EO-1 Science Validation Team Progress Report for 2001

Final Report: EO-1 EVALUATION AND VALIDATION: NRA-99-OES-01

Title: Detection and Mapping of Invasive Leafy Spurge Using Orbital Hyperspectral Imagery from the EO-1 Mission

Category: B - Hyperspectral Applications

Principal Investigator Name: Ralph Root

Department: U.S. Department of the Interior

Institution: U.S. Geological Survey, Rocky Mountain Mapping Center DFC Bldg. 810, MS 516 Denver, CO 80225 USA E-mail: [email protected] Phone: (303) 202-4339 FAX: (303) 202-4354

Co-Investigators:

Steve Hager, National Park Service, Theodore Roosevelt National Park (701)623-4466 x3433 [email protected]

Susan Ustin, University of California Davis, CSTARS Laboratory (530) 752-5092 [email protected]

Gerry Anderson, Agricultural Research Service, Sidney, MT (406) 482-9416 [email protected]

Raymond Kokaly, U.S. Geological Survey, Spectroscopy Laboratory, Denver, CO (303)236-1359 [email protected]

Pre-launch accomplishments: Because the launch of EO-1 did not take place in early 2000 one of the first project activities was to reschedule the coordinated AVIRIS mission from summer of 2000 to summer of 2001. We also arranged with Theodore Roosevelt National Park to postpone their intensive ground validation effort for delineating leafy spurge polygons by multiple GPS teams from the 2000 growing season to 2001.

As a result of early (1999) success with AVIRIS in extracting leafy spurge spectra from neighboring vegetation types, (Root and Wickland, 2000, 2001), the USDA Agricultural Research Service Northern Plains Agricultural Research Laboratory made the decision to purchase a CASI II (Compact Airborne Spectrographic Imager) system to test mapping at higher spatial resolution within the visible and near infrared portions of the electromagnetic spectrum. The first CASI data were flown over Theodore Roosevelt NP and the Little Missouri Grasslands west of the park during the 2000 growing season. Success in calibrating these data and mapping leafy spurge have been reported by Kokaly et al. (2001a, 2002), and detection/mapping has been demonstrated using both field collected spectra (Kokaly et al., 2001b) and from training areas extracted from the imagery (Root et al., 2001a). CASI data were flown again in the 2001 growing season on July 5 and 23, and are currently being calibrated and classified to enable comparisons with the previous growing season. For both the 2000 and 2001 flights, the CASI II spectrometer was configured to collect data from 400 to 1100 nm in 36 spectral bands with 4 m spatial ground resolution. The CASI data completes the sequence of imaging spectrometers from low altitude to high altitude to orbital. The CASI data were a significant addition to this research because it enabled us to make three-way comparisons of classification results from each of these sensors, illustrating specific capabilities of each platform for detecting and mapping leafy spurge. (Root et al., 2002).

Also during the 2000 growing season hundreds of ground spectra using three ASD-FR (Analytical Spectral Devices) portable spectrometers. Spectra were collected at not only the calibration site (a 2+ acre paved parking lot), but also for a wide range of stands of leafy spurge, a variety of grasses, sagebrush, rabbit brush, snowberry, yellow sweet clover, and soil.

2001 data acquisitions: Three EO-1 data acquisitions occurred during 2001 for the Theodore Roosevelt study area. Dates were May 23, July 6, and September 24. Leafy spurge was just emerging on May 3, was in full bract development on July 6, and was in its fall coloration on September 24. A coordinated AVIRIS overflight occurred on June 21, 2001. Although the goal was to schedule the AVIRIS acquisition as close to the hyperion DCE as possible, the two week interval still allow useful comparisons between leafy spurge detection with each of the sensors.

Hyperion data analysis: Level 1 hyperion data from the July 6 Data Collection Event (DCE) were manually edited to remove anomalous scan lines (by averaging values of adjacent lines) and corrected for atmospheric effects. Ground spectra obtained from our calibration site (large asphalt parking area) were used to calibrate the atmospherically corrected data to surface reflectance. Surface reflectance data were then used to classify leafy spurge via several methods (spectral angle mapper, red-edge spectral parameters, and iso-class clustering), obtaining accuracies ranging from approximately 60% to 80%. Details of methodologies and results are reported in Root et al., 2002b.

2001 field data collection: The leafy spurge EO-1 team and other collaborators working on related projects conducted a week-long joint field data collection effort from July 2 through July 6, 2001. A total of four ASD-FR full range ground spectrometers and 10 scientists participated in the 2001 field session. Several thousand spectra of leafy spurge and related shrubs and grasses were collected, along with several hundred calibration site spectra which were obtained in conjunction with the EO-1 overpass on July 6. In a separate field effort, several hundred calibration spectra were obtained simultaneously with the AVIRIS overflight on June 21. Project collaborators eventually hope to compile these spectra, plus those obtained in the three previous years, in a publishable form such as a CDROM or website, for use by other researchers.

2001 leafy spurge canopy analysis: (Pablo J. Zarco-Tejada (CSTARS, UCDavis) A field sampling campaign was carried out for biochemical analysis of leaf chlorophyll concentrations through SPAD-502 chlorophyll meter readings (Minolta Camera Co., Ltd., Japan) along with leaf reflectance and transmittance. Leaf and bracts optical measurements were acquired from the leafy spurge samples at different locations in order to use reflectance and transmittance as inputs in the canopy reflectance models. Scaling- up from leaf level to canopy level requires leaf reflectance and transmittance data as input to canopy reflectance models.

Single leaf reflectance and transmittance measurements were acquired on all leaves and bracts using a Li-Cor 1800-12 Integrating Sphere apparatus coupled by a 200 m diameter single mode fiber to an GER-2600 spectrometer yielding a 0.5 nm sampling interval and 2.5 nm spectral resolution in the 340-2500 nm range. Single leaf reflectance and transmittance measurements were acquired with the integrated sphere following the methodology described in the manual of the Li-Cor 1800-12 system in which six signal measurements are required: transmittance signal (TSP), reflectance signal (RSS), reflectance internal standard (RTS), reflectance external reference (RST), and dark measurements (TDP, RSD). Reflectance (Rfl) and transmittance (Tns) are calculated assuming a constant center wavelength and spectral bandpass (Equations [1] and [2]).

(RSS  RSD)  Rfl Rfl  BaSO4 RTS  RSD [1]

(TSP  TDP)  Rfl Tns  BaSO4 [2] RST  RSD

with RflBaSO4 the reflectance of Barium Sulfate.

The laboratory measurements of leafy spurge reflectance and transmittance along with structural parameters permit the simulation of canopy reflectance through radiative transfer modeling. The approach adopted (Zarco-Tejada et al., 2001) is to use leaf level reflectance and transmittance data to calculate the corresponding above-canopy reflectance through optically-thick vegetation (infinite reflectance R) formulae and through canopy reflectance models.

In more comprehensive approach, the single leaf reflectance and transmittance data collected from the ground-truth deployment are used to derive above-canopy level reflectances through SAILH (Verhoef, 1984), Kuusk (Kuusk, 1996) and GeoSAIL (Huemmrich, 2001) canopy reflectance models. The GeoSAIL model allows for designing multiple components in the simulated canopy reflectance, therefore considering the optical properties of the sampled elements within the leafy spurge patches. Model inversion methods as a function of the density of each component in the simulated scene will be carried out, estimating by iterative optimization and spectral matching the input parameters that minimize the error between the measured Hyperion/AVIRIS hyperspectral reflectance and the simulated reflectance from the model.

A second approach being investigated is based on the calculation of red edge spectral parameters from hyperspectral data, which are a function of biophysical and biochemical constituents of the vegetation canopy. A method for the classification of land cover has recently been reported which exploits systematic differences by species of the reflectance in the short wave infrared spectral regions sensitive to foliar chemistry (Martin et al., 1998). Zarco-Tejada and Miller (1999) described classification of vegetated land cover based on spectral parameters that characterize the red edge reflectance region, which are responsive to foliar chlorophyll pigment levels. Classification with three red edge spectral parameters, red edge inflection point (p), the wavelength at the reflectance minimum

(o), and a shape parameter (), as defined by the inverted-gaussian red-edge curve-fit model (Hare et al., 1984; Miller et al., 1990; 1991) were carried out with the calibrated Hyperion data. The separation of land cover types and location of leafy spurge patches using this classification method is based on cover-type systematic differences in the variables known to affect red edge spectral parameters: vegetation chlorophyll content, canopy structure, canopy cover, and illumination. The inverted-gaussian red-edge curve- fit model for red-edge spectral parameter calculation, adapted for Hyperion reflectance data, was used to classify leafy spurge with an overall accuracy of 75% (Root et al., 2002)

Ground verification data for leafy spurge distributions during the 2001 growing season: In 2001 the National Park Service funded a seasonal team of scientists to document locations and descriptions of leafy spurge populations over several square miles of the Little Missouri River floodplain using sub-meter accuracy GPS field equipment (Harrison, 2001). Ground data collected in this project, developed into an ArcInfo coverage, was used to select spectra for image-derived training areas. In a separate study supported by the NPS and USGS, field surveys were conducted for three consecutive growing seasons from 1999 through 2001 to monitor responses of leafy spurge to chemical and biological control measures. This project entailed the collection of data from 550 3-m by 5-m plots to geographically document the presence/absence of leafy spurge and to produce detailed estimates of crown cover (through stem counts) and biomass for leafy spurge and associated native vegetation types. These data were used for accuracy assessment of the leafy spurge classifications developed in this study.

Final results and research outcomes:

Classification of leafy spurge from reflectance calibrated EO-1 Hyperion data obtained July 6, 2001 (at the peak of bract development) was performed using three methods: (1) spectral angle mapper applied to selected principal components, (2) red-edge spectral parameter calculation using the inverted Gaussian model to calculate p, o, and and Rs and Ro parameters pixel by pixelisoclass clustering using all reflectance bands, and (4) isoclass clustering with simulated landsat data. Overall classification accuracies ranged from 63% using the spectral Angle Mapper algorithm to 72-78% for the red-edge spectral parameters and isoclass clustering algorithms. Accuracy assessment details and classification methods are discussed in Root et al.,2002e.

Simulation of Landsat-sensor capabilities from Hyperion data shows promise for applications with less costly and more available types of data for the future analysis and monitoring of leafy spurge infestations. However, this study has demonstrated that better accuracy is achieved when hyperspectral satellite data are used for classification.

Suggested improvements to future imaging spectrometers that would further enhance the detection and mapping of leafy spurge and perhaps other types of invasive plants with similar growth characteristics would be (1) improved signal-to-noise ratio to enhance spectral discrimination, (2) increased spatial resolution, and (3) greater swath width to increase the coverage area and minimize data processing complexities associated with merging multiple data swaths.

Other collaborative efforts relating to the EO-1 study:

Predictive modeling of leafy spurge infestations and spreading characteristics: As the topic of his Ph.D. dissertation at Colorado State University, Karl Brown, USGS/BRD is developing an expert system model incorporating various types of GIS themes (i.e. soils, geology, topographic variation, drainage, etc.) with image classification, to identify the most likely areas of spread. Spread prediction will incorporate best known factors of plant physiology, soil preferences, moisture, and other factors identified in current efforts in leafy spurge control. By integrating biologic and physiographic factors, the expert system will assist managers in planning control efforts. The expert system will be designed to serve as a subroutine within the Team Leafy Spurge DSS, with outputs compatible to the DSS display and processing requirements. The factors affecting spread of leafy spurge, which drive the expert system, would reflect environmental conditions measured and modeled in the study area. It is hoped that these results could be applied in a larger regional context Expected completion: Early summer, 2002.

Determination of changes in leafy spurge distributions in connection with biological and chemical control measures undertaken by the park: This is a collaborative Ph.D. study by Kay Dudek of Colorado State University which involves analyzing 1999 and 2001 AVIRIS data missions to develop leafy spurge distribution maps for both dates, and to quantify changes in leafy spurge distributions with time/location documented pest control measures undertaken by the National Park Service.

Exploration of regional mapping techniques: Although leafy spurge can clearly be detected and mapped with hyperspectral sensors (on low and high altitude aircraft as well as from orbit), maps of leafy spurge over entire watersheds or states would be a monumental undertaking with the small data swaths covered by any of today’s hyperspectral sensors. There are also additional issues associated with storage and analysis logistics. Another aspect of leafy spurge research being analyzed is the the feasibility of using fused pan/MSS data from more regionally capable sensors such as Landsat 7, and its likely successors such as is characterized by the ALI (Advance Land Imager) on EO-1. A team of researchers at the USGS Rocky Mapping Center is currently examining the possibility of mapping leafy spurge over broader regions by developing algorithms that take advantage of the combination of multispectral and higher resolution panchromatic images available on current medium resolution sensors such as Landsat. A July 6, 2001 Landsat Scene, obtained 1 minute prior to the EO-1 Hyperion and ALI data acquisitions, is being used to explore the hypothesis that leafy spurge can be detected and mapped with Landsat with appropriate types of specifically designed algorithms. Expected analysis completion: June, 2002.

References

Anderson G. L., C. W. Prosser, R. Root, R. Kokaly, S. Hager, and B. Foster. 2001. A five-year comparison of leafy spurge (Euphorbia esula) populations using remote sensing and geographic information systems. Abstract: 221st Annual Meeting of the American Chemical Society. April 1-5, 2001. San Diego, CA. (Invited presentation).

Hare, E. W., J. R. Miller, and G. R. Edwards. 1984. Studies of the vegetation red reflectance edge in geobotanical remote sensing, in Proceedings of the 9th Canadian Symposium on Remote Sensing, pp. 433-440, Can. Remote Sens. Soc., Can. Aeronaut. and Space Inst., Ottawa, 1984.

Harrison, L. 2001. Ground Truthing Remotely Sensed Leafy Spurge Infestations at Theodore Roosevelt National Park: Methodology for Mapping Project using Global Positioning Systems and Geographic Information Systems. Theodore Roosevelt National Park. US Department of the Interior, National Park Service. Project Date – Summer 2001. Unpublished manuscript, Theodore Roosevelt National Park.

Huemmrich, K.F. 2001. The GeoSail model: a simple addition to the SAIL model to describe discontinuous canopy reflectance, Remote Sensing of Environment, 75(3), 2001.

Kokaly, R., R. Root, K. Brown, G. L. Anderson, and S. Hager. 2001a. Calibration of Compact Airborne Sepctrographic Imager (CASI) data to surface reflectance at Theodore Roosevelt National Park. Abstract: 221st Annual Meeting of the American Chemical Society. April 1-5, 2001. San Diego, CA. (Invited paper)

Kokaly, R. R. Root, K. Brown, S. Hager, and G. L. Anderson. 2001b. Discriminating leafy spurge spectral signature from native vegetation using field reflectance measurements from Theodore Roosevelt National Park, North Dakota. Abstract: 221st Annual Meeting of the American Chemical Society. April 1-5, 2001. San Diego, CA. (Invited paper)

Kokaly, R. F., Root, R., and K. Brown. 2001c. Mapping the Distribution of the Invasive Species Leafy Spurge (Euphorbia esula) in Theodore Roosevelt National Park Using Field Measurements of Vegetation Spectra and CASI Imaging Spectroscopy Data. Third International Conference on Geospatial Information in Agriculture and Forestry. Denver, Colorado. 5-7 November, 2001. Poster presentation: (won best in session award, in “Geospatial Information and Rangeland Management” poster session)

Kokaly, R.F., R. Root, K. Brown, S. Hager, and G. Anderson. 2002. “Calibration of CASI Data to Surface Reflectance at Theodore Roosevelt National Park for Mapping Invasive Species.” Submitted June 7, 2002, to International Journal of Remote Sensing.

Kuusk, A. 1996. A computer-efficient plant canopy reflectance model, Computers & Geosciences. 22:149-163.

Martin, M. E., S. D. Newman, J. D. Aber, and R. G. Congalton. 1998. Determining forest species composition using high spectral resolution remote sensing data, Remote Sens. Environ, 65, 249-254, 1998.

Miller, J. R., E. W. Hare, and J. Wu. 1990. Quantitative characterization of the vegetation red edge reflectance I. An inverted-Gaussian reflectance model, Int. J. Remote Sens., 11, 121-127, 1990.

Miller, J. R., J. Wu, M. G. Boyer, M. J. Belanger, and E.W. Hare. 1991. Seasonal patterns in leaf reflectance red edge characteristics, Int. J. Remote Sens., 12, 1509-1524, 1991.

Root, R., R. Kokaly, K. Brown, and G. L. Anderson. 2001. Detection of leafy spurge infestations via imaging spectroscopy using the Compact Airborne Spectrographic Imager (CASI). Abstract: 221st Annual Meeting of the American Chemical Society. April 1-5, 2001. San Diego, CA. (Invited paper)

Root, R. and D. Wickland. 2000. Hyperspectral Technology Transfer to the U.S. Department of the Interior: Status and Results of the NASA/Department of the Interior Hyperspectral Technology Transfer Project. Proceedings of the Ninth JPL Airborne Earth Science Workshop. NASA Jet Propulsion Laboratory, Pasadena, CA. JPL Publication 00-18.

Root, R. and D. Wickland. 2001. Hyperspectral Technology Transfer to the U.S. Department of the Interior: Hyperspectral Technology Transfer to the U.S. Dept. of Interior: Summary of Results of the NASA/DOI Hyperspectral Technology Transfer Project Proceedings of the Tenth JPL Airborne Earth Science Workshop. NASA Jet Propulsion Laboratory, Pasadena, CA.

Root, R., Ray Kokaly, Karl Brown, Carol Mladinich, Susan Stitt, and Alex Konduris, Susan Ustin, Pablo Zarco-Tejada, Steve Hager, Gerry Anderson, Kay Dudek, and Ed Holroyd. 2002a. Comparisons of orbital and aircraft hyperspectral systems for classification and mapping of invasive leafy spurge in southwestern North Dakota. U.S. Geological Survey Colloquium, January 24, 2002. Denver Federal Center, Denver, CO. Monthly scientific forum, presented to the general public by the USGS. Root, R., Susan Ustin, Pablo Zarco-Tejada, Carlos Pinilla, Ray Kokaly, Karl Brown, Gerry Anderson, Steve Hager, Kay Dudek, and Ed Holroyd. 2002b. Comparison of High, Medium, and Low Spatial Resolution Hyperspectral Sensors for Mapping of Invasive Leafy Spurge in Theodore Roosevelt National Park, North Dakota 2002 ASPRS-ACSM Annual Conference and FIG Congress, Washington, DC, April 22-26, 2002 (abstract).

Root, R., Kokaly, R., Anderson, G., and Hager, S. 2002c. Comparison of EO-1 hyperion, AVIRIS, and CASI hyperspectral imaging systems for detecting and mapping leafy spurge infestations in southwestern North Dakota. Preceedings of the 11th JPL Airborne Earth Science Workshop. NASA-JPL, Pasadena, CA. March, 2002

Root, R., Susan Ustin, Pablo Zarco-Tejada, Carlos Pinilla, Ray Kokaly, Karl Brown, Gerry Anderson, Steve Hager, Kay Dudek, and Ed Holroyd. 2002d. Identification, Canopy Characterization, and Mapping of Invasive Leafy Spurge with the EO-1 Hyperion Orbital Imaging Spectrometer. 2002 International Geoscience and Remote Sensing Symposium, Toronto, June 25, 2002.

Root, R., Zarco-Tejada, P., Ustin, S., Anderson, G., Kokaly, R., Hagar, S., Brown, K. 2002e. Comparison of orbital EO-1 hyperion and high altitude aircraft AVIRIS imaging spectrometers for detecting and mapping invasive leafy spurge at Theodore Roosevelt National Park, ND. IEEE transactions for the International Geoscience and Remote Sensing Society, Special Issue on initial results of the investigations conducted by the NASA EO-1 Science Validation Team. Submitted May, 2002, currently under peer review.

Verhoef, W. 1984. Light scattering by leaf layers with application to canopy reflectance modelling: the SAIL model, Remote Sensing of Environment, 16:125-141, 1984.

Zarco-Tejada, P. J. and Miller, J. R. 1999. Land cover mapping at BOREAS using red edge spectral parameters from CASI imagery, Journal of Geophysical Research. 104:27921-27933.

Zarco-Tejada, P.J., J.R. Miller, G.H. Mohammed, T.L. Noland and P.H. Sampson. 2001. Scaling-up and Model Inversion methods with narrow-band Optical Indices for Chlorophyll Content Estimation in closed Forest Canopies with Hyperspectral Data, IEEE Transactions on Geoscience and Remote Sensing, 39(7), 2001.