Operations : Line Creation, Closed Line Creation, Add Point, Move Point, Split Line, Join Lines, Eliminate Line, Eliminate Point, Clean Area, Concatenate Lines, ….

28. Matrix Edition - Copy Area Example • Select in the window 5 the area to be painted • Execute, to perform the modification Zoom

29. Matrix Edition – Area Classification • Select the color and click in the poligon. • Execute, to perform the modification.

30. Measurements of Classes

31. Buffering maps

32. Vector to Matrix Conversion Original Vector Information Matrix structure definition Final Map in a Matrix representation

33. Matrix to Vector Conversion

34. Input/Edition Rectangular and Triangular Models Interpolators for Regular Grids DTM Image representations Slope Maps and Slicing 3D Planar Plojection SPRING Digital Terrain Modeling

35. Digital Terrain Modeling – General View

36. DTM – Edition Tools Edit - Isolines - Points 3D - Break-Lines • Operations • Create Lines • Create Closed Line • Add Points • Move Points • Break Lines • Join Lines • - Delete Line • - Delete Point • - Clean Area Mode - Continuous - Step by Step

37. Digital Terrain Modeling • Regular Rectangular Grids • More often used for representation of geophysical information • More suitable for creating planar projections • It is easy to manipulate • Triangular Networks (TIN) • Represents better complex reliefs • Allows one to incorporate restritions in the model (break lines)

38. Interpolators for rectangular grid models Closest Neighbors Simple Mean Weighted Mean

39. Aplications: Image Generation • Gray Level Image • Linear Mapping of the real Z values to gray levels (0 to 255) • Shadowed Image

40. Aplications:Slope Maps and Slicing The classification (slicing) of the Slope Image considering the classes (0-2, 2-5, 5-10 e >10) Rectangular Grid of Slopes

41. Applications: Geometric Planar Projections Projeção Paralela com Imagem Sombreada como Textura Parallel projection using the shadowed DTM image as a terrain texture

42. Applications: Geometric Planar Projections Perspective projection using a Remote Sensing image as a terrain texture

43. Selection: Map/Table Pie Chart Histogram Graphic Statistics Grouping Attribute Queries Spatial Queries SPRING Manipulation of Cadastral Maps and Queries to the Data Base

44. Tools for queries in the Database

45. Table Module (Window Pointer x Table) Table with the object attributes Spatial Representation 13 21

46. Table Module (Pie Chart)

47. Table Module (Histogram Graphic)

48. Table Module (Statistics)

49. Module of Attribute Grouping :(Total Familiar Gain – Equal Step and Quantil) Districts grouped by Familiar Gains: Central Region: Rich Central Limit: Mean East Region: Poor South Region: Poor Quantil Equal Steps

50. Attribute Queries Module * Table showing the result of the query