Year of Award
2012
Document Type
Thesis
Degree Type
Master of Science (MS)
Degree Name
Forestry
Department or School/College
College of Forestry and Conservation
Committee Chair
Steven Running
Commitee Members
Alexander "Sandy" Ross, Anna Klene
Keywords
indigenous knowledge, Landsat, minnesota, wetlands, wild rice, zizania palustris
Abstract
Landsat-7 ETM+ (SLC-off) multispectral satellite imagery was tested to identify and delineate natural stands of wild rice (Zizania palustris L.) from other aquatic vegetation growing on area lakes of the Leech Lake Native American reservation in northern Minnesota. Leech Lake is located within the Mississippi River Headwaters drainage ecosystem and contains some of the largest natural stands of wild rice in the country. Local indigenous knowledge; in this case, the knowledge of Ojibwe tribal elders who have traditionally harvested wild rice by canoe for centuries, was utilized to build training data polygons for a supervised classification. By testing several supervised classification algorithms, it was hypothesized that wild rice could be delineated from other aquatic vegetation, but the coarse (30 m X 30 m) spatial resolution of Landat-7 ETM+ multispectral imagery (bands 1-5) would be a limiting factor. Masking upland areas using a 5-category ISODATA Boolean mask improved the classification results of the aquatic emergent vegetation. Maximum likelihood classification yielded a 79.03% accuracy (kappa = 0.6747) and a minimum distance to means classification yielded a 51.61% accuracy (kappa = 0.2092). It was also discovered that by adding band 7 to the stack, the accuracy of the maximum likelihood classifier dropped to 43.55% accuracy (kappa = 0.1891); therefore, band 7 was omitted from the study. The use of local indigenous knowledge, which includes personal observations and recollection of past harvest years, in conjunction with satellite remote sensing data demonstrated a more precise methodology for identifying culturally important resources on tribal lands. It is recommended that higher spatial resolution imagery be used in conjunction with local indigenous knowledge to identify and delineate species-specific landcover categories such as wild rice. This unique methodology has great potential in many remote regions of the world where indigenous peoples still subsist from the land.
Recommended Citation
Price, Michael Wassegijig, "Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data" (2012). Graduate Student Theses, Dissertations, & Professional Papers. 910.
https://scholarworks.umt.edu/etd/910
© Copyright 2012 Michael Wassegijig Price