2. Chapter 1. Introduction to Geospatial Information, Technology, and Science Jingxiong ZHANG Remote Sensing Information Engineering Wuhan University E-mail: jxzhang@whu.edu.cn

4. 1. 汶川地震

5. D-InSAR results from Linlin Ge The University of New South Wales, Cooperative Research Centre for Spatial Information and New South Wales Department of Lands

6. 灾区专题信息

7. ADS40 数字传感器系统 GPS 卫星 GPS 基准站 ADS40 系统 1 2 3 45 6 1. 传感器头 SH40 ：包括 IMU 、 数字镜头 2. 控制单元 CU40 ： GPS 单元、 POS 计算单元 3. 大规模存储器 MM40 4. 系统控制操作界面 OI40 5. 导航指示 GI40 6. 陀螺稳定平台 PAV30

8. 北川局部影像图 ADS40, 0.3m, 28/05/2008

10. 汶川县震后正射影像（ GSD 0.5m) ADS40 影象

11. 都江堰 QuickBird 图像（地震前）

12. Cosmo-1 米图像（地震后）

13. Cosmo-1 米图像疑似倒塌区域 房屋疑似倒塌面积 占总面积的 14.8%

16. 唐家山堰塞湖库区河道变化情况（白色区域） 灾后影像： SPOT5 分 辨 率： 10 米 成像时间： 2008.5.16 灾前影像： SPOT5 分 辨 率： 10 米 成像时间： 2006.11.10

17. 降雨后入湖水量过程模拟 唐家山堰塞湖以上集水面积为： 3567km2

18. n Information gathering Optical: SPOT 5, CBERS 02B, ALOS, 福卫 2, Quickbird,KH-11, … SAR: COSMO, TerraSAR, RADARSAT, ASAR, PALSAR,RS-1… n High resolution data (RS+GPS/INS) –ADS40 三线阵扫描仪采集北川、江油、都江堰数据 –ALS50 机载激光雷达获取震后堰塞湖区数据 n Information extraction (RS+GIS) n Barrier lakes (GIS+RS)

19. Key questions in landscape ecology 1.What process(es) creates landscape pattern? 2.What are the consequences? 3.How do we measure pattern? At what scale? 4.How does pattern change through time? 5.How do we predict and manage pattern?

22. Contents n Geospatial information n Geospatial information technology (3S) n GI Science & Technology

23. n Information about places on the Earth’s surface n Knowledge about where something is n Knowledge about what is at a given location Geospatial information

24. Geographic resolution –detailed (individual buildings, trees) –coarse (whole country, global) n Often relatively static Very voluminous –1 gigabyte of data US street network –terabyte satellite data daily Digital information –coded in bits, –data as sequences of bits –“bags of bits”, disks, Internet Some characteristics

25. n For collecting and handling geo-information n Global Positioning System (GPS) n Remote sensing (RS) n Geographic information systems (GIS) Geospatial information technology

26. n a system of Earth-orbiting satellites transmitting precisely timed signals, which are n received by a special electronic device n provides direct measurement of position GPS

27. Public land survey system - Elementary Surveying, Wolf and Brinker, 1994.

28. Remote Sensing n use of Earth orbiting satellites to capture information about the surface and atmosphere below n satellites vary depending on how much detail can be seen, what parts of the electromagnetic spectrum are sensed n signals transmitted to Earth receiving stations where they are transformed for dissemination as digital images

29. ASPRS adopted a combined formal definition of photogrammetry and remote sensing as (Colwell, 1997): “the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from noncontact sensor systems”. ASPRS adopted a combined formal definition of photogrammetry and remote sensing as (Colwell, 1997): “the art, science, and technology of obtaining reliable information about physical objects and the environment, through the process of recording, measuring and interpreting imagery and digital representations of energy patterns derived from noncontact sensor systems”.

30. A remote sensing instrument collects information about an object or phenomenon within the instantaneous-field-of-view (IFOV) of the sensor system without being in direct physical contact with it. The sensor is located on a suborbital or satellite platform. A remote sensing instrument collects information about an object or phenomenon within the instantaneous-field-of-view (IFOV) of the sensor system without being in direct physical contact with it. The sensor is located on a suborbital or satellite platform.

32. Geographic information systems (GISs) n a system for input, storage, manipulation, and output of geographic information n a class of software n a practical instance of a GIS combines software with hardware, data, a user, etc., to solve a problem, support a decision, help to plan

33. n keep inventories of what is where n manage properties, facilities n judge the suitability of areas for different purposes n help users make decisions about places, to plan n make predictions about the future n … these require human expertise as well

37. The integration of “3S”

38. RS + GIS RS + GPS GIS + GPS RS + GIS + GPS Strategies

39. Levels/depths Data Platforms Functions

40. Simultaneousness Simultaneous Quasi-simultaneous Non-simultaneous

41. Transportation n a state department of transportation needs to –store information on the state of pavement everywhere on the state highway network –maintain an inventory of all highway signs –analyze data on accidents, look for 'black spots‘

42. n a delivery company, e.g. Federal Express, UPS, needs to –keep track of shipments, know where they are –plan efficient delivery routes n a traveling salesperson needs –a system in the car for finding locations, routes

43. Agriculture (farmers) n increasingly use detailed maps and images to plan crops –analyze yields –plan efficient application of fertilizers, chemicals n these techniques are known as precision agriculture

44. Forestry n need to keep track of what timber is growing where n need to be able to plan timber harvest - how to provide for timber needs now, but maintain a healthy forest resource for the future n need to plan locations of roads, methods of cutting and removing logs to comply with environmental regulations n need to manage forests for many purposes, including recreation

45. GIScience (finally!) n is the science behind the technology –fundamental questions raised by tech –Keep tech at the cutting edge n is a multidisciplinary field plan crops –cartography, geodesy, photogrammetry, CS –cognitive psychology, spatial statistics –'geomatics‘, 'geoinformatics' n is a multidisciplinary field plan crops –the Earth (2-D surface, 3D atmosphere, oceans, sub-surface –any multi-dimensional frame

46. The big questions of GIScience n representation –sampling, data format –criteria (accuracy, data volume, computing) n Uncertainty –description, visualization, simulation n relationship btw the representation and the user –how can computer representations be made more like the ways people think? –how do people reason with, learn about, communicate about the geographical world? –output from GIS made more intelligible?

47. n data models and structures –store a given representation efficiently –retrieve information rapidly through appropriate indexing –achieve interoperability between systems n display –how do methods of display affect the interpretation of geographic data? –how can the science of cartography be extended to take advantage of the power of the digital environment?

48. n analytical tools –methods of analysis needed to support specific types of decisions made using GIS n the University Consortium for Geographic Information Science is a group of over 30 U.S. universities dedicated to promotion of GIScience –http://www.ucgis.orghttp://www.ucgis.org

49. The disciplines of GIScience n Geospatial information technologies –Cartography: map-making –remote sensing: Earth observation from space –Geodesy: accurate measurement of the Earth –Surveying: accurate measurement of natural and human-made features on the Earth –Photogrammetry: measurement from photographs and images –image processing: analysis of image data

50. n Digital technology and information in general –computer science, particularly: databases, computational geometry, image processing, pattern recognition –information science

51. The Earth n Earth surface & near-surface, physical & human –geology –geophysics –oceanography –agriculture –biology (ecology, biogeography) –environmental science –geography –sociology –political science –anthropology

53. CF. Conceptual Foundations CV. Cartography and Visualization DA. Data Analysis DE. Design Aspects DM. Data Modeling DN. Data Manipulation GC. Geocomputation GD. Geospatial Data GS. GI S&T and Society OI. Organizational and Institutional Aspects GI S&T Body of knowledge

54. Conceptual framework n The object (identity-based) view ► dependent role that location, attribute, and time play in the object view ► Model “gray area” phenomena, such as categorical coverages (a.k.a. discrete fields), in terms of objects n The field (location-based) view ► field view’s description of “objects” as discretizations of continuous patterns ► Model “gray area” phenomena, such as categorical coverages (a.k.a. discrete fields), in terms of fields n The process (time-based) view ► Differentiate a process-oriented view of the world from the state-based views (object and field) common to GIS

55. CF4-2 Scale n Perform basic scale calculations n Differentiate among the concepts of scale (as in map scale), scope, and resolution n Determine the mathematical relationships among scale, scope, and resolution, including Topfer’s Radical Law n Identify geographic phenomena, patterns, and processes that are scale-dependent n Identify geographic phenomena, patterns, and processes that are scale-independent n Compare and contrast the nature and behavior of phenomena at the “table-top” scale with phenomena at geographic scales

56. CF7 Imperfections in geographic information Our models (mental, digital, visual, etc.) of the geographic environment are necessarily imperfect. While the mathematical principle of homomorphism (often operationalized as “fitness for use”) allows for imperfect data to be useful as long as they yield accurate results, imperfections are frequently problematic. two types of imperfection: vagueness (a.k.a. fuzziness, imprecision, and indeterminacy), generally caused by oversimplification in the conceptualization processes discussed throughout this knowledge area; and uncertainty (or ambiguity), generally the result of imperfect measurement processes (as discussed in Knowledge Area GD). Both of these can be manifested in all forms of geographic information, including space, time, attribute, categories, and even existence.

57. CV. Cartography and Visualization n Cartography and visualization primarily relate to the visual display of geographic information. This knowledge area addresses the complex issues involved in effective visual thinking and communication of geospatial data and of the results of geospatial analysis. This knowledge area reflects much of the domain of cartography and visualization, although some concepts and skills in these areas can be found in other Knowledge Areas.

58. DA. Data Analysis DA1 Academic foundations of geospatial data analysis DA2 Query operations & query languages DA3 Geometric operations on spatial objects DA4 Modeling relationships and patterns DA5 Analysis of surfaces DA6 Spatial statistics DA7 Geostatistics DA8 Spatial econometrics DA9 Data Mining DA10 Network analysis DA11 Operations research

59. DA4-5 Spatial processes and their patterns n Differentiate between processes and patterns n Demonstrate how patterns are realizations of processes n Describe a simple process model that would generate a given set of spatial patterns n Explain how diffusion modeling can be used to yield and explain spatial patterns

60. DA10 Network analysis Network analysis encompasses a wide range of procedures, techniques, and methods that allow for the examination of phenomena that can be modeled in the form of connected sets of edges and vertices. Such sets are termed a network or a graph, and the mathematical basis for network analysis is known as graph theory. Graph theory contains descriptive measures and indices of networks (such as connectivity, adjacency, capacity, and flow) as well as methods for proving the properties of networks. Networks have long been recognized as an efficient way to model many types of geographic data, including transportation networks, river networks, and utility networks (electric, cable, sewer and water, etc.) to name just a few. The data structures to support network analysis are covered in DM4.

61. DA7 Geostatistics n Geostatistics may be thought of as a subdomain of spatial statistics, but given its increasing popularity—especially in the physical sciences using continuous geospatial variables, such as levels of precipitation in a region—it is treated here as a separate unit. The fundamental structure of geostatistics is based on the nature of variograms and its use for spatial prediction (kriging).

62. DM. Data Modeling n DM1 Basic storage and retrieval structures n DM2 DBMS and the relational model n DM3 Tessellation data models n DM4 Vector data models (examples and implementations) n DM5 Multiple scale representation/models (examples and implementations) n DM6 Object (oriented) and object based models (examples and implementations) n DM7 Temporal representation/models n DM8 Metadata n DM9 Data exchange and interoperability

63. GC. Geocomputation n GC1 History and trends in geocomputation n GC2 Uncertainty n GC3 Computational aspects and neurocomputing n GC4 Fuzzy sets n GC5 Cellular Automata (CA) models n GC6 Heuristics n GC7 Genetic algorithms n GC8 Agent-based models n GC9 Activity analysis

64. GD. Geospatial Data n GD1 Earth geometry n GD2 Land partitioning systems n GD3 Coordinate systems n GD4 Datums n GD5 Map projections n GD6 Data quality n GD7 Land surveying and GPS n GD8 Digitizing n GD9 Field data collection n GD10 Aerial surveys and photogrammetry n GD11 Satellite and shipboard remote sensing n GD12 Data standards and infrastructures

66. Summary n geographic information is information about places on the earth's surface n geographic information technologies include global positioning systems (GPS), remote sensing and geographic information systems. n geographic information science is the science behind GI technology

67. References n Michael F. Goodchild. (1997) What is Geographic Information Science?, NCGIA Core Curriculum in GIScience,http://www.ncgia.ucsb.edu/giscc/units/ u002/u002.html. n Goodchild, M.F. (1992) Geographical information science. International Journal of Geographical Information Systems 6(1): 31-45. n Wright, D.J., M.F. Goodchild, and J.D. Proctor (1997) Demystifying the persistent ambiguity of GIS as "tool" versus "science". Annals of the Association of American Geographers 87(2): 346-362.

68. Questions 1. What do 'geographic' and 'spatial' mean, and why is the term 'geospatial' popular? 2. Identify any traditional disciplines missing from the lists given in the unit and explain their relationship to GIScience. 3. Explain why geographic information science should or should not be a distinct discipline: –with its own journals. –with its own departments. –with its own degrees.