Airborne Hyperspectral Research & Development for Invasive Species Detection and MappingKenneth McGwire1, Timothy Minor1, Bradley Schultz2, and Christopher Kratt1

1Desert Research Institute, Reno, Nevada, 89512 USA2University of Nevada Cooperative Extension, Winnemucca, NV 89445 USA

Field Data Collection

Status

Hyperspectral Data Acquisition

Introduction

The first acquisition of high resolution imagery for this effort was on July 17, 2006 under clear-sky conditions. The imagery was collected by SpectIR, a Nevada-based provider of airborne hyperspectral data. The imagery was collected at 1.5 meter resolution with SpectIR’s new Dual hyperspectral imaging system that uses bore-sighted VNIR and SWIR sensors (specifications below). Absolute positional error for the SpectIR imagery is reported as +/-3 meters. Space-borne hyperspectral imagery for the study areas was also collected by the Hyperion sensor on the Earth Observing-1 satellite. The Hyperion sensor measures radiance in 220 spectral bands ranging from 0.4 to 2.5 microns covering a ground swath of approximately 7.5 kilometers with 30 meter spatial resolution.

Acknowledgments

Field data were collected over a period of three days following the overpass of the aircraft. Percent cover data for the selected invasive species were collected for quadrats corresponding to the 1.5 meter pixels that were nested within a 3x3 pixel block. These plots covered a variety of plant size and cover classes, as well as different mixtures of plant species. In addition, polygons representing complete cover and complete absence by the targeted species were surveyed with precision GPS. Field spectra were acquired for vicarious calibration and to support the generation of vegetative endmembers. A combination of precision GPS measurements and recent orthophotography will be used to ensure proper registration of field measures with airborne imagery.

This work was funded through the National Aeronautics and Space Administration (NNS06AA91G).

High spatial resolution hyperspectral imagery collected from airborne platforms present a promising way to address basic and applied research questions regarding invasive species, as well as providing a mechanism for better understanding how available methods scale up to satellite-based systems. This project is testing the ability of airborne and space-borne hyperspectral remote sensing to map and monitor the distribution of specific noxious, non-native plants into rangeland, agricultural, and riparian landscapes of northern Nevada. This analysis will test multiple endmember spectral mixture analysis (MESMA) and stepwise discriminant functions for identifying the extent and percent cover of Lepidium latifolium (tall whitetop), Tamarix spp. (tamarisk), and Acroptilon repens (Russian knapweed) in the Humboldt River basin and elsewhere in Nevada. Research efforts will be coordinated with collaborators from the University of Nevada Cooperative Extension (UNCE) who work with agricultural and land management interests in the area. The developed monitoring techniques will complement ongoing control activities such as herbicide spraying and the use of biological control agents.

Our first field effort was successful, though we did encounter a number of challenges, including flooding and idiosyncratic scheduling of cutting and herbicide application in the agricultural study area. At this time, data entry has been completed from the field data sheets for plant cover that were recorded at the time of the overflight. SpecTIR is processing the hyperspectral data to a finished georeferenced radiance product, and initial quick-look products suggest good image data quality.

Measuring %cover of tall white-top (bottom-left) Measuring %cover of Russian knapweed

Data AnalysisThe first mapping approach to be tested will be multiple endmember spectral mixture analysis (MESMA), a form of linear mixture modeling that allows different, limited combinations of candidate spectral endmembers for vegetation to be tested in estimating the composition of each pixel. (Roberts et al., 1998). This analysis will be performed using the new “Viper Tools” ENVI plugin that has been developed by Dar Roberts’ research group at the University of California, Santa Barbara. While field spectra were acquired, it is expected that the high spatial resolution of the SpecTIR imagery will allow the use of image-based vegetation endmembers.

The second approach to be tested is a stepwise discriminant function analysis (DFA). The DFA approach presents an efficient way to identify unique spectral features of the target plant species and creates a transformation function that maximizes the difference of the target species from other image components. A stepwise approach will reduce problems with collinearity arising from correlation between adjacent spectral channels. As part of this effort we will develop software to integrate the DFA mapping method into the ENVI software environment.

Accuracy assessments will be performed for both discrete and continuously varying map products. This will provide information on the smallest detectable amount of vegetative cover at a given confidence level. In order to better understand the limitations of space-borne hyperspectral remote sensing for these invasive species, simulations will be performed in which the high resolution SpecTIR imagery will be sequentially degraded, both spatially and radiometrically, to match the acquired Hyperion imagery. A regression-based accuracy analysis will be applied across the simulations of degraded SpecTIR products to provide information on the tradeoffs for differing satellite sensor design parameters for spectral and spatial response. This will provide insight into the required spatial and spectral resolutions and signal-to-noise performance that will be required to map these species at a given level of confidence using space-borne instruments.

CIR composite of first tall white-top study area with GPS for plots and ground control locations

Collecting spectra of hoary cress

Specifications for the Dual Hyperspectral System