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Geoinformatics(nce 402)

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Geoinformatics(nce 402)

  1. 1. GEOINFORMATICS(NCE 402) By- Md Mozaffar Masud Assistant Professor Civil Engineering Department JIT, Barabanki
  2. 2. UNIT 1
  3. 3. INTRODUCTION  Aerial photography is defined as art of taking photograph from a point in the air for the purpose of making study on earth surface.  Aerial photography and its planning includes selection of types of aero plane and camera, film and filter combination which is of great importance in photo interpretation.  Most of the conventional aerial photography is done at 1:30000 to 1:60000 scale on a conventional black and white panchromatic film.
  4. 4. INTRODUCTION  For more specific and detailed information such as ground water surveys, land use planning , mineral exploration, photographs of scale 1:10000 to 1:15000 are most suitable.  Quality of photographs depend upon-  flight and weather condition  Camera lens  Film and filters  Developing and printing processes
  5. 5. Basic Terminology  Focal Length – the distance between the camera lens and the film  Flying Height – the height of the plane (and therefore the camera) above the ground  Nadir – the point on the ground directly below the camera  Flight Line – the path of the airplane over which a sequence of pictures is taken  Stereoscope - a device used to view/measure feature heights and/or landscape elevations using pairs of air photographs  Fiducial Marks – marks on photographs used to align adjacent photos for stereoscopic analysis
  6. 6. Scale of photographs
  7. 7. Air Photo Scale  Scale (RF) = [1 : (flying height / focal length)] or (focal length/flying height)  Focal length and flying height should be in the same units  Example:  Focal length = 6 inches or 0.5 ft  Flying height = 10,000 ft  Scale = 0.5 / 10,000 = 1:20,000
  8. 8. Basic Camera  Everything above “C” is inside the camera  The film sits on the film plane  f = focal length  H = Elevation above ground  ACB = angle of coverage  Scale: RF = 1:(H / f)
  9. 9. Types of vantage points to acquire photographs  Vertical vantage points  Low-oblique vantage points  High-oblique vantage points
  10. 10. Vertical Aerial Photography San Juan River
  11. 11. Low-oblique Aerial Photography Bridge on the Congaree river near Columbia
  12. 12. High-oblique Aerial Photography Grand Coulee Dam in Washington
  13. 13. Types of film Black and White  most often used in photogrammetry  cheap Color  easy to interpret  fuzzy due to atmospheric scattering Infrared Color Infrared (CIR)
  14. 14. CIR and True Color Film Type Examples CIR True Color
  15. 15. CIR Films
  16. 16. Stereoscopic Parallax  Stereoscopic Parallax is caused by a shift in the position of observation  Parallax is directly related to the elevation / height of features  Vertical stereo pairs of aerial photographs are used to take 3-D measurements by measuring parallax
  17. 17. Stereoscope
  18. 18. Sources of Distortion  From Collection:  Yaw – plane fuselage not parallel to flight line Think about having to steer your car slightly into a strong cross wind Leads to pictures not being square with the flight-line  Pitch – nose or tail higher than the other Leads to principal point not being at nadir  Roll – one wing higher than the other Leads to principal point not being at nadir  Natural:  Haze  Topographic changes For example, if flying over mountains, the height above the ground will a) change from picture to picture, and b) not be uniform in a single picture. Both of these lead to irregularities in the photo scale
  19. 19. Photo interpretation: Recognition Elements Shape Size Color/Tone Texture Pattern Site Association Shadow
  20. 20. Photo interpretation: Recognition Elements  Shape  cultural features - geometric, distinct boundaries  natural features - irregular shapes and boundaries  Shape helps us distinguish old vs. new subdivisions, some tree species, athletic fields, etc. The pentagon Meandering river in Alaska Interior Alaskan village (note airstrip near top of image)
  21. 21.  Size  relative size is an important clue  big, wide river vs. smaller river or slough  apartments vs. houses  single lane road vs. multilane Photo interpretation: Recognition Elements
  22. 22. Photo interpretation: Recognition Elements  Color/Tone  coniferous vs. deciduous trees CIR - Spruce forest (black) with some deciduous (red) trees. CIR – Deciduous (leafy) vegetation (red). CIR- Mixed spruce And deciduous forest on hillside with tundra in valley bottom
  23. 23. Photo interpretation: Recognition Elements  Texture  coarseness/smoothness caused by variability or uniformity of image tone or color  smoothness – tundra, swamps, fields, water, etc.  coarseness - forest, lava flows, mountains etc. CIR- Marshy tundra with many small ponds CIR - Bare rounded Mountains (blue) surrounded by tundra and lakes CIR - Tundra showing drainage pattern
  24. 24. Photo interpretation: Recognition Elements Pattern  overall spatial form of related features  repeating patterns tend to indicate cultural features - random = natural  drainage patterns can help geologists determine bedrock type A dendritic pattern is characteristic of flat- lying sedimentary bedrock
  25. 25. Photo interpretation: Recognition Elements Site site - relationship of a feature to its environment differences in vegetation based on location: In interior Alaska, black spruce dominant on the north side of hills and deciduous trees on the south side. Vegetation is often has different characteristics by rivers than away from them Meandering Alaskan river Interior Alaskan hillside
  26. 26. Photo interpretation: Recognition Elements  Association  identifying one feature can help identify another - correlation The white cloud and black shadow have the same shape, they are related The long straight airstrip near the top of the image indicates that there might be a village or settlement nearby
  27. 27. Photo interpretation: Recognition Elements  Shadows  shadows cast by some features can aid in their identification  some tree types, storage tanks, bridges can be identified in this way  shadows can accentuate terrain The mountain ridge on the right side of this image is accentuated by shadow
  28. 28. UNIT 2
  29. 29. What is remote sensing used for What is reRemote Sensingmote sensing used for What is remote sensing used for  Definitions:  The acquisition of physical data of an object without touch or contact .  The observation of a target by a device some distance away.  The use of electromagnetic radiation sensors to record images of the environment, which can be interpreted to yield useful information.
  30. 30. Advantages of RS  Provides a view for the large region  Offers Geo-referenced information and digital information  Most of the remote sensors operate in every season, every day, every time and even in real tough weather.  Remote sensing can be either passive or active. Active systems have their own source of energy whereas the passive systems depend upon the solar illumination or self emission for remote sensing
  31. 31. Elements of RS
  32. 32. Process of RS Data  Emission of electromagnetic radiation, or EMR (sun/self- emission)  Transmission of energy from the source to the surface of the earth, as well as absorption and scattering  Interaction of EMR with the earth's surface: reflection and emission  Transmission of energy from the surface to the remote sensor  Sensor data output  Data transmission, processing and analysis
  33. 33. Remotely Sensed Data
  34. 34. Remote Sensing Satellite Polar-Orbiting Satellites A polar orbit is a satellite which is located near to above of poles. This satellite mostly uses for earth observation by time.
  35. 35. Remote Sensing Satellite Geostationary Satellites A geostationary satellite is one of the satellites which is getting remote sense data and located satellite at an altitude of approximately 36000 kilometres and directly over the equator
  36. 36. Remote Sensing Sensors  Sensor is a device that gathers energy (EMR or other), converts it into a signal and presents it in a form suitable for obtaining information about the target under investigation. These may be active or passive depending on the source of energy .  Sensors used for remote sensing can be broadly classified as those operating in Optical Infrared (OIR) region and those operating in the microwave region. OIR and microwave sensors can further be subdivided into passive and active.
  37. 37. Active sensors use their own source of energy. Earth surface is illuminated through energy emitted by its own source, a part of its reflected by the surface in the direction of the sensor is received to gather information. Passive sensors receive solar electromagnetic energy reflected from the surface or energy emitted by the surface itself. These sensors do not have their own source of energy and can not be used at night time, except thermal sensors. Again, sensors (active or passive) could either be imaging, like camera, or Sensor which acquire images of the area and non-imaging types like non-scanning radiometer or atmospheric sounders.
  38. 38. Resolution  Resolution is defined as the ability of the system to render the information at the smallest discretely separable quantity in terms of distance (spatial), wavelength band of EMR (spectral), time (temporal) and/or radiation quantity (radiometric)
  39. 39. Types of Resolution Spatial resolution Spectral Resolution Radiometric Resolution Temporal Resolution
  40. 40.  Spatial resolution—  The earth surface area covered by a pixel of an image is known as spatial resolution  Large area covered by a pixel means low spatial resolution and vice versa
  41. 41. Spatial resolution
  42. 42.  Spectral Resolution –  Is the ability to resolve spectral features and bands into their separate components  More number of bands in a specified bandwidth means higher spectral resolution and vice versa
  43. 43. Spectral Resolution
  44. 44. Spectral Resolution Three spectra recorded at low, medium and high spectral resolution, illustrating how the high resolution mode yields sharper peaks, and separates close lying peaks, which are merged together at low resolution
  45. 45.  Radiometric Resolution -  Sensitivity of the sensor to the magnitude of the received electromagnetic energy determines the radiometric resolution  Finer the radiometric resolution of a sensor, if it is more sensitive in detecting small differences in reflected or emitted energy
  46. 46. Radiometric Resolution 6-bit range 0 63 8-bit range 0 255 0 10-bit range 2-bit range 0 4
  47. 47.  Temporal Resolution-  Frequency at which images are recorded/ captured in a specific place on the earth.  The more frequently it is captured, the better or finer the temporal resolution is said to be  For example, a sensor that captures an image of an agriculture land twice a day has better temporal resolution than a sensor that only captures that same image once a week.
  48. 48. Temporal Resolution- Remote Sensing & GIS Applications Directorate Time July 1 July 12 July 23 August 3 11 days 16 days July 2 July 18 August 3
  49. 49. Color Science  Additive primary colors :  Blue, Green, and Red  Subtractive primary colors (or complementary colors):  Yellow, Magenta, and Cyan  Filters (subtract or absorb some colors before the light reaches the camera):  Red filter (absorbs green and blue, you can see red)  Yellow (or minus-blue) filter (absorbs blue, allows green and red to be transmitted, which is yellow)  Haze filter (absorbs UV) additive Subtractive
  50. 50. Normal color False-color infrared
  51. 51. UNIT 3
  52. 52. Satellite image Satellite imagery consists of photographs from which collected by satellites
  53. 53. Global overview  What does satellite imagery give you?  Information on land cover, land use, habitats, landscape and infrastructure  multiple engagements by time series  Mapping and monitoring changes and predict future
  54. 54. Image Histograms The histogram of an image shows us the distribution of grey levels in the image Massively useful in image processing, especially in segmentation Grey Levels Frequencies
  55. 55. Histogram example
  56. 56. Histogram example
  57. 57. Histogram example contd.
  58. 58. Histogram example contd.
  59. 59. Histogram example contd.
  60. 60. Histogram example contd.
  61. 61. Histogram example contd.
  62. 62. Histogram example contd.
  63. 63. Histogram example contd. A selection of images and their histograms Notice the relationships between the images and their histograms Note that the high contrast image has the most evenly spaced histogram
  64. 64. Digital Image A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels
  65. 65. Digital Image contd.  Pixel values typically represent gray levels, colours, heights, opacities etc  Remember digitization implies that a digital image is an approximation of a real scene 1 pixel
  66. 66. Image is not perfect sometime
  67. 67. Image Enhancement  Spatial domain techniques  Point operations  Histogram equalization and matching  Applications of histogram-based enhancement  Frequency domain techniques  Unsharp masking  Homomorphic filtering
  68. 68. Examples of Image Enhancement
  69. 69. Land use and Land cover  Land use – defined by economic terms  Land cover – visible features  Both are important and are really inseparable  We depend on accurate LU/LC data for scientific and administrative purposes
  70. 70. LU and LC Classification System  general-purpose classification system  Land Utilization Survey  Land Use and Natural Resources Survey  Special Purpose Classification Systems  Wetlands Classification
  71. 71. Unsupervised and Supervised Classification  Supervised learning: discover patterns in the data that relate data attributes with a target (class) attribute.  These patterns are then utilized to predict the values of the target attribute in future data instances.  Unsupervised learning: The data have no target attribute.  We want to explore the data to find some intrinsic structures in them.
  72. 72. Application of RS Urbanization & Transportation  Urban planning  Roads network and transportation planning  City expansion  City boundaries by time  Wetland delineation
  73. 73. Application of RS Agriculture The application of remote sensing in agriculture include: -Soil sensing -Farm classification - Farm condition assessment - Agriculture estimation - Mapping of farm and agricultural land characteristics - Mapping of land management practices - Compliance monitoring
  74. 74. Application of RS  Monitoring dynamic changes  Urban/Rural infrastructure  Water logging & salinity  Assessment of spatial distribution of land resources  Infrastructure monitoring  Availability of usable land  Future planning for better land management for socio- economic development Land use/ land cover mapping
  75. 75. UNIT 4
  76. 76. GIS Basic Geographic Information System Allows the viewing and analysis of multiple layers of spatially related information associated with a geographic region/location The widespread collection and integration of imagery into GIS has been made possible through remote sensing With the increasing technological development of remote sensing, the development of GIS has simultaneously accelerated
  77. 77. Introduction contd.  A system to present information and analysis that has a geographic component.  A system that uses maps and images to track any sort of information.  Both spatial and attribute (tabular) data are integrated.
  78. 78. The GIS data types  Discrete geographic features  points, lines, areas  the contents of maps  with associated attributes  countable  conceived as tables with associated feature geometry  ESRI shape files
  79. 79. GIS Fields  Geography as a collection of continuous variables  measured on nominal, ordinal, interval, ratio scales  vector fields of direction and magnitude  exactly one value per point  z=f(x)  population density, land ownership, zoning
  80. 80. Arc Info
  81. 81. Arc Info Contd.
  82. 82. Field representations  Raster of rectangular cells  Raster of uniformly spaced points  Irregularly spaced points  Irregular areas (polygons)  Digitized contours  Triangular mesh (triangulated irregular network or TIN)  ESRI coverages
  83. 83. Field Representation
  84. 84. GIS as a data access mechanism  The geo library  place-based search  integrating information about a place  making access transparent
  85. 85. Types of GIS There are a number of Geographical Information Systems (GIS) (or GIS software) available today. They range from high- powered analytical software to visual web applications, and each of those are used for a different purpose. Due to the vast number of GIS available it is simply not possible to provide training for each in this course. However, there are common feature in all GIS. Understanding these basic features will give you confidence with any GIS system that you use in the future.  This course will cover three groups of GIS:  Web-based GIS: ONS and London Profiler  Geobrowser: Google Earth  Desktop GIS: Arc GIS
  86. 86. Web-based GIS Web-based GIS, or WebGIS, are online GIS applications which in most cases are excellent data visualisation tools. Their functionality is limited compared to software stored on your computer, but they are user-friendly and particularly useful as they not required data download. There are many WebGIS available, but in this course we will use two of them: the Office of National Statistics (ONS) Neighbourhood mapping tool and the London Profiler.
  87. 87. Geobrowser A Geobrowser is better explained with reference to an internet browser, i.e. Internet Explorer. In short, a geobrowser can be understood as an Internet Explorer for geographic information. Like the internet it allows the combination of many types of geographic data from many different sources. The biggest difference between the World Wide Web and the geographic web however is that everything within the latter is spatially referenced. Google Earth is the most popular geobrowser available and will be the one used for this course.
  88. 88. Desktop GIS A GIS, or GIS software, allows you to interactively work with spatial data. A desktop GIS is a mapping software that needs to be installed onto and runs on a personal computer. In this course, we will use ArcGIS, which is developed by ESRI. ArcGIS is what ESRI refer to as a suite of products which can be tailored to your need. ArcGIS is used for a vast range of activities, covering both commercial and educational uses. The basic version of ArcGIS is what we will be using in this course and is all the majority of GIS users will ever need.
  89. 89. Spatial Data  Spatial data  information about phenomena organized in a spatial frame  the geographic frame  Methods applied to spatial data that  add value  reveal patterns and anomalies  support decisions
  90. 90. Spatial Analysis  Methods whose results depend on the locations of phenomena in the frame  are not invariant under relocation  Some types of relocation may not affect social processes  rotation  relocation  inversion
  91. 91. Spatial analysis as a collaboration  The computer as butler to the human mind  Are maps “mere”?  Humans as sources of context  cross-sectional data are already rich in context
  92. 92. Taxonomies of spatial analysis  Thousands of methods  every one a command, menu item, icon, …  Based on data type  point pattern analysis  area (polygon) analysis  analysis of interactions
  93. 93. A six-way conceptual classification Query and reasoning Measurement Transformation Descriptive summary Optimization Hypothesis testing
  94. 94. Query and reasoning  Real-time answers to geographic questions  Where is…?  What is this?  How do I get from here to here?  Based on alternative views of a database
  95. 95. Measurement  Area  Distance  Length  Perimeter  Slope, aspect  Shape
  96. 96. Transformations  Buffering  Points in polygons  Polygon overlay  Spatial interpolation  Density estimation
  97. 97. Descriptive summary  Centers  Measures of spatial dispersion  Spatial dependence  Fragmentation  Fractional dimension
  98. 98. Optimization  Design to achieve specific objectives  Location of central point-like facilities to serve dispersed demand  Location of linear facilities  Design of boundaries for elections
  99. 99. Hypothesis testing  Geographic objects as a sample from a population  what is the population?  The independence assumption  the First Law of Geography  failure to find spatial dependence is always a Type II error  hell is a place with no spatial dependence
  100. 100. 1990 1564 2886 995
  101. 101. Application  Change Detection  Disaster Assessment  2004 Tsunami  Atmospheric Modeling  aerosols  air pollution  climate change  Ocean  topography  currents
  102. 102. UNIT 5
  103. 103. GPS  Stands for Global Positioning System  GPS is used to get an exact location on or above the surface of the earth (1cm to 100m accuracy).  Developed by DoD (Department of Defense, U.S.) and made available to public in 1983.  GPS is a very important data input source.  GPS is one of two (soon to be more) GNSS – Global Navigation Satellite System
  104. 104. GNSS  NAVSTAR – U.S. DoD (“GPS”)  GLONASS – Russian system  Galileo – European system (online in 2019?)  Compass/BeiDou-2 – Chinese system in development (operational with 10 satellites as of December, 2011; 35 planned)  GPS and GLONASS are free to use!
  105. 105. Segments of GPS Control Segment Space Segment User Segment Ground Antennas Master Station Monitor Station
  106. 106. Data Models  Raster Model  The first GIS model developed  Based on grids of cells that are assigned values and grouped into layers  Vector Model  Uses points, lines, and polygons define data classes  Grouped into themes
  107. 107. GNSS Comparison  GLONASS  24 satellites (100% deployed)  3 orbital planes  GPS  31 satellites (>100% deployed)  6 orbital planes
  108. 108. System Components  Receiver  Receives satellite signals  Compiles location info, ephemeris info, clock calibration, constellation configuration (PDOP)  Calculates position, velocity, heading, etc…  Data Collector  Stores positions (x,y,z,t)  Attribute data tagged to position  Software  Facilitates file transfer to PC and back  Performs differential correction (post-processing)  Displays data and
  109. 109. Differential GPS  Real Time  Post Process
  110. 110. GPS Applications  GPS uses into five categories  Location – positioning things in space  Navigation – getting from point a to point b  Tracking - monitoring movements  Mapping– creating maps based on those positions  Timing – precision global timing
  111. 111. GPS Applications  Agriculture  Surveying  Navigation (air, sea, land)  Engineering  Military operations  Unmanned vehicle guidance  Mapping