Hostname: page-component-76fb5796d-r6qrq Total loading time: 0 Render date: 2024-04-28T00:30:01.068Z Has data issue: false hasContentIssue false
  • English
  • Français

Use of Remote Sensing for Detecting and Mapping Leafy Spurge (Euphorbia esula)

Published online by Cambridge University Press:  12 June 2017

James H. Everitt ,
Gerald L. Anderson ,
David E. Escobar ,
Michael R. Davis ,
Neal R. Spencer  and
Roger J. Andrascik
James H. Everitt
Affiliation:
Remote Sensing Research Unit, Agric. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy 83, Weslaco, TX 78596
Gerald L. Anderson
Affiliation:
Remote Sensing Research Unit, Agric. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy 83, Weslaco, TX 78596
David E. Escobar
Affiliation:
Remote Sensing Research Unit, Agric. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy 83, Weslaco, TX 78596
Michael R. Davis
Affiliation:
Remote Sensing Research Unit, Agric. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy 83, Weslaco, TX 78596
Neal R. Spencer
Affiliation:
Agric. Res. Serv., U.S. Dep. Agric., P.O. Box 1109, Sydney, MT 59270
Roger J. Andrascik
Affiliation:
National Park Service, U.S. Dep. Inter., P.O. Box 7, Medora, ND 58645
Get access Rights & Permissions [Opens in a new window]

Abstract

Leafy spurge is a troublesome, exotic weed in the northern Great Plains of the United States. Leafy spurge produces showy yellow bracts during June that give this weed a conspicuous appearance. A study was conducted to determine the feasibility of using remote sensing techniques to detect leafy spurge in this phenological stage. Study sites were located in North Dakota and Montana. Plant canopy reflectance measurements showed that leafy spurge had higher visible (0.63- to 0.69-μm) reflectance than several associated plant species. The conspicuous yellow bracts of leafy spurge gave it distinct yellow-green and pink images on conventional color and color-infrared aerial photographs, respectively. Leafy spurge also could be distinguished on conventional color video imagery where it had a golden yellow image response. Quantitative data obtained from digitized video images showed that leafy spurge had statistically different digital values from those of associated vegetation and soil. Computer analyses of video images showed/that light reflected from leafy spurge populations could be quantified from associated vegetation. This technique permits area estimates of leafy spurge populations. Large format conventional color photographs of Theodore Roosevelt National Park near Medora, ND were digitized and integrated with a geographic information system to produce a map of leafy spurge populations within the park that can be useful to monitor the spread or decline of leafy spurge.

Keywords

Leafy spurge, Euphorbia esula L.,# EPHESColor-infrared photographyconventional color photographyconventional color video imagerygeographic information systemglobal positioning systemlight reflectance
Type
Research
Information
Weed Technology , Volume 9 , Issue 3 , September 1995 , pp. 599 - 609
Copyright
Copyright © 1995 by the Weed Science Society of America 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

1. Alley, H. P. and Messersmith, C. G. 1985. Chemical control of leafy spurge. p. 65–79 in Watson, A. K., ed. Leafy Spurge. Weed Sci. Soc. Am., Champaign, IL.Google Scholar
2. Anderson, G. L., Everitt, J. H., Richardson, A. J., and Escobar, D. E. 1993. Using satellite data to map false broomweed (Ericameria austrotexana) infestations on South Texas rangelands. Weed Technol. 7:865–871.CrossRefGoogle Scholar
3. Anderson, G. L., Hanson, J. D., and Haas, R. H. 1993. Evaluating LANDS AT thematic mapper derived vegetation indices for estimating above-ground biomass on semi-arid rangelands. Remote Sens. Environ. 45:165–175.Google Scholar
4. Anonymous. 1989. Biological control of leafy spurge. U.S. Dep. of Agric., Animal and Plant Health Inspection Serv. Progress Aid No. 1435. 11 p.Google Scholar
5. Bowers, S. A. and Hanks, R. J. 1965. Reflectance of radiant energy from soils. Soil Sci. 100:130–138.Google Scholar
6. Dewey, S. A., Price, K. P., and Ramsey, D. 1991. Satellite remote sensing to predict potential distribution of Dyers woad (Isatis tinctoria). Weed Technol. 5:479–484.Google Scholar
7. Eidenshink, J. C., Haas, R. H., Zokaites, D. M., Ohlen, D. O., and Gallo, K. P. 1988. Integration of remote sensing and GIS technology to monitor fire danger in the Northern Great Plains. U.S. Geol. Surv. Contract 14-08-0001-22521. 13 p.Google Scholar
8. Elliston, R. and Miller, L. D. 1987. Mapping leafy spurge with color video and micro-computer image processing. p. 61–63 in Proc. West. Soc. Weed Sci. Vol. 40.Google Scholar
9. Everitt, J. H., Alaniz, M. A., Escobar, D. E., and Davis, M. R. 1992. Using remote sensing to distinguish common (Isocoma coronopifolia) and Drummond goldenweed (Isocoma drummondii). Weed Sci. 40:621–628.Google Scholar
10. Everitt, J. H. and Deloach, C. J. 1990. Remote sensing of Chinese tamarisk (Tamarix chinensis) and associated vegetation. Weed Sci. 38:273–278.Google Scholar
11. Everitt, J. H., Escobar, D. E., Gerbermann, A. H., and Alaniz, M. A. 1988. Detecting saline soils with video imagery. Photogramm. Eng. Remote Sens. 54:1283–1287.Google Scholar
12. Everitt, J. H., Escobar, D. E., Villarreal, R., Alaniz, M. A., and Davis, M. R. 1993. Canopy light reflectance and remote sensing of shin oak (Quercus havardii) and associated vegetation. Weed Sci. 41:291–297.Google Scholar
13. Everitt, J. H., Richardson, A. J., and Nixon, P. R. 1986. Canopy reflectance characteristics of succulent and nonsucculent rangeland plant species. Photogramm. Eng. Remote Sens. 52:1891–1897.Google Scholar
14. Everitt, J. H., Richerson, J. V., Alaniz, M. A., Escobar, D. E., Villarreal, R., and Davis, M. R. 1994. Light reflectance characteristics and remote sensing of Big Bend loco (Astragalus mollissimus var. earlei) and Wooton loco (Astragalus wootonii). Weed Sci. 42:115–122.Google Scholar
15. Everitt, J. H., Pettit, R. D., and Alaniz, M. A. 1987. Remote sensing of broom snakeweed (Gutierrezia sarothrae) and spiny aster (Aster spinosus). Weed Sci. 35:295–302.Google Scholar
16. Everitt, J. H., Richardson, A. J., and Wiegand, C. L. 1981. Inventory of semi-arid rangelands in south Texas with Landsat data. p. 404–415 in Proc. Symp. Machine Processing Remotely Sensed Data. LARS, Purdue Univ., West Lafayette, IN.Google Scholar
17. Everitt, J. H. and Villarreal, R. 1987. Detecting huisache (Acacia farnesiana) and Mexican palo-verde (Parkisonia aculeata) by aerial photography. Weed Sci. 35:427–432.CrossRefGoogle Scholar
18. Fay, P. K. 1991. Controlling leafy spurge with grazing animals. p. 193–199 in James, L. F., Evans, J. O., Ralphs, M. H., and Child, R. D., eds. Noxious Range Weeds. Western Press, Boulder, CO.Google Scholar
19. Gausman, H. W., Menges, R. M., Escobar, D. E., Everitt, J. H., and Bowen, R. L. 1977. Pubescence affects spectra and imagery of silverleaf sunflower (Helianthus argophyllus). Weed Sci. 25:437–440.Google Scholar
20. Graetz, R. D., Pech, R. P., Gentle, M. R., and O'Callaghan, J. F. 1983. The application of Landsat image data to rangeland assessment and monitoring: the development and demonstration of a land image-based resource information system (LIBRIS). J. Arid Environ. 10:53–80.Google Scholar
21. Gylling, S. R. and Arnold, W. E. 1985. Efficacy and economics of leafy spurge (Euphorbia esula) control on pasture. Weed Sci. 33:381–385.Google Scholar
22. Lacey, C. A., Fay, P. K., Lym, R. G., Messersmith, C. G., Maxwell, B., and Alley, H. P. 1985. The distribution, biology and control of leafy spurge. Circ. 309. Coop. Ext. Serv., Montana State Univ., Bozeman, MT. 15 p.Google Scholar
23. Landgraf, B. K., Fay, P. K., and Havstad, K. M. 1984. Utilization of leafy spurge (Euphorbia esula) by sheep. Weed Sci. 32:348–352.Google Scholar
24. Lym, R. G. and Messersmith, C. G. 1985. Leafy spurge control with herbicides in North Dakota: 20-year summary. J. Range Manage. 38:149–154.Google Scholar
25. Menges, R. M., Nixon, P. R., and Richardson, A. J. 1985. Light reflectance and remote sensing of weeds in agronomic and horticultural crops. Weed Sci. 33:569–581.Google Scholar
26. Myhre, R. J. 1987. Applications of aerial photography to several new and unusual vegetation pest problems. p. 49–53 in Proc. 10th Biennial Workshop on Color Aerial Photography in the Plant Sciences. Am. Soc. Photogramm. Remote Sens., Falls Church, VA.Google Scholar
27. Myhre, R. J. 1992. Use of color airborne videography in the U.S. Forest Service. p. 145–152 in Proc. Resource Technol. 92 Symp. Am. Soc. Photogramm. Remote Sens., Bethesda, MD.Google Scholar
28. Noble, D. L., Dunn, P. H., and Andres, L. A. 1979. The leafy spurge problem. p. 8–15 in Proc. Leafy Spurge Symposium. North Dakota Coop. Ext. Serv., Fargo, ND.Google Scholar
29. Prather, T. S. and Callihan, R. H. 1993. Weed eradication using geographic information systems. Weed Technol. 7:265–269.CrossRefGoogle Scholar
30. Quimby, P. C., Bruckart, W. L., Deloach, C. J., Knutson, L., and Ralphs, M. H. 1991. Biological control of rangeland weeds. p. 85–102 in James, L. F., Evans, J. O., Ralphs, M. H., and Child, R. D., eds. Noxious Range Weeds. Westview Press, Boulder, CO.Google Scholar
31. Rees, N. E. and Spencer, N. R. 1991. Biological control of leafy spurge. p. 182–192 in James, L. F., Evans, J. O., Ralphs, M. H., and Child, R. D., eds. Noxious Range Weeds. Westview Press, Boulder, CO.Google Scholar
32. Richardson, A. J. 1981. Measurement of reflectance factors under daily and intermittent irradiance variations. Appl. Optics 20:1336–1340.Google Scholar
33. Richardson, A. J., Summy, K. R., Davis, M. R., Gomez, A., and Williams, D. W. 1993. The use of 1990 Tiger/Line Census files for monitoring the Rio Grande Valley cotton stalk destruction program. Proc. Appl. Advanced Inf. Technnol. Symp. p. 231–239.Google Scholar
34. Richardson, A. J., Wiegand, C. L., Gausman, H. W., Cuellar, J. A., and Gerbermann, A. H. 1975. Plant, soil, and shadow reflectance components of row crops. Photogramm. Eng. Remote Sens. 41:1401–1407.Google Scholar
35. Skidmore, E. L., Dickerson, J. D., and Schimmelpfennig, H. 1975. Evaluating surface-soil water content by measuring reflectance. Soil Sci. Soc. Am. Proc. 39:238–242.Google Scholar
36. Steel, R.G.D. and Torrie, J. H. 1980. Principles and Procedures of Statistics. McGraw-Hill Book Co., New York. 481 p.Google Scholar
37. Stevens, O. A. 1963. Handbook of North Dakota Plants. Cushing-Malloy, Inc. Ann Arbor, MI. p. 197.Google Scholar
38. Tucker, C. J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8:127–150.Google Scholar
39. Tucker, C. J., Jones, W. H., Kley, W. A., and Sunstorm, C. J. 1980. The GSFC MARK-II three band hand-held radiometer. NASA Tech. Memo. 80641. 8 Google Scholar
40. Tueller, P. T. 1982. Remote sensing for range management. p. 125–140 in Johannsen, C. J. and Sanders, J. L., eds. Remote Sensing for Resource Management. Soil Conserv. Soc. Am., Ankeny, IO.Google Scholar