Hi-Res Landcover Pete Kollasch, Iowa DNR

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It’s about resolution HRLC 1m

It’s about resolution m

It’s about resolution m

It’s about resolution m

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

Need 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

Opportunity Annual NAIP imagery available –From 2004 through band spring leaf-off imagery available –2007 Northwest by Sanborn –2009 West & 2010 East by ASI Lidar elevation data becoming available

Criteria for Process Reliable enough to produce compatible products from a wide range of input quality That can be completed in a finite period

Issues 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

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

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

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

Inputs 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

Inputs 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?

Preprocessing Aerial Imagery Stack –10 bands ( ) –Areas of consistent spectral character –ICA (primary flattening technology) Add lidar normalized elevation band Unsupervised / Supervised Classification –250 clusters

Interpretation ERDAS Class Grouping Tool Initially 2 tier –Grouping / Checking Later 3 tier –Grouping / Checking / Final Check –Final check by a single interpreter for consistency

Postprocessing 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

Counties 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)

HRLC Data Access NRGIS library, by FTP –By county: HRLC_2009_xx.img – Map Service available

Thanks 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 …

Questions? Pete Kollasch –