Lesley Bross - Portland State University [email protected] August 1, 2014 Using multispectral imagery...
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Lesley Bross - Portland State University [email protected] August 1, 2014 Using multispectral imagery to monitor vegetation change following flow restoration
Lesley Bross - Portland State University [email protected] August
1, 2014 Using multispectral imagery to monitor vegetation change
following flow restoration to the Lower Owens River,
California
Slide 2
Research question(s) Can Landsat scenes be used to monitor
riparian vegetation change following flow restoration to the Lower
Owens River ? 1.Compare different change detection techniques
2.Calculate and analyze landscape pattern metrics 3.Compare results
from study plots with different vegetation communities Source: OVC
2008
Slide 3
Riparian zones Source: Ecosystem Sciences 2008B Interface
between terrestrial and aquatic ecosystems Diverse habitat =
relatively high species richness Provide important ecological
functions About 2% of original riparian land cover remains in
western United States (Jones et al. 2008)
Slide 4
Restoration efforts Source: Coffin 2013 River restoration
projects are expensive (time and money) Monitoring success with
ground surveys is also costly Is there an alternative?
Slide 5
Satellite multispectral imagery Ground-truth data has limited
spatial and temporal resolutions Landsat images cover a large areas
inexpensively Unique landscape patterns are revealed at larger
scale Regularly scheduled satellite images can monitor landscape
change Archived remotely sensed data provides views of
pre-restoration landscape
Slide 6
Owens River Watershed Source: Ecosystem Sciences 2008B
Slide 7
Lower Owens River Source: Risso 2007
Slide 8
Hydrologic history 1913: First Los Angeles aqueduct opens 1929:
Tinemaha Dam completed 1970: Second Los Angeles aqueduct opens
1991: LADWP and Inyo County approve Long Term Water Agreement; EIR
completed 1997: Memorandum of Understanding 2006: Base flow
restored to Lower Owens
Slide 9
2008: Seasonal habitat flow Source: OVC 2008
Slide 10
NDVI NDVI: Normalized Difference Vegetation Index represents
greenness: ((IR - R)/(IR + R)) * 100 + 100 Ratio minimizes
multiplicative noise from topographic factors (shadows, aspect)
when comparing images Source: ESRI 2010
Slide 11
Landscape pattern metrics Tool to explain effects of landscape
patterns on biological processes and vice versa
Patch-corridor-matrix is a popular model for quantifying landscape
change Source: Barnes 2000
Slide 12
Fragmentation and connectivity Fragmentation: breaking up of
land cover type into smaller, isolated plots Connectivity: spatial
continuity of land cover type across a landscape; How easy is it to
move among patches? Source: Fahrig 2003
Slide 13
Select metrics appropriate for scale and research question
Freeman et al. recommend: percent of landscape occupied (per class)
number of patches mean patch size patch density edge density How
did land cover patterns change between 2002 and 2009? Which metrics
to calculate? Source: ESRI 2010
Slide 14
Plot 2: Vegetation maps Source: Ecosystem Sciences 2002, 2010
Ground surveys conducted in 2001, 2002, and 2009 Vegetation
complexes reclassified to NLCD classes
Acquire Landsat images for summers of 2002 and 2009 Source data
for 1.Post-classification change detection 2.Image differencing
(NDVI) Landsat multispectral imagery Source: USGS 2014
Slide 17
#1: Post-classification change detection 1.Unsupervised
classification => land cover map (5 NLCD classes) 2.Perform
accuracy assessment using ground truth polygons 3.Accuracy =
important! Every error in both classifications = error in final
results 4.Collapse classes if needed 5.Analyze from-to maps
(percent occupied)
Slide 18
Spatial pattern analysis 2002 and 2009 land cover maps = input
for pattern analysis Class-level metrics for: forest, wetlands, and
grasslands Calculate: number of patches mean patch size patch
density edge density Plot mean patch size against density
(connectivity) Source: Freeman et al. 2003
Slide 19
#2: NDVI image differencing 1.Preprocessing: atmospheric
correction? 2.Calculate NDVI for both dates 3.Subtract 2009 NDVI
from 2002 NDVI 4.Difference values indicate: a)Direction of change
(bare earth -> grasses) b)Magnitude of change 5.Set threshold
values for change (difficult) Source: ESRI 2010 2002 2009
Slide 20
Spatial pattern analysis (redux) Determine NDVI threshold value
indicating green vegetation Use value to create data layers with
vegetation/no- vegetation parcels 2002 and 2009 data layers = input
for pattern analysis Calculate: number of patches mean patch size
patch density edge density Plot mean patch size against density
(connectivity)
Slide 21
Anticipated outcomes 1.Evaluate two common change detection
methods and report their benefits and limitations 2.Assess the
usability of Landsat-derived vegetation maps for riparian (narrow)
landscapes 3.Demonstrate an economical, repeatable process that can
be used to monitor vegetation change following river rehabilitation
efforts Source: Ecosystem Sciences 2008A
Slide 22
Timeline Fall 2014: Literature review and technical tasks
Winter 2015: Write-up results Spring 2015: Thesis presentation
Slide 23
References ArcGIS 10. 2010. ArcGIS 10 Help. Redlands, CA:
Environmental Systems Research Institute (ESRI). Barnes, T. 2000.
Landscape ecology and ecosystems management. Lexington, KY:
University of Kentucky College of Agriculture. Available at
http://www2.ca.uky.edu/agc/pubs/for/for76/for76.htm (last accessed
10 July 2014). Coffin, B. 2013. Hemlock Dam removalClearing a path
for steelhead recovery in Trout Creek. Vancouver, WA: Salmon
Recovery Conference. Available at:
http://www.rco.wa.gov/documents/SalmonConference/presentations/TuesdayPMCoffin.pdf
(last accessed 13 September 2013). Danskin, W. 1998. Evaluation of
the hydrologic system and selected water-management alternatives in
the Owens Valley, California. United States Geological Survey
(USGS), Water-supply Paper 2370:1-175. Ecosystem Sciences. 2002.
Lower Owens River Project Baseline polygons. Prepared for the site
scale mapping component of the LORP Monitoring and Adaptive
Management program. (Received from Timothy Maguire on April 21,
2014). Ecosystem Sciences. 2008A. Lower Owens River project 2008
annual monitoring draft report. Prepared for Los Angeles Department
of Water and Power and Inyo County Water Department. Available at
http://www.inyowater.org/projects/lorp/ (last accessed 10 July
2014). Ecosystem Sciences. 2008B. Lower Owens River Project
Monitoring, Adaptive Management and Reporting Plan. Prepared for
Los Angeles Department of Water and Power and Inyo County Water
Department. Available at http://www.inyowater.org/projects/lorp/
(last accessed 12 June 2014).
Slide 24
Ecosystem Sciences. 2010. Lower Owens River Project 2010
polygons. Prepared for the site scale mapping component of the LORP
Monitoring and Adaptive Management program. (Received from Timothy
Maguire on April 21, 2014). Fahrig, L. 2003. Effects of Habitat
Fragmentation on Biodiversity. Annual Review of Ecology, Evolution,
and Systematics 34(2003): 487-515. Freeman, R., E. Stanley, and M.
Turner. 2003. Analysis and conservation implications of landscape
change in the Wisconsin River floodplain, USA. Ecological
Applications 13(2): 416-31. Jones, K., C. Edmonds, E. Slonecker, J.
Wickham, A. Neale, T. Wade, K. Riiters, and W. Kepner. 2008.
Detecting changes in riparian habitat conditions based on patterns
of greenness change: A case study from the Upper San Pedro River
Basin, USA. Ecological Indicators 8(1): 89-99. Naiman, R. and H.
Decamps. 1997. The ecology of interfaces: riparian zones. Annual
Review of Ecology & Systematics 1997(28):621-58. The Owens
Valley Committee (OVC). 2008. Lower Owens River Project. Bishop,
CA: OVC. Available at
http://www.ovcweb.org/issues/lorp%20overview.html (last accessed 10
July 2014). Risso, D. 2007. Floodplain vegetation following over 80
years of intensive land use and de-watering: Lower Owens River,
California. Masters Thesis. Department of Fisheries and Wildlife,
Oregon State University. Turner, M., Gardner, R., and R. ONeill.
2001. Landscape ecology in theory and practice pattern and process.
New York: Springer-Verlag. United States Geological Service (USGS).
2014. EarthExplorer. Washington D.C.: USGS. Available at
http://earthexplorer.usgs.gov/ (last accessed 24 January 2014).
References