An Introduction to Geomatics. Prepared by: Dr. Maher A. El-Hallaq خاص بطلبة مساق مقدمة في علم. Associate Professor of Surveying IUG

Transcription

1 An Introduction to Geomatics خاص بطلبة مساق مقدمة في علم الجيوماتكس Prepared by: Dr. Maher A. El-Hallaq Associate Professor of Surveying IUG 1

2 Airborne Imagery Dr. Maher A. El-Hallaq Associate Professor of Surveying The Islamic University of Gaza 2

3 Part One Airborne Imagery Photogrammetry 3

4 Background 4

5 Background 5

6 Background 6

7 Background Aerial photography has a history dating back to the mid 1800s, when balloons and even kites were used as camera platforms. In 1908, photographs were taken from early aircraft. Aerial photography became accepted technique for collecting mapping and other ground data from 1930s to the present. Photogrammetry is the science of making measurements from aerial photographs. 7

8 Background Measurements of horizontal distances and elevations form the backbone of this science. These capabilities result in the compilation of planimetric maps or orthophoto maps showing the horizontal locations of both natural and cultural features, and topographic maps showing spot elevations and contour lines. Both black and white panchromatic and color film are used in aerial photography. Color film has three emulsions: blue, green and red light sensitive. 8

9 Background 9

10 Background The more recent topic of airborne imagery is digital imagery (2000). The most common detector is the Charge-Coupled Device (CCD) 10

11 Background New Old 11

12 Background Elements of an aerial mapping camera 12

13 Background Orthographic versus perspective projection 13

14 Photogrammetric Process Photogrammetric mapping is achieved through four general processes : Imagery Acquisition. Ground Control Acquisition. Accurate Adjustment of the Imagery to the Earth. Feature Collection. 14

15 Photogrammetric Process 15

16 Photogrammetric Process Imagery Acquisition. Imagery Types and Uses Imagery Type Black and White Aerial Photography Natural Color Aerial Photography Infrared Aerial Photography Satellite Imagery Microwave General Purposes Topographic and Planimetric Mapping Topographic and Planimetric Mapping Vegetation Analysis, Land use Small Scale Mapping, Vegetation Analysis, Land use/land Classification Groundwater 16

17 Photogrammetric Process Imagery Acquisition. 17

18 Photogrammetric Process Imagery Acquisition. 18

19 Photogrammetric Process Imagery Acquisition. Scale of an aerial photograph 19

20 Photogrammetric Process Imagery Acquisition. Flight Plan 20

21 Photogrammetric Process Imagery Acquisition. Flight Plan 21

22 Example: Photogrammetric Process 22

23 Example: Photogrammetric Process 23

24 Example: Photogrammetric Process 24

25 Photogrammetric Process Ground Control Acquisition. Ground control methods 25

26 Photogrammetric Process Accurate Adjustment of the Imagery to the Earth. The process of adjusting the aerial photography to the earth is critical to the accuracy of final mapping. most projects are adjusted using aerotriangulation methods. These methods require fewer ground control points than conventional adjustment methods Aerotriangulation methods are accomplished with computer software. The software is very efficient and allows for quality control checks throughout the process. 26

27 Photogrammetric Process Feature Collection. Photogrammetric mapping feature collection can generally be divided into four categories: 1. Topographic Features (DEM and TIN models) 2. Planimetric Features 3. Orthophotography 4. Land use. These feature types can be collected accurately using stereo imagery and stereo viewing equipment. 27

28 Photogrammetric Process Feature Collection. 3. Orthophotography 28

29 Height Determination 29

30 Height Determination 30

31 Height Determination Note: If h B is not known, it is sufficiently accurate to use (h avg ) instead of h B especially if H is large. 31

32 Ground Coordinates 32

33 Thank you Any Question? 33

34 Satellite Imagery Dr. Maher A. El-Hallaq Lecturer of Surveying The Islamic University of Gaza 34

35 Part Two Satellite Imagery Remote Sensing 35

36 Background Remote sensing derives from photography, optics and spectrometry; its history is deeply entwined with the domains of electromagnetic spectrum and aeronautics. 36

37 Background 37

38 Background 38

39 Background Remote sensing is a broad research field with a wide range of applications. Technically the term means acquisition of information without being in direct contact with the object that is studied. This will typically imply detection of some kind of radiation. The detected radiation is either emanating from the object itself or is reflected by it. The remote sensing principle, using waves of the electromagnetic spectrum. 39

40 Background 40

41 Electromagnetic Spectrum The radiation propagates through a vacuum with the speed of light, c, at about km/second. 41

42 Electromagnetic Spectrum 42

43 Electromagnetic Spectrum 43

44 Electromagnetic Spectrum 44

45 Techniques of Remote Sensing Passive remote sensing instruments develop images of the ground surface as they detect the natural energy that is either reflected (if the sun is the signal source) or emitted from the observed target area. Active remote sensing instruments (for example, radar and lidar) transmit their own electromagnetic waves and then develop images of the earth's surface as the electromagnetic pulses (known as backscatter) are reflected back from the target surface. 45

46 Spectrum Sensors Optical: spectral range in the interval μm, typical of passive remote sensing, identified by the sensors: panchromatic: one band including the visible range and in some cases part of the near infrared; multispectral: 2 9 spectral bands; super-spectral: spectral bands; hyperspectral: more than 16 spectral bands; The increase of the number of bands in general improves the bandwidth (bandwidth is more common) and the spectral interval. 46

47 Spectrum Sensors Radar: microwaves ranging from 1 mm to 1 m, typical active remote sensing tool, that can operate, with single or multi-polarization and with single or multiple incidence angle, in: single frequency; multi-frequency. Technical problems of acquisition and representation are currently being operatively solved, while problems still exist in understanding the characteristics of these techniques by decision makers and administrators at national, regional, provincial and city level. 47

48 Techniques of Remote Sensing 48

49 Techniques of Remote Sensing 49

50 Techniques of Remote Sensing 50

51 Spectrum Signature One important way of discriminating objects in a remotely sensed scene is by means of examining their spectral signatures, a spectral response. Each material has its own spectral signature constituting of the spectral distributions of its emittance and reflectance. 51

52 Spectrum Signature Spectral signature of some artificial materials 52

53 Spectrum Signature 53

54 Sensor Fusion Electromagnetic sensors are designed to detect only radiation in a limited wavelength-range; a band. The reason for this is that the emitted energy within a narrow band tells us more about the reflectance of an object than an average over a wide band When the satellite image is received and processed on the ground, bands from several sensors may be combined. This will generally simplify the interpretation of a satellitescene 54

55 Sensor Fusion Some object features stand out in one band while other features are spotted in another band. The combination of information from several sensors is usually termed sensor fusion. The combination or fusion of several bands is similar to the approach used by the human vision system to create colors. 55

56 Sensor Fusion Satellite systems differ from the human vision system in that each satellite has its own set of sensors, constituting a unique set of bands and will thus require interpreting software specially adapted for it. 56

57 Image Characteristics 57

58 Image Characteristics 58

59 Image Characteristics small equal-sized and shaped areas, called picture elements or pixels, and representing the brightness of each area with a numeric value or digital number 59

60 Image Resolution Image Resolution defines the ability of a sensor to distinguish between spatial characteristics of objects on the earth s surface. It can change due to sensor design, detector size, focal length, satellite altitude and time. 60

61 Image Resolution Spatial Resolution Spectral Resolution Radiometric Resolution Temporal Resolution 61

62 Spatial Resolution The greater the altitude of the sensor, the larger the area seen but the ability to distinguish some detail may be lost. Some sensors have greater ability to see details, greater spatial resolution. The ground sample distance GSD (Pixel Size in image) IFOV: Instantaneous Field Of View GSD (m) = IFOV (radians) Altitude (m) 62

63 Spatial Resolution 63

64 Spectral Resolution Surface features can be identified by analyzing the spectral responses over distinct wavelength changes. The higher the spectral resolution of the sensor, the more distinctions that can be made of surfaces materials. Multispectral vs. hyperspectral sensors. 64

65 Radiometric Resolution Refers to the sensors ability to detect small changes in energy and reflects the number of bits available for each pixel. Imagery data are represented by positive digital numbers like binary format. Each bit records an exponent of 2. 2-bit is 2 2 =4, 8-bit is 2 8 =256, 10-bit is 2 10 = bit resolution of a region holds finer details than 2- bit resolution. 65

66 Radiometric Resolution 66

67 Temporal Resolution The surface of the earth is always changing, slowly or rapidly. The time period required to achieve repeat coverage of the same surface is called the revisit time. Temporal variations in surface features can be used to identify some features and to track systematically the changes in other features. 67

68 Temporal Resolution 68

69 R.S.Satellites Satellite Launch Date Sensor Data Altitude km Swath km Orbit Type Orbit Period Revisit time ERS-2 20/5/95 SAR C band m IKONOS-2 24/9/99 1 m MSS panchronmatic Near polar; sun synchronous Near polar; sun synchronous 100 min 35 days 98 min 2.9 days IRS 2000 Panchronmatic/ hyperspectral days Landsat 5 1/3/84 TM and MSS Landsat 7 15/5/99 ETM MSS Radarsat-1 20/12/95 SAR C band Near polar; sun synchronous Near polar; sun synchronous Circular; sun synchronous 99 min 16 days 99 min 16 days days min 69

70 R.S.Satellites Satellite Launch Date Sensor Data Altitude km Swath km Orbit Type Orbit Period Revisit time QUICKBIRD m MSS panchronmatic 470 Not sun synchronous Less than 5 days SPOT 1 22/2/86 MSS panchronmatic Near polar; sun synchronous 101 min 26 days SPOT 2 21/1/90 MSS panchronmatic Near polar; sun synchronous 101 min 26 days SPOT 4 24/3/98 MSS panchronmatic Near polar; sun synchronous 101 min 26 days SPOT TERRA 18/12/99 MODIS ASTER Near polar; sun synchronous 96.5 min 16 days 70

71 R.S.Satellites 71

72 R.S.Satellites 80 m 72

73 R.S.Satellites 30 m 73

74 R.S.Satellites 10 m 20 m 74

75 R.S.Satellites 75

76 Feature Extraction 76

77 Feature Extraction Unsupervised: relies on color and tone as well as statistical clustering to identify features. Supervised: requires comparative examples of imaging for each ground feature category. Hybrid: is a combination of the first two. Classification and regression tree: using binary partitioning software to analyze and arrive eventually at a best estimate about the ground feature identification. 77

78 Thank you Any Question? 78