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Advanced GIS for UCCE Analysis

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Pattern of point and polygon values. Continuous data: gradients and localized variability ... Provides a single statistics summarizing pattern. For continuous data ... – PowerPoint PPT presentation

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Title: Advanced GIS for UCCE Analysis


1
Advanced GIS for UCCE - Analysis
  • August 22, 2007
  • Maggi Kelly
  • Department of Environmental Science, Policy, and
    Management
  • Karin Tuxen-Bettman
  • GIIF
  • http//giif.cnr.berkeley.edu

We will begin at 110 PM. Login info Username
!workshopuser Password 1WRKshop USR! Domain
CAMPUS
Geospatial Imaging Informatics Facility College
of Natural Resources _at_ UC Berkeley
2
This Afternoons Outline
  • Overview of specific GIS analysis
  • Spatial statistics
  • Landscape ecology
  • Hydrologic modeling and watershed delineation
  • Examples of spatial analysis in natural resource
    science and ecology
  • Overview of land cover datasets
  • Other software for integrated statistical
    analysis
  • Spatial analysis and statistics tools in ArcGIS
    9.2
  • Computer exercises Choose from 1 or more
    applications, including
  • Map measure polygonal clusters and patterns
  • Measure point patterns and distributions
  • Hydrologic modeling and watershed delineation
    using the Model Builder
  • Using Google Earth for 3D visualization

3
What are Spatial Statistics?
  • Spatial statistics are not traditional statistics
    about things that happen to have spatial
    component…
  • Spatial statistics take space into account, e.g.
    distance.
  • Two types
  • Descriptive characterizes pattern
  • How are points distributed?
  • What is the pattern?
  • Where are the clusters?
  • Quantitative quantifies/measures pattern
    (e.g. pattern, relationships, trends)
  • How clustered/dispersed is the data?
  • What are the relationships with other data?

4
What is Landscape Ecology?
  • Spatial pattern is linked to ecological process
  • i.e. Turner, Forman and Godron, etc.
  • A landscape is made of
  • Structure
  • Patch, corridor, mosaic
  • Size, shape, spatial configuration
  • Function
  • Population dynamics, nutrient cycling,
    competition, succession, physical processes
  • Change
  • Anthropogenic change
  • Natural change

5
What is Hydrologic Modeling Watershed
Delineation?
  • Hydrology concerns the movement of water across a
    surface, the flow of water through a drainage
    system

6
Methods for performing GIS analysis
  • Ask your question,
  • Collect your data,
  • Choose a GIS analysis method,
  • Calculate the statistic(s) and/or metrics,
  • Interpret the statistics, and
  • Test significance.

7
Land Cover Datasets
  • Multi-source Land Cover Dataset (2002, 2006)
  • Source CDF (http//frap.cdf.ca.gov/data/frapgisda
    ta/select.asp)
  • Spatial resolution 100 meter (2002), 30 m (2006)
  • Landfire dataset (2005)
  • Source USGS (http//www.landfire.gov/products_ove
    rview.php)
  • Spatial resolution 30 m
  • Coastal-Change Analysis Project (2002) …coastal
    counties only!
  • Source NOAA (http//csc.noaa.gov/crs/lca/pacificc
    oast.html)
  • Spatial resolution 30 m
  • National Land Cover Dataset
  • Source USGS (http//edcftp.cr.usgs.gov/pub/data/l
    andcover/states/)
  • Spatial resolution 30 m
  • CalGAP (1986)
  • Source UCSB CalGAP Project (http//www.biogeog.u
    csb.edu/projects/gap/gap_data_state.html)
  • Spatial resolution 4 ha MMU
  • CalVeg77 (1977) (http//frap.cdf.ca.gov/data/frapg
    isdata/select.asp)
  • Wieslander Vegetation Type Mapping Project
    (1920s) (http//vtm.berkeley.edu)

8
Measuring Geographic Distributions (e.g. How are
the points distributed?)
  • Mean
  • Median
  • Central feature

9
Spatial Statistics
10
Spatial Pattern Analysis
  • Pattern of point distribution
  • Nearest neighbor index
  • Ripleys K
  • Theissen polygons, or Voronoi diagrams
  • Semi-variogram
  • Quadrat analysis
  • Pattern of point and polygon values
  • Continuous data gradients and localized
    variability
  • Morans I
  • Getis-Ord General G
  • Kriging
  • Discrete/categorical data
  • Landscape pattern metrics
  • Join count

11
PATTERN OF POINT DISTRIBUTION Neighborhood
Operations
  • What is close to me?
  • Methods
  • Straight-line distance (Euclidean distance)
  • Spider diagram
  • Distance of cost over network
  • Cost over a surface
  • Buffers
  • Variable distance buffers
  • Filters
  • Local, Focal and Zonal functions
  • Distance to/from features
  • Theissen polygons, or Voronoi diagrams

12
PATTERN OF POINT DISTRIBUTION Nearest Neighbor
Index
  • Calculates the average distance between points
  • Significance is tested with Z-score
  • Types
  • Inter-centroid distance
  • Boundary-boundary distance

13
PATTERN OF POINT DISTRIBUTION Ripleys K Function
  • Counts the of features within defined distances
  • Measures spatial arrangement (clustered,
    uniform, random)
  • Uses multiple simulations to create a random
    distribution envelope
  • Detect the scale of those patterns, e.g. what is
    the cluster size?
  • Assumes
  • Stationary No trends in the data
  • Isotropy No directional detection (although it
    is possible to modify the K function to detect
    anisotropy.
  • Regular study area (rarely encountered)

14
PATTERN OF POINT DISTRIBUTION Ripleys K function
15
Spatial Autocorrelation
  • Spatial autocorrelation measures the level of
    interdependence between the variables, the nature
    and strength of the interdependence
  • Can be either positive or negative
  • Positive spatial autocorrelation has all similar
    values appearing together, while negative spatial
    autocorrelation has dissimilar values appearing
    in close association (less common)
  • Measured by
  • Semivariograms
  • Morans I
  • Gearys C

16
PATTERN OF POINT DISTRIBUTION Semivariograms
semivariance
sill
nugget
h
range
  • Range the average distance within which the
    variable remains spatial autocorrelated ? the
    extent of spatial trends, distance beyond which
    sampling is random
  • Sill the maximum variance of the sample data
  • Nugget measurement errors or smaller variations
    within the minimum sampling distance ? the noise
    in the data

17
PATTERN OF POINT DISTRIBUTION Semivariograms
18
PATTERN OF POINT DISTRIBUTION Semivariograms
19
PATTERN OF POINT POLYGON VALUES Morans I
  • Shows similarity of neighboring features
  • Provides a single statistics summarizing pattern
  • For continuous data
  • Spatial covariation/total variation
  • Ranges from 1 to 1
  • Positive positive spatial autocorrelation,
    negative represents negative autocorrelation. 0
    no spatial autocorrelation (random).

20
PATTERN OF POINT POLYGON VALUES Getis-Ord Gi
and General G
  • Hot-spot analysis, showing concentration of high
    or low values
  • Indicates whether high or low values are
    clustered
  • Uses a neighborhood based on a distance you
    specify
  • Applies a weight to those within the distance
    that have similar values

21
Other Software for Statistical Analysis
  • Fragstats
  • http//www.umass.edu/landeco/research/fragstats/fr
    agstats.html
  • ArcGIS Geostatistical Analyst
  • http//www.esri.com/geostatisticalanalyst/
  • GEODA
  • Great for categorical (and other!) pattern
    analysis
  • FREE https//www.geoda.uiuc.edu/
  • VARIOWIN
  • Great for semi-variograms
  • FREE http//www-sst.unil.ch/research/variowin/
  • R
  • FREE http//www.r-project.org/
  • S spatial statistics module
  • NOT FREE http//www.insightful.com/products/spati
    al/
  • SAS
  • NOT FREE http//www.sas.com/technologies/analytic
    s/statistics/

22
PATTERN OF POINT POLYGON VALUES Landscape
Pattern Metrics
  • Landscape Ecology uses pattern metrics to
    quantify structure
  • Size
  • Patch size
  • Shape
  • Elongated, circular, amount of edge
  • Spatial configuration
  • Measuring patterns in the mosaic (patch metrics)
  • Clustered, dispersed
  • Dominance, linkages, isolation, proximity…
  • Fragmentation, isolation, connectivity

23
ArcGrid enabled Fragstats
24
Landscape Metrics ONE metric per site
(landscape)
Whole landscape
25
Class Metrics ONE metric per class in the map
Each color represents separate class
26
Patch Metrics ONE metric per patch (landscape)
Each patch metric calculated for each patch
27
Problems with Pattern Metrics
  • There has been much scrutiny of these techniques,
    and criticism, including…
  • Metrics are highly redundant
  • Metrics are very sensitive to inputs and to scale
  • Conceptual flaws in landscape pattern analysis
  • Unwarranted relationships between pattern and
    process
  • Quantifying pattern without considering process
  • Ecological irrelevance of landscape indices
  • Two recent papers discuss these issues and more
  • Wu, J. 2004. Effects of changing scale on
    landscape pattern analysis scaling relations.
    Landscape Ecology 19 125-138.
  • Li, H., and J. Wu. 2004. Use and misuse of
    landscape metrics. Landscape Ecology 19 389-399.

28
Definitions
  • Drainage system
  • Area upon which water falls, and the network
    through which it travels to an outlet
  • Drainage basin
  • Area that drains water to a common outlet
  • This area is normally defined as the total area
    flowing to a given outlet, or pour point.
  • Other common terms for a drainage basin are
    watershed, basin, catchment, or contributing
    area.
  • Outlet, or pour point
  • Point at which water flows out of an area
  • Usually the lowest point along the boundary of
    the drainage basin
  • Drainage divide or watershed boundary
  • The boundary between two basins

29
Definitions
  • Network
  • Outlet
  • Stream channels
  • Junction, or node
  • Intersection of two stream channels
  • Interior links
  • Sections of a stream channel connecting two
    successive junctions, or a junction
  • Exterior links
  • Outermost branches of the tree, (i.e., they have
    no tributaries).

30
Hydrologic Analysis
31
Flow Direction
  • The output of this request is an integer Grid
    whose values range from 1 to 255. The values for
    each direction from the center are
  • For example, if the direction of steepest drop
    was to the left of the current processing cell,
    its flow direction would be coded as 16.

32
Flow Accumulation
  • Flow Accumulation creates a grid of accumulated
    flow to each cell, by accumulating the weight for
    all cells that flow into each downslope cell.
  • Hydrography is usually created with a threshold
    of accumulated cell values.

33
Hydrology Tools in ArcToolbox
  • Watersheds basins
  • Snap Pour Point
  • Stream to Feature simplify vs. non-simplify
  • Stream Order

34
Data for Hydrological GIS
  • Elevation
  • SF Bay Area Regional Database (BARD) 30m and some
    10m DEMs http//bard.usgs.gov
  • SF Bay NGA 2m DEM see GIIF
  • California 90m DEM see GIIF
  • National Elevation Dataset (NED) 30m DEM
    http//ned.usgs.gov
  • North America 1,000m DEM (ESRI) see GIIF
  • Global 1km GTOPO30 (USGS) http//edcdaac.usgs.go
    v/gtopo30/gtopo30.html
  • Stream gage data (daily and real-time)
  • USGS National Water Information Systems (NWIS)
  • Watersheds, water districts, rivers
  • Calif. Spatial Information Library (CaSIL)
    http//gis.ca.gov
  • U.S. National Hydrography Dataset (NHD)
    http//nhd.usgs.gov/

35
Elevation Data
36
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