Detecting and Mapping Four Invasive Species Along The Floodplain of North Platte River, Nebraska

Abstract Geospatial technologies are increasingly important tools used to assess the spatial distributions and predict the spread of invasive species. The objective of our research was to quantify and map four dominant invasive plant species, including saltcedar, Russian olive, Canada thistle, and musk thistle, along the flood plain of the North Platte River corridor within a 1-mile (1.6-km) buffer. Using the Airborne Imaging Spectroradiometer for Applications (AISA) hyperspectral imager (from visible to near infrared), we evaluated an image processing technique known as spectral angle mapping for mapping the invasive species distribution. A minimum noise fraction algorithm was used to remove the inherent noise and redundancy within the dataset during the classification. The classification algorithm applied on the AISA image revealed five categories of invasive species distribution including (1) saltcedar; (2) Russian olive; and a mix of (3) Canada and musk thistle, (4) Canada/musk thistle and reed canary grass, or (5) Canada/musk thistle, saltcedar, and reed canary grass. Validation procedures confirmed an overall map accuracy of 74%. Saltcedar and Russian olive classes showed producer and user accuracies of greater than 90%, whereas the mixed categories revealed accuracy values of between 35 and 74%. The immediate benefit of this research has been to provide information on the spatial distribution of invasive species to land managers for implementation of management programs. In addition, these data can be used to establish a baseline of the species distributions for future monitoring and control efforts. Nomenclature: Canada thistle, Cirsium arvense L. Scop.; musk thistle, Carduus nutans L.; reed canary grass, Phalaris arundinacea L.; Russian olive, Elaeagnus angustifolia L.; saltcedar, Tamarix sp. Lour

[1]  Lori Lach,et al.  ENVIRONMENTAL AND ECONOMIC COSTS ASSOCIATED WITH NON-INDIGENOUS SPECIES IN THE UNITED STATES , 1999 .

[2]  S. Ustin,et al.  Mapping nonnative plants using hyperspectral imagery , 2003 .

[3]  R. Congalton.  A Quantitative Method to Test for Consistency and Correctness in Photointerpretation , 1983 .

[4]  James Woodward,et al.  Biological invasions as global environmental change , 1996 .

[5]  Jacob T. Mundt,et al.  Hyperspectral data processing for repeat detection of small infestations of leafy spurge , 2005 .

[6]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[7]  R. Mccoy,et al.  Mapping Desert Shrub Rangeland Using Spectral Unmixing and Modeling Spectral Mixtures with TM Data , 1997 .

[8]  J. Townshend,et al.  African Land-Cover Classification Using Satellite Data , 1985, Science.

[9]  E. Zavaleta,et al.  The Economic Value of Controlling an Invasive Shrub , 2000 .

[10]  Amy E. Parker Williams,et al.  Accuracy assessment for detection of leafy spurge with hyperspectral imagery , 2004 .

[11]  K. Makisara,et al.  A system for geometric and radiometric correction of airborne imaging spectrometer data , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[12]  Joseph W. Boardman,et al.  Considerations in collecting, processing, and analysing high spatial resolution hyperspectral data for environmental investigations , 2002, J. Geogr. Syst..

[13]  J. Woolley.  Reflectance and transmittance of light by leaves. , 1971, Plant physiology.

[14]  Alan R. Johnson,et al.  A Framework for Spatial Risk Assessments: Potential Impacts of Nonindigenous Invasive Species on Native Species , 2006 .

[15]  M. Coleman,et al.  COLOR FOR SHRUBS , 1974 .

[16]  James R. Anderson,et al.  A land use and land cover classification system for use with remote sensor data , 1976 .

[17]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[18]  D. Roberts,et al.  Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments , 2001 .

[19]  Amy E. Parker Williams,et al.  Estimation of leafy spurge cover from hyperspectral imagery using mixture tuned matched filtering , 2002 .

[20]  D. Pimentel,et al.  Environmental and Economic Costs of Nonindigenous Species in the United States , 2000 .

[21]  Kevin P. Price,et al.  Satellite Remote Sensing to Predict Potential Distribution of Dyers Woad (Isatis tinctoria) , 1991, Weed Technology.

[22]  M. Cochrane.  Using vegetation reflectance variability for species level classification of hyperspectral data , 2000 .

[23]  Paul M. Treitz,et al.  Application of detailed ground information to vegetation mapping with high spatial resolution digital imagery , 1992 .

[24]  M. Ashton,et al.  Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests , 2004 .

[25]  Lawrence W. Lass,et al.  Detection of Yellow Starthistle (Centaurea solstitialis) and Common St. Johnswort (Hypericum perforatum) with Multispectral Digital Imagery , 1996, Weed Technology.

[26]  Rick L. Lawrence,et al.  FIFTEEN YEARS OF REVEGETATION OF MOUNT ST. HELENS: A LANDSCAPE-SCALE ANALYSIS , 2000 .

[27]  James H. Everitt,et al.  Using Spatial Information Technologies to Map Chinese Tamarisk (Tamarix chinensis) Infestations , 1996, Weed Science.

[28]  J. H. Everitt,et al.  Use of spatial information technologies for noxious plant detection and distribution on rangelands , 1996 .

[29]  R. Congalton,et al.  Accuracy assessment: a user's perspective , 1986 .

[30]  Gail P. Anderson,et al.  Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data , 2002, Applied Imagery Pattern Recognition Workshop, 2002. Proceedings..

[31]  B. Rundquist,et al.  Flat Water: A History of Nebraska and Its Water , 1993 .

[32]  Lawrence W. Lass,et al.  Detection of Yellow Hawkweed (Hieracium pratense) with High Resolution Multispectral Digital Imagery , 1995, Weed Technology.

[33]  J. R. Jensen.  Remote Sensing of the Environment: An Earth Resource Perspective , 2000 .

[34]  C. Allen,et al.  Red Imported Fire Ant Impacts on Wildlife: A Decade of Research , 2004 .

[35]  Fred A. Kruse,et al.  The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data , 1993 .

[36]  D. Richardson,et al.  Effects of Invasive Alien Plants on Fire Regimes , 2004 .

[37]  Nancy F. Glenn,et al.  A review of remote sensing of invasive weeds and example of the early detection of spotted knapweed (Centaurea maculosa) and babysbreath (Gypsophila paniculata) with a hyperspectral sensor , 2005, Weed Science.

[38]  Sunil Narumalani,et al.  A Comparative Evaluation of ISODATA and Spectral Angle Mapping for the Detection of Saltcedar Using Airborne Hyperspectral Imagery , 2006 .

[39]  Fred A. Kruse,et al.  The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data , 1993 .

[40]  K. Makisara,et al.  Geometric correction of airborne imaging spectrometer data , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[41]  James H. Everitt,et al.  Mapping leafy spurge (euphorbia esula) infestations using aerial photography and geographic information systems , 1996 .

[42]  E. Vermote,et al.  Second Simulation Of The Satellite Signal In The Solar Spectrum - 6s Code , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[43]  Lawrence W. Lass,et al.  The Effect of Phenological Stage on Detectability of Yellow Hawkweed (Hieracium pratense) and Oxeye Daisy (Chrysanthemum leucanthemum) with Remote Multispectral Digital Imagery , 1997 .

[44]  Jacob T. Mundt,et al.  Discrimination of hoary cress and determination of its detection limits via hyperspectral image processing and accuracy assessment techniques , 2005 .