chapter 1. introduction to geospatial information, technology, and science jingxiong zhang remote...

Chapter 1. Introduction to Geospatial Information, Technology,

and Science

Chapter 1. Introduction to Geospatial Information, Technology,

and Science

Jingxiong ZHANG

Remote Sensing Information Engineering

Wuhan University

E-mail: jxzhang@whu.edu.cn

1. 汶川地震1. 汶川地震

D-InSAR results from Linlin GeD-InSAR results from Linlin Ge

The University of New SouthWales, Cooperative Research Centre for Spatial Information and New

South Wales Department of Lands

灾区专题信息

ADS40 数字传感器系统GPS 卫星

GPS 基准站

ADS40 系统

1

2

34 5

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

北川局部影像图北川局部影像图

ADS40, 0.3m, 28/05/2008ADS40, 0.3m, 28/05/2008

汶川县震后正射影像（ GSD 0.5m)

ADS40影象

都江堰 QuickBird 图像（地震前）都江堰 QuickBird 图像（地震前）

Cosmo-1 米图像（地震后）Cosmo-1 米图像（地震后）

Cosmo-1 米图像疑似倒塌区域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%房屋疑似倒塌面积占总面积的 14.8%

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

降雨后入湖水量过程模拟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

Information gathering

Optical: SPOT 5, CBERS 02B, ALOS,福卫 2,

Quickbird,KH-11, …

SAR: COSMO, TerraSAR, RADARSAT, ASAR,

PALSAR,RS-1… 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

Information extraction (RS+GIS) Barrier lakes (GIS+RS)

Key questions in landscape ecology1. 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?

ContentsContents

Geospatial information Geospatial information technology (3S) GI Science & Technology

Information about places on the Earth’s surface Knowledge about where something is Knowledge about what is at a given location

Geospatial informationGeospatial information

Geographic resolution

– detailed (individual buildings, trees)

– coarse (whole country, global) 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 characteristicsSome characteristics

For collecting and handling geo-information Global Positioning System (GPS) Remote sensing (RS) Geographic information systems (GIS)

Geospatial information technologyGeospatial information technology

a system of Earth-orbiting satellites transmitting precisely timed signals, which are

received by a special electronic device provides direct measurement of position

GPSGPS

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

Remote SensingRemote Sensing

use of Earth orbiting satellites to capture information about the surface and atmosphere below

satellites vary depending on how much detail can be seen, what parts of the electromagnetic spectrum are sensed

signals transmitted to Earth receiving stations where they are transformed for dissemination as digital images

ASPRS adopted a combined formal definition of ASPRS adopted a combined formal definition of photogrammetryphotogrammetry andand remote sensingremote sensing as (Colwell, as (Colwell, 1997):1997):

““the art, science, and technology of obtaining the art, science, and technology of obtaining reliable information about physical objects and reliable information about physical objects and the environment, through the process of the environment, through the process of recording, measuring and interpreting imagery recording, measuring and interpreting imagery and digital representations of energy patterns and digital representations of energy patterns derived from noncontact sensor systems”.derived from noncontact sensor systems”.

ASPRS adopted a combined formal definition of ASPRS adopted a combined formal definition of photogrammetryphotogrammetry andand remote sensingremote sensing as (Colwell, as (Colwell, 1997):1997):

““the art, science, and technology of obtaining the art, science, and technology of obtaining reliable information about physical objects and reliable information about physical objects and the environment, through the process of the environment, through the process of recording, measuring and interpreting imagery recording, measuring and interpreting imagery and digital representations of energy patterns and digital representations of energy patterns derived from noncontact sensor systems”.derived from noncontact sensor systems”.

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 suborbitalor 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 suborbitalor satellite platform.

Geographic information systems (GISs)Geographic information systems (GISs)

a system for input, storage, manipulation, and output of geographic information

a class of software a practical instance of a GIS combines software

with hardware, data, a user, etc., to solve a problem, support a decision, help to plan

keep inventories of what is where manage properties, facilities judge the suitability of areas for different

purposes help users make decisions about places, to plan make predictions about the future … these require human expertise as well

The integration of “3S”The integration of “3S”

• RS + GIS • RS + GPS • GIS + GPS• RS + GIS + GPS

StrategiesStrategies

Levels/depthsLevels/depths

• Data• Platforms• Functions

SimultaneousnessSimultaneousness

• Simultaneous• Quasi-simultaneous• Non-simultaneous

TransportationTransportation

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‘

a delivery company, e.g. Federal Express, UPS, needs to– keep track of shipments, know where they are– plan efficient delivery routes

a traveling salesperson needs– a system in the car for finding locations, routes

Agriculture (farmers)Agriculture (farmers)

increasingly use detailed maps and images to plan crops– analyze yields– plan efficient application of fertilizers,

chemicals these techniques are known as precision

agriculture

ForestryForestry

need to keep track of what timber is growing where

need to be able to plan timber harvest - how to provide for timber needs now, but maintain a healthy forest resource for the future

need to plan locations of roads, methods of cutting and removing logs to comply with environmental regulations

need to manage forests for many purposes, including recreation

GIScience (finally!)GIScience (finally!)

is the science behind the technology– fundamental questions raised by tech– Keep tech at the cutting edge

is a multidisciplinary field plan crops– cartography, geodesy, photogrammetry, CS– cognitive psychology, spatial statistics– 'geomatics‘, 'geoinformatics'

is a multidisciplinary field plan crops– the Earth (2-D surface, 3D atmosphere,

oceans, sub-surface– any multi-dimensional frame

The big questions of GIScienceThe big questions of GIScience

representation– sampling, data format– criteria (accuracy, data volume, computing)

Uncertainty– description, visualization, simulation

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?

data models and structures– store a given representation efficiently– retrieve information rapidly through

appropriate indexing– achieve interoperability between systems

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?

analytical tools– methods of analysis needed to support

specific types of decisions made using GIS the University Consortium for Geographic

Information Science is a group of over 30 U.S. universities dedicated to promotion of GIScience– http://www.ucgis.org

The disciplines of GIScienceThe disciplines of GIScience

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

Digital technology and information in general– computer science, particularly: databases,

computational geometry, image processing, pattern recognition

– information science

The EarthThe Earth

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

CF. Conceptual FoundationsCV. Cartography and VisualizationDA. Data AnalysisDE. Design AspectsDM. Data ModelingDN. Data ManipulationGC. GeocomputationGD. Geospatial DataGS. GI S&T and SocietyOI. Organizational and Institutional Aspects

GI S&T Body of knowledge

Conceptual framework

The object (identity-based) viewThe object (identity-based) view► dependent role that location, attribute, and dependent role that location, attribute, and

time play in the object viewtime play in the object view► Model “gray area” phenomena, such as Model “gray area” phenomena, such as

categorical coverages (a.k.a. discrete fields), in categorical coverages (a.k.a. discrete fields), in terms of objectsterms of objects

The field (location-based) viewThe field (location-based) view► field view’s description of “objects” as field view’s description of “objects” as

discretizations of continuous patternsdiscretizations of continuous patterns► Model “gray area” phenomena, such as Model “gray area” phenomena, such as

categorical coverages (a.k.a. discrete fields), in categorical coverages (a.k.a. discrete fields), in terms of fieldsterms of fields

The process (time-based) viewThe process (time-based) view► Differentiate a Differentiate a process-oriented view of the process-oriented view of the

world from the state-based views (object and world from the state-based views (object and field)field) common to GIS common to GIS

CF4-2 Scale

Perform basic scale calculations Differentiate among the concepts of scale (as in map

scale), scope, and resolution Determine the mathematical relationships among

scale, scope, and resolution, including Topfer’s Radical Law

Identify geographic phenomena, patterns, and processes that are scale-dependent

Identify geographic phenomena, patterns, and processes that are scale-independent

Compare and contrast the nature and behavior of phenomena at the “table-top” scale with phenomena at geographic scales

CF7 Imperfections in geographic informationOur 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.

CV. Cartography and Visualization 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.

DA. Data Analysis

DA1 Academic foundations of geospatial data analysisDA2 Query operations & query languagesDA3 Geometric operations on spatial objectsDA4 Modeling relationships and patternsDA5 Analysis of surfaces DA6 Spatial statisticsDA7 Geostatistics DA8 Spatial econometricsDA9 Data MiningDA10 Network analysisDA11 Operations research

DA4-5 Spatial processes and their patterns Differentiate between processes and

patterns Demonstrate how patterns are realizations

of processes Describe a simple process model that would

generate a given set of spatial patterns Explain how diffusion modeling can be used

to yield and explain spatial patterns

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.

DA7 Geostatistics 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).

DM. Data Modeling

DM1 Basic storage and retrieval structures DM2 DBMS and the relational model DM3 Tessellation data models DM4 Vector data models (examples and

implementations) DM5 Multiple scale representation/models

(examples and implementations) DM6 Object (oriented) and object based models

(examples and implementations) DM7 Temporal representation/models DM8 Metadata DM9 Data exchange and interoperability

GC. Geocomputation

GC1 History and trends in geocomputation GC2 Uncertainty GC3 Computational aspects and

neurocomputing GC4 Fuzzy sets GC5 Cellular Automata (CA) models GC6 Heuristics GC7 Genetic algorithms GC8 Agent-based models GC9 Activity analysis

GD. Geospatial Data

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

SummarySummary

geographic information is information about places on the earth's surface

geographic information technologies include global positioning systems (GPS), remote sensing and geographic information systems.

geographic information science is the science behind GI technology

ReferencesReferences

Michael F. Goodchild. (1997) What is Geographic Information Science?, NCGIA Core Curriculum in GIScience,http://www.ncgia.ucsb.edu/giscc/units/u002/u002.html.

Goodchild, M.F. (1992) Geographical information science. International Journal of Geographical Information Systems 6(1): 31-45.

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.

QuestionsQuestions

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.