Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-28T02:45:55.488Z Has data issue: false hasContentIssue false

Distinguishing Brush and Weeds on Rangelands Using Video Remote Sensing

Published online by Cambridge University Press:  12 June 2017

James H. Everitt
Affiliation:
Remote Sensing Research Unit, Agr. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy. 83, Weslaco, TX 78596-8344
David E. Escobar
Affiliation:
Remote Sensing Research Unit, Agr. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy. 83, Weslaco, TX 78596-8344
Mario A. Alaniz
Affiliation:
Remote Sensing Research Unit, Agr. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy. 83, Weslaco, TX 78596-8344
Ricardo Villarreal
Affiliation:
Remote Sensing Research Unit, Agr. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy. 83, Weslaco, TX 78596-8344
Michael R. Davis
Affiliation:
Remote Sensing Research Unit, Agr. Res. Serv., U.S. Dep. Agric., 2413 E. Hwy. 83, Weslaco, TX 78596-8344

Abstract

This paper describes the application of a relatively new remote sensing tool, airborne video imagery, for distinguishing weed and brush species on rangelands. Plant species studied were false broomweed, spiny aster, and Chinese tamarisk. A multispectral video system that acquired color-infrared (CIR) composite imagery and its simultaneously synchronized three-band [near-infrared (NIR), red, and yellow-green] narrowband images was used for the false broomweed and spiny aster experiments. A conventional color camcorder video system was used to study Chinese tamarisk. False broomweed and spiny aster could be detected on CIR composite and NIR narrowband imagery, while Chinese tamarisk could be distinguished on conventional color imagery. Quantitative data obtained from digitized video images of the three species showed that their digital values were statistically different (P = 0.05) from those of associated vegetation and soil. Computer analyses of video images showed that populations of the three species could be quantified from associated vegetation. This technique permits area estimates of false broomweed, spiny aster, and Chinese tamarisk populations on rangeland and wildland areas.

Type
Research
Copyright
Copyright © 1990 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. Baum, B. R. 1967. Introduced and naturalized tamarisks in the United States and Canada. Baileya 15:1925.Google Scholar
2. Carneggie, D. M., Schrumpf, B. J., and Mouat, D. M. 1983. Rangeland applications. p. 23252384 in Colwell, R. N., ed. Manual of Remote Sensing, Vol. 2. Am. Soc. Photogrammetry and Remote Sensing, Falls Church, VA.Google Scholar
3. Driscoll, R. S. and Coleman, M. D. 1974. Color for shrubs. Photogram. Eng. and Remote Sensing 40:451460.Google Scholar
4. Escobar, D. E., Bowen, R. L., Gausman, H. W., and Cooper, G. R. 1983. Use of near-infrared video recording system for the detection of freeze-damaged citrus leaves. J. Rio Grande Valley Hortic. Soc. 36:6166.Google Scholar
5. Everitt, J. H. 1988. Introduction to videography: historical overview, relation to remote sensing, advantages, disadvantages. p. 14. Proc. First Workshop on Videography. Am. Soc. Photogrammetry and Remote Sensing, Falls Church, VA.Google Scholar
6. Everitt, J. H. and Deloach, C. J. 1990. Remote sensing of Chinese tamarisk (Tamarix chinensis) and associated vegetation. Weed Sci. 38:273278.Google Scholar
7. Everitt, J. H., Escobar, D. E., Gerbermann, A. H., and Alaniz, M. A. 1988. Detecting saline soils with video imagery. Photogram. Eng. and Remote Sensing. 54:12831287.Google Scholar
8. Everitt, J. H., Escobar, D. E., and Judd, F. W. 1991. Evaluation of video imagery for distinguishing black mangrove (Avicennia germinans) on the lower Texas gulf coast. J. Coastal Res. 7:11691173.Google Scholar
9. Everitt, J. H., Escobar, D. E., Villarreal, R., Noriega, J. R., and Davis, M. R. 1991. Airborne video systems for agricultural assessment. Remote Sensing of Environment 35:231242.CrossRefGoogle Scholar
10. Everitt, J. H., Ingle, S. J., Gausman, H. W., and Mayeux, H. S. Jr. 1984. Detection of false broomweed (Ericameria austrotexana) by aerial photography. Weed Sci. 32:621624.CrossRefGoogle Scholar
11. Everitt, J. H. and Nixon, P. R. 1985. Video imagery: A new remote sensing tool for range management. J. Range Manage. 38:421424.Google Scholar
12. 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. 35:295302.CrossRefGoogle Scholar
13. 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. 25:437440.CrossRefGoogle Scholar
14. Horton, J. S. and Campbell, C. J. 1974. Management of phreatophyte and riparian vegetation for maximum multiple use values. USDA For. Serv. Paper RM-117. 23 p.Google Scholar
15. Kerpez, T. A. and Smith, N. S. 1989. Saltcedar control for wildlife habitat improvement in the southwestern United States. USDI, U.S. Fish Wildl. Serv. Resour. Publ. 169. 16 p.Google Scholar
16. King, D. and Vlcek, J. 1990. Development of a multispectral video system and its application to forestry. Can. J. Remote Sensing 16:1522.CrossRefGoogle Scholar
17. Manzer, F. E. and Cooper, G. R. 1982. Use of portable video-taping for aerial infrared detection of potato disease. Plant Dis. 66:665667.Google Scholar
18. Mayeux, H. S. Jr. and Chamrad, A. D. 1982. Response of false broomweed (Ericameria austrotexana) and associated herbaceous vegetation to pelleted herbicides. Weed Sci. 30:668671.CrossRefGoogle Scholar
19. Mayeux, H. S. Jr., Scifres, C. J., and Crane, R. A. 1980. Ericameria austrotexana and associated range forage responses to herbicides. Weed Sci. 28:602606.Google Scholar
20. Mayeux, H. S. Jr., Scifres, C. J., and Meyer, R. E. 1979. Some factors affecting the response of spiny aster to herbicide sprays. Texas Agr. Exp. Stn. B-1197. 16 p.Google Scholar
21. Meisner, D. E. and Lindstrom, O. M. 1985. Design and operation of a color-infrared aerial video system. Photogram. Eng. and Remote Sensing 51:555560.Google Scholar
22. Mutz, J. L., Scifres, C. J., Mohr, W. C., and Drawe, D. L. 1979. Control of willow baccharis and spiny aster with pelleted herbicides. Texas Agr. Exp. Stn. B-1194. 12 p.Google Scholar
23. Myers, V. I., Bauer, M. E., Gausman, H. W., Hart, W. G., Heilman, J. L., McDonald, R. B., Park, A. B., Ryerson, R. A., Schmugge, T. J., and Westin, F. C. 1983. Remote sensing in agriculture. p. 21112228 in Colwell, Robert N., ed. Manual of Remote Sensing. Am. Soc. Photogrammetry, Falls Church, VA.Google Scholar
24. Myhre, R. J. 1987. Applications of aerial photography to several new and unusual vegetation pest problems. p. 4953. Proc. 10th Biennial Workshop on Color Aerial Photography in the Plant Sciences. Am. Soc. Photogrammetry and Remote Sensing, Falls Church, VA.Google Scholar
25. Nixon, P. R., Escobar, D. E., and Bowen, R. L. 1987. A multi-video false color imaging system for remote sensing applications. p. 295305, 340. Proc. 11th Biennial Workshop on Color Aerial Photography and Videography in the Plant Sciences. Am. Soc. Photogrammetry and Remote Sensing, Falls Church, VA.Google Scholar
26. Nixon, P. R., Escobar, D. E., and Menges, R. M. 1985. Use of a multi-band video system for quick assessment of vegetal condition and discrimination of plant species. Remote Sensing of Environment 17:203208.CrossRefGoogle Scholar
27. Richardson, A. J., Escobar, D. E., Gausman, H. W., and Everitt, J. H. 1981. Use of LANDSAT-2 data technique to estimate silverleaf sunflower infestation. p. 676683. Proc. Machine Processing of Remotely Sensed Data Symposium, Purdue Univ. Google Scholar
28. Richardson, A. J., Menges, R. M., and Nixon, P. R. 1985. Distinguishing weed from crop plants using video remote sensing. Photogram. Eng. and Remote Sensing 51:17851790.Google Scholar
29. Steel, R.G.D. and Torrie, J. H. 1980. Principles and procedures of statistics. McGraw-Hill Book Co., New York. 481 p.Google Scholar
30. Tueller, P. T. 1982. Remote sensing for range management. p. 125140 in Johannsen, C. J. and Sanders, J. L., eds. Remote Sensing in Resource Management. Soil Conserv. Soc. Am., Ankeny, IA.Google Scholar
31. Tueller, P. T. and Swanson, J. D. 1973. Color and color-infrared photography for evaluating vegetation characteristics in the cold deserts of central Nevada. p. 128155. Proc. 4th Biennial Workshop on Color Aerial Photography in the Plant Sciences. Am. Soc. Photogrammetry, Falls Church, VA.Google Scholar
32. Vlcek, J. 1983. Videography: some remote sensing applications. p. 6369. Proc. 49th Annual Meeting Am. Soc. Photogrammetry. Am. Soc. Photogrammetry, Falls Church, VA.Google Scholar
33. Vlcek, J. and King, D. 1985. Development and use of a 4-camera video system. p. 483489. Proc. 19th Int. Symp. on Remote Sensing of Environment. Univ. of Michigan, Ann Arbor, MI.Google Scholar