Josh Knopik, WRS Jessica Campbell, MGIS FR 5262

Outline Background and Objectives Data and Materials Methods Results Discussion

Background and Objectives USFWS has been monitoring wild rice and other aquatic vegetative species at Rice Lake NWR since Wild rice has a cultural significance to local Native American tribes for harvesting. Previous studies have calculated area of wild rice present on lake.

Background and Objectives (cont.) Objective was to conduct an assessment of wild rice present on lake in Previous assessment was done in Goal was to classify into three classes; mostly wild rice, open water, and mostly other vegetative species.

Data and Materials Aerial photographs were taken in the summer of 2010, orthorectified, and mosaicked to form a “complete” picture of the lake. Photos were captured in CIR film with three bands; Red/NIR nm, Green/Red nm, and Blue/Green nm and a 0.1m pixel resolution. In late August 2010, 76 reference plots were collected and in early October, another 24 were gathered as well.

Data and Materials (cont.) Used ERDAS 2010 and ArcGIS for classification. Took over 200 photos and a half dozen videos along with reference data plots. Report from study in 2004 to compare methods and remain consistent with previous practices.

Methods Unsupervised Classification – RGB Clustering Layer Stack

Methods (cont.) Unsupervised (cont.) – Image Segmentation Convert Feature to Polygon – In ArcGIS Zonal Attributes

Methods (cont.) Assessed Means from Segmented Feature Classes – Compared each stacked layer and verify with training data collected Supervised Classification – Wrote SQL queries to pull polygon segments that satisfied mean ranges for a given class.

Methods (cont.) Supervised Classification (cont.) – Manually reclassified polygons based off query results, training area values, and various elements of image interpretation. – Performed this for all 24 sections of the lake and then merged features based on class.

Results 2010ClassArea %AcresArea (m 2 ) Mostly Rice 32.91,1954,836,047.8 Mostly Water ,154,189.3 Mostly Other 45.61,6556,696, Analysis 1 Mostly Wild Rice 2 Mostly Water 3 Mostly Other Projected in UTM Zone 15N

Results (cont.)

Discussion Challenges – Image Segmentation – Species with similar spectral signatures Accuracy Assessment – Unable to conduct at this time; no ground data – Could conduct “expert interpreter” assessment Continuing Project… – Short Term: Texture tool in ERDAS 2010 – Long Term: LiDAR?

Questions?