Hi-Res Landcover

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Hi-Res Hi-Res Landcover Landcover Pete Kollasch, Iowa

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Hi-Res Landcover. Pete Kollasch, Iowa DNR. You are here. It’s about resolution. HRLC 1m. It’s about resolution. 2002 15m. It’s about resolution. 2009 2m. It’s about resolution. 2002 15m. What is it?. Statewide Land Cover file 1 meter spatial resolution - PowerPoint PPT Presentation

Transcript of Hi-Res Landcover

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Hi-Res Hi-Res LandcoverLandcover

Pete Kollasch, Iowa DNR

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You are here

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It’s about It’s about resolutionresolution

HRLC 1m

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It’s about It’s about resolutionresolution

2002 15m

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It’s about It’s about resolutionresolution

2009 2m

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It’s about It’s about resolutionresolution

2002 15m

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What is it?What is it?

• Statewide Land Cover file

• 1 meter spatial resolution– Compare to previous 15m 1986, 1990, 2002

• Derived from aerial imagery and lidar data– Previous all derived from Landsat imagery

• Interpreted to Summer 2009 NAIP

• County files ~ 50% complete now– 100% complete by end of 2013

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NeedNeed

• 2002 – most recent landcover product– More current data desired

• In May 2003 – Landsat 7 partial failure– With only Landsat 5: difficult to obtain

sufficient satellite imagery coverage

• Interest in higher resolution product

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OpportunityOpportunity

• Annual NAIP imagery available– From 2004 through 2011

• 4 band spring leaf-off imagery available– 2007 Northwest by Sanborn– 2009 West & 2010 East by ASI

• Lidar elevation data becoming available

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Criteria for ProcessCriteria for Process

• Reliable enough to produce compatible products from a wide range of input quality

• That can be completed in a finite period

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IssuesIssues

• Aerial Photography has high spectral variability– Collection date (esp. NAIP)– Multiple cameras / collections– Internal variability – hotspots, etc.– Suggests the use of “flattening” technologies

• Need sufficient spectral content

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TechnologiesTechnologies

• Multitemporal• Lidar Normalized Elevation• Common Land Units• Segmentation• Knowledge-based classification• Classification & Regression Tree• •

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TechnologiesTechnologies

• Multitemporal • Lidar Normalized Elevation • Common Land Units X• Segmentation X• Knowledge-based classification X• Classification & Regression Tree X• Independent Component Analysis • Classical Unsupervised

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HRLC HistoryHRLC History

• Initial research began in 2002– Initial results were not very successful

• Meetings: DNR, UI, ISU, UNI late 2008

• Procedure design 2009

• Began receiving enough data in late 2009

• 2010 to present– Preprocessing, Interpretation, Postprocessing– Final results began emerging early 2012

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InputsInputs

• Multitemporal Aerial Imagery– 2007/2009/2010 Four band spring imagery– 2009 NAIP imagery– 2008 NAIP imagery

• LiDAR normalized elevation layer– First return minus Bare earth

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InputsInputs

• Multitemporal Aerial Imagery– 2007/2009/2010 Four band spring imagery– 2009 NAIP imagery– 2008 NAIP imagery

• LiDAR normalized elevation layer– First return minus Bare earth

• What issues do they solve?

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PreprocessingPreprocessing

• Aerial Imagery Stack– 10 bands (4 + 3 + 3)– Areas of consistent spectral character– ICA (primary flattening technology)

• Add lidar normalized elevation band

• Unsupervised / Supervised Classification– 250 clusters

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InterpretationInterpretation

• ERDAS Class Grouping Tool

• Initially 2 tier– Grouping / Checking

• Later 3 tier– Grouping / Checking / Final Check– Final check by a single interpreter for

consistency

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PostprocessingPostprocessing

• Fuzzy Recode (another flattener)

• Erode edges of tiles, sequence

• Mosaic tiles together

• Lidar normalized elevation filtering

• Shadow conversion around structures

• Eliminate objects < 10 pixels

• Reconstruct entire mosaic

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CountiesCounties

• Clip county to rectangle with 100m buffer– If there be holes, wait for enough data to fill

• Raster edit steps– General rule: if not possible, change it– Affects only a small percent of space, but

makes a big difference in the look– 2 sets of eyes

• Prep for NRGIS library– (4 bit, color table, names, round to .5 m)

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HRLC Data AccessHRLC Data Access

• NRGIS library, by FTP– By county: HRLC_2009_xx.img– http://www.igsb.uiowa.edu/nrgislibx/

• Map Service available

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ThanksThanks

• Thejashwini Ramarao• Matt Swanson• Kathryne Clark• Matt Gosse• Sarah Porter• Cody Hackney • ISU, UI, UNI remote

sensing personnel

• Jim Giglierano• Chris Ensminger• Daryl Howell• Casey Kohrt• Chris Kahle• and many more …

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Questions?Questions?

• Pete Kollasch– [email protected]– 319-335-1578