A landscape classification approach for watersheds of the Pacific Northwest: is aquaticecosubregiona - PowerPoint PPT Presentation

1 / 21
About This Presentation
Title:

A landscape classification approach for watersheds of the Pacific Northwest: is aquaticecosubregiona

Description:

A landscape classification approach for watersheds of the Pacific Northwest: ... Zonal Statistics & Reclassify Raster. Raster Calculator or Command Line: ... – PowerPoint PPT presentation

Number of Views:125
Avg rating:3.0/5.0
Slides: 22
Provided by: rentmee
Category:

less

Transcript and Presenter's Notes

Title: A landscape classification approach for watersheds of the Pacific Northwest: is aquaticecosubregiona


1
A landscape classification approach for
watersheds of the Pacific Northwest is
aquaticecosubregionalizationeven a word?
  • Chris Jordan, Steve Rentmeester, Carol Volk, Mimi
    DIorio, George Pess, Tim Beechie
  • NOAA-NWFSC, Seattle

2
What are we doing, and why?
  • Classify the aquatic-landscape of the Pacific
    Northwest based on relevant broad-scale
    characteristics
  • Major determinants of watershed processes
  • Immutable geomorphic characteristics
  • Human impact
  • Data analysis support
  • Environmental variance partitioning
  • Evaluation tool for site selection

3
A Made-up Example of What We Want the Output to
Look Like
4
A couple of examples of something similar, but
not quite the same
  • Hessburg et al. 2000. Ecological subregions of
    the ICRB based on PVG, Temp-precip, solar
    radiation, elevation.
  • Omernik et al. 1999, US EPA Level III IV
    Ecoregions based on terrestrial vegetation
    assemblages.

5
(No Transcript)
6
(No Transcript)
7
What are we doing, and why?
  • Classify the aquatic-landscape of the Pacific
    Northwest based on relevant broad-scale
    characteristics
  • Data analysis support
  • Evaluation tool for site selection
  • Assess representativeness of current monitoring
    and restoration efforts.
  • Locate additional monitoring and restoration
    projects.

8
(No Transcript)
9
How are we doing this?
  • Taking commonly available spatial data w/
    consistent coverage across study area.
  • Generating functional data layers from above.
  • Attributing 6th field watersheds with a single
    value for each input data layer.
  • Grouping watersheds into clusters of like, or
    classes.

10
Input Data
Climate
  • Annual Precipitation
  • Month of Max Precipitation
  • Growing Degree Day

Topography
  • Median Elevation
  • Median Hill Slope

Geology
  • Stream sediment production
  • Water chemistry

Channel Network
  • Density (by gradient)
  • Complexity (valley width)
  • Stream power
  • Tributary junctions
  • Watershed shape

11
How are we doing this?
  • Taking commonly available spatial data w/
    consistent coverage across study area.
  • Generating functional data layers from above.
  • Attributing 6th field watersheds with a single
    value for each input data layer.
  • Grouping watersheds into clusters of like, or
    classes.

12
(No Transcript)
13
(No Transcript)
14
How are we doing this?
  • Taking commonly available spatial data w/
    consistent coverage across study area.
  • Generating functional data layers from above.
  • Attributing 6th field watersheds with a single
    value for each input data layer.
  • Grouping watersheds into clusters of like, or
    classes.

15
Hydrologic Unit Code
6th field HUCs Sub-watersheds (10,000-40,000
ac)
16
Five data layers 6th field watersheds with a
single values for each input characteristic.
17
Five data layers 6th field watersheds with a
single values for each input characteristic.
18
How are we doing this?
  • Taking commonly available spatial data w/
    consistent coverage across study area.
  • Generating functional data layers from above.
  • Attributing 6th field watersheds with a single
    value for each input data layer.
  • Grouping watersheds into clusters of like, or
    classes.

19
Processing Step
Processing Tools
Spatial Analyst Zonal Statistics Reclassify
Raster
Compile categorical data for 6th order HUCS and
build as attributes into a GIS shapefile Convert
features from vectors to 200m raster
grids Stack separate raster integer grids into
one multi-band raster file Apply ISOCLUSTER and
Maximum Likelihood Classification algorithms to
separate classes based on pixel
spectra Evaluate spatial patterns using
Fragstats
Spatial Analyst Convert Features to Raster
Raster Calculator or Command Line Make Grid
Stack or Composite Bands Tool
Spatial Analyst Tools Command Line ISOCLUSTER
Fragstats Patch Class and Landscape Metrics
20
(No Transcript)
21
Where are we and next steps
  • Need to resolve 200m pixel v. 6th HUC grain
  • Need to clean up a few more data layers
  • Erosion potential v. Slope x Area
  • T, R, S
  • Month of max ppt v. hydro regime
  • Need to resolve classification tool
  • ISODATA v. MCLUST
  • Need to make maps and get feedback
  • Need to move on to anthropogenic layers
Write a Comment
User Comments (0)
About PowerShow.com