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Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using Gis

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Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using Gis FINAL REPORT: DETECTION, PREDICTION, IMPACT, AND MANAGEMENT OF INVASIVE PLANTS USING GIS Keith T. Weber, editor GIS Director Idaho State University GIS Training and Research Center Pocatello, Idaho 83209-8130 FINAL REPORT: DETECTION, PREDICTION, IMPACT, AND MANAGEMENT OF INVASIVE PLANTS USING GIS Keith T. Weber, Editor Contributing Investigators Keith T. Weber, Principal Investigator ([email protected]), Idaho State University, GIS Training and Research Center, Campus Box 8130, Pocatello, ID 83209-8130. Nancy F. Glenn, Co-Principal Investigator ([email protected]), Idaho State University, Department of Geosciences, Campus Box 8072, Pocatello, ID 83209-8072. Matthew Germino, Co-Principal Investigator ([email protected]), Idaho State University, Department of Biological Sciences, Campus Box 8007, Pocatello, ID 83209- 8007. Project web-site: http://giscenter.isu.edu/research/techpg/nasa_weeds/template.htm All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means without the prior permission of the editor. ACKNOWLEDGEMENTS This study was made possible by a grant from the National Aeronautics and Space Administration Goddard Space Flight Center. ISU would also like to acknowledge the Idaho Delegation for their assistance in obtaining this grant. Recommended citation style: Streutker, D. R., and N. F. Glenn. 2006. LiDAR Measurement of Sagebrush Steppe Vegetation Heights. Pages 33-50 in K. T. Weber (Ed), Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using GIS. 196 pp. Table of Contents Chapter Title Page Executive Summary 1 Rangeland Health Modeling with Quickbird 1 3 Imagery Mapping Sagebrush Distribution Using Fusion of 2 17 Hyperspectral and LiDAR Classifications LiDAR Measurement of Sagebrush Steppe 3 33 Vegetation Heights Interactive Effects of Fire, Grazing, and 4 Precipitation on Long-Term Variability in 51 Remotely Sensed Indices of Vegetation Challenges of Integrating Geospatial Technologies 5 65 into Rangeland Research and Management 6 Modeling Cheatgrass using Quickbird Imagery 77 Range Vegetation Assessment in the Big Desert, 7 85 Upper Snake River Plain, Idaho Ecological Syndromes of Invasion in Semiarid 8 Rangelands and their Implications for Land 91 Management and Restoration. Spatial and Temporal Patterns of Sagebrush 9 (Artemesia tridentata ssp.vaseyana) Establishment 99 Following Fire Measuring Early Vegetation Changes after Fire in 10 Mountain Big Sagebrush (Artemesia tridentate 111 Nutt. ssp. vaseyana [Rydb] Beetle) Rangelands Correlation of Neighborhood Relationships, Carbon 11 Assimilation, and Water Status of Sagebrush 131 Seedlings Establishing After Fire Analysis of LiDAR-Derived Topographic 12 Information for Characterizing and Differentiating 141 Landslide Morphology and Activity Advantages in Water Relations Contribute to 13 Greater Photosynthesis in Centaurea maculosa 161 Compared with Established Grasses 14 Comparing GPS Receivers: A Field Study 177 A Comparison Between Multi-Spectral and 15 Hyperspectral Platforms for Early Detection of 185 Leafy Spurge in Southeastern Idaho Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using GIS DETECTION, PREDICTION, IMPACT, AND MANAGEMENT OF INVASIVE PLANTS USING GIS Executive Summary Significant Findings and Achievements • While high spatial resolution satellite imagery seems to offer numerous advantages to the scientific community to assess and monitor rangeland ecosystems, they are currently of limited application due to cost and, more importantly, unreliable accuracy of patchy targets. This is a function of geo-registration error (RMS~5.0m) that routinely exceeds the absolute spatial resolution of the imagery (2.4m) (chapters 1, 5, and 6). • High spatial resolution satellite imagery has limited applicability for large study areas because the method in which these data are acquired is not systematic, but rather scheduled. A large study area may be imaged over a period of several weeks. While the imagery can be atmospherically corrected to achieve a seamless and “color- balanced” product, this temporal resolution is not satisfactory for rangeland applications where the phenological state of plants changes fairly rapidly throughout the growing season. • The accuracy of invasive weed classifications is strongly influenced by co-registration between imagery and field training sites. Since most training sites are acquired using GPS, the accuracy and precision of GPS receivers is extremely important (chapters 5 and 14). • Reliable classification of rangeland ecosystems is a function of minimum target cover. It appears that targets need to exist at a percent cover of nearly 1/3rd (33%) within each pixel to assure reliable classification results (>70% users accuracy). • We developed LiDAR statistical tools for detection and characterization of rangeland vegetation (chapter 3). LiDAR routinely underestimated the height of vegetation and it appears that a minimum mass of vegetation (i.e., the interior of the shrub rather than the surface canopy) was required to return the LiDAR signal. This known and consistent underestimation allows LiDAR data to be applied to numerous rangeland ecosystems studies. • We developed LiDAR/hyperspectral data fusion methods for rangeland vegetation (chapter 2). This methodology increased overall classification accuracy (from 74% to 89%) and provided vegetation structure information previously unavailable with standard image classification techniques. • We are applying the LiDAR methodologies pioneered by this study to areas with wind erosion/deposition. Two proposals have been submitted to continue this research. • The effect of livestock grazing on vegetation composition in rangeland ecosystems is dependent upon stocking level and spatial distribution. As a result, we have begun investigating the temporal effect of livestock grazing animals on sagebrush-steppe rangelands. 1 Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using GIS • Vegetation structure and cover becomes variable in space and time after fire, particularly when sites were grazed extensively before the fire. We predict that where and when vegetation indices are low during the growing season, there must be resources available to exotic plants, making invasions possible (chapters 4 and 9). • Soil water becomes more available after fire --at depth-- due primarily to the loss of sagebrush (chapter 10). • Spotted knapweed, which appears representative of Eurasian forbs, has major growth advantages over other plants. The extra advantages arise from its ability to tap into deep soil water that is available when sagebrush or other deep-rooted species are not present (e.g., following fire). This growth advantage is linked to superior photosynthesis and morphological features of knapweed (and probably most exotic forbs of rangelands) conferring greater efficiency in its use of soil resources. Soil resources are a key driver of invasions (chapter 13). • We addressed how invasive plants persist in the long term and felt it was necessary to first investigate factors affecting reestablishment of the community existing before fire. Herbs come back immediately (chapter 10), but sagebrush is slow to reestablish. We found recovery of mountain sagebrush is negatively affected by neighboring herbs, particularly forbs (chapters 8 and 9). The effect appears linked more to competition over nitrogen (or similar elements) rather than water (WNAN). As rangelands become enriched with forbs as a result of invasive plants like knapweed and other Eurasian forbs, we expect sagebrush recovery after fire to be more sluggish than it currently is. • One student completed his Graduate Certificate in Geotechnologies (Luke Sander) through this research, while two others completed their Master degree (Ryan Baum and Katie DeCristina). Three students were partially funded by this study which ultimately will result in completion of doctoral degrees (Bhushan Gokhale, Judson Hill, and Erik Jackson) (degrees are expected to be conferred in August 2006). • Public outreach events associated with this study were very successful. Over 200 people (ranchers, range scientists, range managers, and geospatial scientists) were exposed to our research at the annual Geo-spatial and Range Sciences Conference. Several have become very involved and have used products produced through our research in the ranch/range planning. 2 Final Report: Detection, Prediction, Impact, and Management of Invasive Plants Using GIS Rangeland Health Modeling with Quickbird Imagery Bhushan Gokhale. Idaho State University, GIS Training and Research Center, Campus Box 8130, Pocatello, Idaho 83209-8130. ([email protected]) Keith T. Weber. Idaho State University, GIS Training and Research Center, Campus Box 8130, Pocatello, Idaho 83209-8130. ([email protected]) ABSTRACT Rangeland health is very important for ranchers, farmers and land management agencies. It is also important to identify different rangeland health parameters and evaluate their impact on rangeland health. This study obtained various data describing rangeland health conditions in southeastern Idaho and prepared a rangeland health model using Quickbird multispectral satellite imagery. Five elements were chosen to evaluate rangeland health: presence of cheatgrass (Bromus tectorum), bare ground exposure, litter, percent shrub cover, and percent grass cover. A field survey collected information (percentage, dimensions
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