2. Copyright, 1998-2013 © Qiming Zhou GEOG1150. Cartography Sources of Data

3. 2 Sources of data  Map as a representation of the reality  Ground survey and positioning  Remote sensing data collection  Census and sampling

4. Sources of Data3 Map as a representation of reality  Spatial data - spatially referenced objects or phenomena Reality Model construction and selection Selection and construction to a cartographic representation Map Results in the user’s mental map

5. Sources of Data4 The nature of spatial data The nature of spatial data: from reality (a), via model construction and selection to digital landscape model (b), followed by selection and construction to a cartographic representation towards a digital cartographic model (c), presented as a map (d), which results in the user's mental map (e). From Kraak and Ormelig, 1996. reality digital landscape model digital cartographi c model map menta l map drawing code for dots, dashes & patches model construction geographical object selection select and construct cartographic representation medium output area geometry attributes points geometry attributes lines geometry attributes x y z

6. Sources of Data5 Geographical objects The representation of geographical objects in a (digital) environment as (a) points, (b) lines, (c) areas and (d) volumes. From Kraak and Ormeling, 1996

7. Sources of Data6 1-D and 2-D objects The dimensionality of geographical objects – 1-D (inset map) and 2-D. From Kraak and Ormeling, 1996

8. Sources of Data7 3-D objects The dimensionality of geographical objects – 3-D. From Kraak and Ormeling, 1996

9. Sources of Data8 4-D objects The dimensionality of geographical objects – 4-D/time. From Kraak and Ormeling, 1996 beforeafter 18 May 1980

10. Sources of Data9 Ground survey and positioning  Geodesy - study of the shape and size of the earth.  The earth is so large that its curvature is relatively insignificant at the local scale.  Thus, we may use plane geometry instead of spherical geometry for plane survey. plane sphere

11. Sources of Data10 Surveying  The aim of surveying is basically to define the location of a point.  Since location is a relative rather than absolute concept, surveyors determine new positions with respect to an existing reference feature.  The geodetic control points provide the frame of reference for surveying.  Measurement of distance and angles based on the Euclidean geometry.

12. Sources of Data11 Measuring distance  Mechanical aids: measuring rods, flexible chains and ruled measuring tapes Physical limitations  Electronic distance measuring (EDM) instruments: laser beam or radio waves Line of sight

13. Sources of Data12 Laser distance measuring Laser beams and radio waves can be used to determine distances between electronic distance measuring instruments with great accuracy. From Robinson, et al., 1995 A laser distance measurer

14. Sources of Data13 Measuring direction  Direction is defined as angular deviation from a baseline True north - direction to the north pole Magnetic north pole: > 1600 km south of the true north pole and changing Magnetic declination - local difference between the true and magnetic north Compass deviation - unpredictable error in compass readings  Compass, optical sighting instruments, gyrocompass, radio compass

15. Sources of Data14 A theodolite By combining optics with a bubble level and vertical degree circle (a circular protractor ruled in degrees), surveyors could measure horizontal angles as well as vertical angles. The resulting instrument was called transit, which evolved into the modern theodolite. Robinson, et al., 1995

16. Sources of Data15 Traditional survey methods  Finding horizontal position Traverse Triangulation Trilateration  Finding vertical position Differential leveling Trigonometric leveling  Using a transit or theodolite

17. Sources of Data16 Some basic theorems A B C A(x 1, y 1 ) B(x 2, y 2 ) C(x 2, y 1 ) X Y A C B X Y ab c X Y A C B a b c Trigonometric Functions Pythagorean Theorem Distance Theorem Law of Cosines Law of Sines

18. Sources of Data17 Traverse The traverse method involves determining the location of an unknown point by making a series of direction and distance measurements. From Robinson, et al., 1995. (Measured angles and distance)

19. Sources of Data18 Triangulation Starting with a baseline of known length on the ground, the position of an off- baseline point can be determined by triangulation, which involves measuring the angles to the point to be located from the ends of the baseline. From Robinson, et al., 1995. (Measured angles)

20. Sources of Data19 Trilateration Starting with a baseline of known length on the ground, the position of an off- baseline point can be determined by trilateration, which involves measuring distances to the point to be located from the ends of the baseline. From Robinson, et al., 1995. (Measured distance)

21. Sources of Data20 Differential levelling

22. Sources of Data21 Trigonometric levelling

23. Sources of Data22 Automated survey systems  Total-station instruments Electronic tacheometer  Electronic positioning NAVSTAR (USDOD) global positioning system (GPS)  Fully operational in 1994  24 orbiting satellites (21+3)  Positioned in 6 evenly spaced orbital planes  Standard position service (SPS) and precise positioning service (PPS)

24. Sources of Data23 Total station A total station looks like a normal theodolite but it has a microcomputer for measuring and recording, as well as laser-beam device for distance measuring.

25. Sources of Data24 Global Positioning System A Global Positioning System (GPS) receiver that can be used in the field as a hand-held instrument or connected to the computer with digital maps as field navigation system.

26. Sources of Data25 Remote sensing data collection  Electromagnetic radiation (EMR) Electromagnetic wave Absorption and reflection  Aerial photography Panchromatic film (0.3 - 0.7  m) Aerial photograph geometry  Electronic imaging devices Satellite images

27. Sources of Data26 Visible UV Infrared Sun’s energy (at 6000°K) Earth’s energy (at 300°K) 0.3  m1m1m10  m100  m 1mm1m1m Wavelength Energy (a) Energy sources 0.3  m1m1m10  m100  m 1mm1m1m Wavelength Human eye PhotographyThermal IR scanners Electro-optical sensors Passive microwave (c) Common remote sensing systems Imaging radar 0.3  m1m1m10  m100  m 1mm1m1m Wavelength 0% 100% Transmission (b) Atmospheric transmittance Energy absorbed and scattered The electro- magnetic spectrum

28. Sources of Data27 B/W airphoto

29. Sources of Data28 Natural colour airphoto

30. Sources of Data29 Colour infrared airphoto

31. Sources of Data30 Panchromatic satellite image

32. Sources of Data31 Multi- spectral satellite image

33. Sources of Data32 Census and sampling  Census - identify and record all members of a population.  Geocoding - the practice of attaching locational information to census data. Entity focus - vector and raster geocoding. Aggregation.

34. Sources of Data33 Vector geocoding Coordinates are used to define the location of point, line, area and volume features in vector geocoding. From Robinson, et al., 1995 POINT (X, Y) P 1 (x 1, y 1 ) P 2 (x 2, y 2 ) P 1 (x 1, y 1 ) P 2 (x 2, y 2 ) P 3 (x 3, y 3 ) P 4 (x 4, y 4 ) P 5 (x 5, y 5 ) x y z P 1 (x 1, y 1, z 1 )P 2 (x 2, y 2, z 2 ) P 3 (x 3, y 3, z 3 ) P 4 (x 4, y 4, z 4 ) P 5 (x 5, y 5, z 5 ) P 6 (x 6, y 6, z 6 ) P 7 (x 7, y 7, z 7 ) P 8 (x 8, y 8, z 8 )

35. Sources of Data34 Raster geocoding Pixels are used to define the location of geographical entities in raster geocoding. After Robinson, et al., 1995

36. Sources of Data35 Spatial sampling  To make observations at a limited number of carefully chosen locations that are representative of a distribution  Size of sample - dependent upon the nature of distribution  Sampling units - points, lines (transects) and areas (quadrats)

37. Sources of Data36 Sampling Units Line (Transect) sample Area (Quadrat) sample Point sample Spatial sampling is performed using either point, line or area units, or some combination of these geometric forms.

38. Sources of Data37 Sampling Strategy  Spatial distribution Clustered, random and uniform distribution  Sampling strategy Random Systematic Stratified  Sampling theorem - a sampling interval should be less than half the size of target features in a distribution

39. Sources of Data38 Sample scatter Sample scatter is usually described in terms of deviation from randomness, with clustering at one extreme and uniformity at the other. From Robinson, et al., 1995 ClusteringRandomRegularity

40. Sources of Data39 Stratification Sampling based on stratification is highly efficient, because it takes advantage of what is already known about the distribution being sampled. From Robinson, et al., 1995 Forest Type Survey High Medium Low Sample site Vegetation diversity

41. Sources of Data40 Sampling interval Period Sampling Interval Amplitude According to the sampling theorem, the sampling interval needs to be less than half the size of target features in a distribution. Robinson, et al., 1995