GIS for Environmental GIS for Environmental ScienceScience

ENSC 3603ENSC 3603

Class 22Class 224/2/094/2/09

Spatial Data AnalysisSpatial Data Analysis

ModelingModeling

Data miningData mining

Spatial Data AnalysisSpatial Data Analysis

• Classical spatial analysis: Deterministic– Good at answering where and what

• Modern spatial analysis: Probabilistic– Tries to answer what-if scenarios that contain a

certain amount of uncertainty due to data that is incomplete or has errors.

– Major objectives are to investigate possible spatial relationships such as association, neighborhood, proximity, and autocorrelation.

– And to discover spatial heterogeneity such as clustering, pattern, dispersion, variability and anomaly. (Lo and Yeung,2007 Chapter 10)

Spatial Data AnalysisSpatial Data Analysis

• Modern spatial analysis consists of:– a database model– a set of statistical and graphical data analysis

tools– a set spatial visualization tools

Spatial Data AnalysisSpatial Data Analysis

• Ways spatial analysis can be used with GIS:

–Free standing, ex. CrimeStat, GeoVista–Embedded in Statistical Software, ex.

SAS/GIS, S+SPATIALSTAT–Loose coupling, not used much any more–Close coupling, ex. ArcGIS Spatial analyst

extension–Complete integration, ex. Idrisi

Spatial Data AnalysisSpatial Data Analysis

• Descriptive Statistics–Central tendency

• Mean, sum of values divided by the number of values

• Median, middle value in values listed least to most• Mode, most frequently occurring value.

Spatial Data AnalysisSpatial Data Analysis

• Descriptive Statistics

Accessed 4-4-07 http://syque.com/quality_tools/toolbook/Variation/measuring_centering.htm

Spatial Data AnalysisSpatial Data Analysis

• Dispersion– Depicts the pattern of the spread of values

• Range, the difference between the largest and the smallest measurement value.

• Standard deviation, The square root of the sum of the values subtracted from the mean squared, divided by the number of values minus 1.

• Skewness, (mean – median)/ standard deviation,– Measures the degree of asymmetry

• Kurtosis, indicates the peakedness or the spread of the frequency distribution

Spatial Data AnalysisSpatial Data Analysis

• Spatial Autocorrelation–Remember Toblers First Law of Geography:–“everything is related to everything else, but

near things are more related than distance things”, (Tobler, 1970)

–Geary’s Index and Moran’s Index are used to measure autocorrelation.

Spatial Data AnalysisSpatial Data Analysis

• Quadrant Counts– A spatial pattern is covered with a Quadrat or grid and

the number of points in each quadrat are counted and tabulated. Quadrat size depends on application.

• Nearest-Neighbor analysis– Measures distances between sample points and their

nearest neighboring points. The mean of the nearest-neighbor distance measurements is compared with expected mean distance.

Spatial Data AnalysisSpatial Data Analysis

• Trend Surface Analysis–Used with continues surfaces such as

elevation. Can also be used to explore other data by showing regional and local trends.

Spatial Data AnalysisSpatial Data Analysis

• Gravity models–Most widely used of the spatial interaction

models.–Spatial interaction is any movement over

space that results from a human process.• Ex. Population migration, journey to work,

information and commodity flows, and other activity that has to do with the movement of people, goods or ideas form one place to another.

Spatial Data AnalysisSpatial Data Analysis

• Gravity models–Idea borrowed from Newton’s law of gravity;

• The force of attraction of two bodies is proportional t the product of their masses but inversely proportional to the squared distance separating them.

• F =mi x mj/d2ij

– m = mass– d = distance (straight-line)Ex. Cities close to each other have greater interaction than

cities further apart, and larger cities have greater influence that smaller ones.

Spatial Data AnalysisSpatial Data Analysis

• Network Analysis–Closely related to spatial interaction modeling.

• A network refers to a system of lines that have distance, connectivity and are topologically structured.– Ex. Transportation lines such as roads, railways and

rivers and streams.

Spatial ModelingSpatial Modeling

• Spatial modeling process - When spatial data analysis is used to solve a spatial problem using a sequence of geoprocessing steps.

Spatial ModelingSpatial Modeling• Model, a simplified representation of the real

world and it’s processes.• GIS and Modeling and managing Agricultural

non-point-source pollution (AGNPS)• USGS AGNPS Water shed Modeling with

GIS databases by Finn et al.http://carto-research.er.usgs.gov/watershed/ppt/AGNPS_Vegas_v2.PPT#256,1,AGNPS

Watershed Modeling with GIS

Other models include routing applications such as the best routes for emergency vehicles and hazardous materials transpiration.

Spatial Data MiningSpatial Data Mining

• Uses machine learning or artificial intelligence to analyze huge amounts of geospatial data.

• Data mining is also known as knowledge discovery in databases. This is the process of finding previously unknown information from huge data warehouses

• A logical sequence of data-processing steps including:– Data integration and cleaning,– Data selection and transformation– Data mining– Knowledge discovery and construction– Deployment

Spatial Data MiningSpatial Data Mining• Spatial Data Mining Techniques are complex

mathematically and computationally and include:– Spatial Classification, looks for the best criteria for data set

categorization.– Spatial Prediction, regression methods for prediction.– Spatial Class/Concept Description, a generalization process.– Spatial Association, looks for topological, spatial and distance

relationships.– Spatial Clustering, find the optimum number of clusters in a data

set.– Spatial Outlier Analysis, Graphical and Quantitative outlier

detection.– Spatial time-Series Analysis, most complex logically and

technically.

Read and DoRead and Do• Spatial analyst Chapter 2 quick-start tutorial. Spatial

PDF and Spatial.zip Data are one the Class web site.• In ArcGIS turn on Spatial Analyst: Tools, Extensions,

Then right click on the tool bar to check Spatial analyst on.

• Read Chapter 10 in Lo and Yeung (2007) • Next Thursday turn in ESRI Spatial Analyst quick start

tutorial map in and email as a PDF. Use map layout and design on the map.

• Review progress on your Project

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