Download PowerPoint Presentation - Earth Systems Education

Dept. of Civil and Environmental
Engineering and Geodetic Science
College of Engineering
The Ohio State University
Columbus, Ohio 43210
[email protected]
Data Acquisition
Data Acquisition
Analysis & Modeling
F(
)xyz=f(p1)xyz+f(p2)xyz+…+f(pN)xyz
Data Organization
Map Composition
Analysis & Modeling
F( ) =Layer1+Layer2+ … + LayerN
Result
Report
Result
Report
Definition of GIS
GIS
Component
Input
Management & Analytical Modules
Data Acquisition
- Geodetic Positioning
- Remote Sensing
- Field Sampling
Analog Data Conversion
- Scan
- Digitize
Output
Data Output
Management
- Data Storage
- Data Retrieval, Expand
Edit, and Update
- Query
Analytical Modules
- Data Conversion
- Data Manipulation
- Modeling
- Visual Presentation
- Analog Map Output
- Reports
GIS Data Elements & Characteristics
Data Types
Vector
- Based on mathematical function
- point, line, polygon, & surface
Point
Polygon
Lines
Surface
Image
Grid
Raster
- Data present on a fixed grid
structure (matrix)
- image, grid
Data Characteristics
Space – feature locations
Attribute – feature attributes,
qualities & characteristics
of geographic places.
Relationships Between Features
Time – additional spatial
dimension
GIS Data Layers
Data Organization
Research Data Layers
Research Data Layers
Basemap
Coordinate System
- Nominal Data
- categorized & named – class value
- relates numbers to names
- ex: tree species, soil type, parcel owner names
- Ordinal data
- classes are in a rank or order
- ex: 1 - good, 2 – moderate, 3 - poor
- Interval data
- intervals between data values are meaningful
- quantify differences
- ex: elevation, °F
- Ratio data
- measures a condition with a natural zero value
- quantify proportions
- ex: electromagnetic radiation, rainfall, slope
Basemap
- Provides spatial relation and geometric shape of ground
features
- Serves as a foundation for data rectifications
Coordinate System
- Geographic coordinate system for small scale research.
- Plane coordinate system for large scale research.
GIS Data Availability
GIS DATA
Remotely Sensed Data
Spatial & Biophysical
Spatial Only
-
B/W aerial photo
Panchromatic images
Radar image
GPS
Bathymetry
LIDAR
-
Color aerial photo
Multispectral images
Hyperspectral image
Multiband radar image
Conventional Data
- Data driven from maps.
- Statistical data from published
tables.
- CAD drawings.
- Data from archives using the Internet
or other network.
- 4Ds: DRGs, DLGs, DEMs, DOQQs.
DRG
DLG
DEM
DOQQ
Inventory Operation
Measurement
A=0.175km2
P=1.5km
Inventory operation is to obtain
information from existing data
layers or databases
Measurement
Spatial Query
- Distance
- Area/Size
- Perimeter
Spatial Query
- Graphic Query
- Boolean Query: AND, OR, NOT
Database operations
Database Operations
- Lists & Reports
- Relational Database
Spatial Analysis
Soil
Soil 1
Soil 3
Landuse
Hydrology Observation
Urban
Station 1
Corn
Forest
Soil 4
Soil 2
Soybean
River
Spatial Operations
Soil type and Landuse along
the river, but within 150m
radius of Station 2
Station 2
Station3
Spatial analysis can be used to
derive spatial relationships
among data layers
The basic operation involves:
- Buffer operation
- Overlay operation
Network Analysis
Service Area
Routing &
Network Distance
Network analysis is to solve the
problem or model the behavior of
a network structure by connecting
lines, such as a transportation
network or a stream network
The basic operation involves:
Pollutant Transport
Effective Area
Time to Distribute
- Locating routes
- Determine which facility or feature
is closest (allocation)
- Modeling travel directions
- Obtaining area around a site within
a given distance or time
3-D Analysis
3-D analysis is to analyze spatial
information in a 3-D perspective.
Visualization
- Provide 3-D view of spatial data
Terrain analysis
- Viewshed
- Elevation
- Slope, Aspect, Hillshading
- Watershed
DEM
Slope Aspect Sink Stream
Space-Time Analysis
Time is used as a spatial dimension (t).
2-D View
- The Space-Time concept is to model spatiallyrelated events by using time as one dimension.
This is so that the correlation between spatial
movement and time can be derived by using
conventional mathematical functions, such as
distance, in 3D:
Distance( )x,y,t = sqrt(x2+y2)
Velocity( )x,y,t= sqrt(x2+y2)/t
Space-Time Distance( )x,y,t= sqrt (x2+y2+t2)
X
Y
3-D View
Time
X
X
Y
Y
Time
T3
Y
T2
T1 X
Time
Time
River Boundary Change in Time
X
X
Change in Time
Y
X
Change in Time
Observation Points
Function in Time
- Data sets are registered to a common
coordinate system
- Geospatial data sets can be stored
across a distance
- Analytical tools are available for
modeling
environmental processes
- GIS & remote sensing offer a way to study
latitudinal gradients effectively