Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-24T07:25:47.495Z Has data issue: false hasContentIssue false
  • English
  • Français

Integration of Airborne Video, Global Positioning System and Geographic Information System Technologies for Detecting and Mapping Two Woody Legumes on Rangelands

Published online by Cambridge University Press:  12 June 2017

James H. Everitt ,
David E. Escobar ,
Ricardo Villarreal ,
Mario A. Alaniz  and
Michael R. Davis
James H. Everitt
Affiliation:
U. S. Dep. Agric., Agric. Res. Serv., Subtropical Agric. Res. Lab., Remote Sensing Res. Unit, Weslaco, TX 78596-8344
David E. Escobar
Affiliation:
U. S. Dep. Agric., Agric. Res. Serv., Subtropical Agric. Res. Lab., Remote Sensing Res. Unit, Weslaco, TX 78596-8344
Ricardo Villarreal
Affiliation:
U. S. Dep. Agric., Agric. Res. Serv., Subtropical Agric. Res. Lab., Remote Sensing Res. Unit, Weslaco, TX 78596-8344
Mario A. Alaniz
Affiliation:
U. S. Dep. Agric., Agric. Res. Serv., Subtropical Agric. Res. Lab., Remote Sensing Res. Unit, Weslaco, TX 78596-8344
Michael R. Davis
Affiliation:
U. S. Dep. Agric., Agric. Res. Serv., Subtropical Agric. Res. Lab., Remote Sensing Res. Unit, Weslaco, TX 78596-8344
Get access Rights & Permissions [Opens in a new window]

Abstract

Blackbrush acacia and huisache, two troublesome woody legumes on Texas rangelands, could be distinguished on conventional color aerial video imagery. The integration of a global positioning system with the video imagery permitted latitude/longitude coordinates of blackbrush acacia and huisache infestations to be recorded on each image. Global positioning system coordinates were entered into a geographic information system to map blackbrush acacia and huisache populations over an extensive rangeland area.

Keywords

Blackbrush acacia, Acacia rigidula Benth., # ACARIhuisache, Acacia farnesiana (L.) Willd. # ACAFAConventional color video imageryACARIACAFA
Type
Research
Information
Weed Technology , Volume 7 , Issue 4 , December 1993 , pp. 981 - 987
Copyright
Copyright © 1994 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. Anonymous. 1967. Munsel Book of Color. Neighboring Hue Edition. Matte Finish Collection. Munsel Color Co., Inc. Baltimore, MD.Google Scholar
2. Bobbe, T. J. 1992. Real-time differential GPS for aerial surveying and remote sensing. GPS World 3(7):18–22.Google Scholar
3. Bobbe, T. J. and Ishikawa, P. 1992. Real-time differential GPS: An aerial survey—remote sensing applications. Proc. Resource Technology 92 Symp. Am. Soc. Photogramm. Remote Sensing. Bethesda, MD. p. 108–116.Google Scholar
4. Everitt, J. H. 1985. Using aerial photography for detecting blackbrush (Acacia rigidula) on south Texas rangelands. J. Range Manage. 38: 228–231.Google Scholar
5. Everitt, J. H., Escobar, D. E., Alaniz, M. A., Villarreal, R., and Davis, M. R. 1992. Distinguishing brush and weeds on rangelands using video remote sensing. Weed Technol. 6:913–921.Google Scholar
6. 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. 7:1169–1173.Google Scholar
7. Everitt, J. H., Escobar, D. E., and Nixon, P. R. 1987. Near-real-time video systems for rangeland assessment. Remote Sensing of Environment 23:291–311.Google Scholar
8. 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 35:231–242.Google Scholar
9. Everitt, J. H. and Villarreal, R. 1987. Detecting huisache (Acacia farnesiana) and Mexican palo-verde (Parkinsonia aculeata) by aerial photography. Weed Sci. 35:427–432.Google Scholar
10. King, D. and Vlcek, J. 1990. Development of a multispectral video system and its application in forestry. Canadian J. Remote Sensing 16: 15–22.Google Scholar
11. Manzer, F. E. and Cooper, G. R. 1982. Use of portable video-taping for aerial infrared detection of potato disease. Plant Dis. 66:665–667.Google Scholar
12. Meisner, D. E. and Lindstrom, O. M. 1985. Design and operation of a color-infrared aerial video system. Photogramm. Eng. Remote Sensing 51:555–560.Google Scholar
13. Mutz, J. L., Scifres, C. J., Drawe, D. L., Box, T. W., and Whitson, R. E. 1978. Range vegetation after mechanical brush treatment on the Coastal Prairie. Texas Agric. Exp. Stn. Bull. 1191. 16 p.Google Scholar
14. Myhre, R. J. 1992. Use of color airborne videography in the U. S. Forest Service. Proc. Resource Technology 92 Symp. Am. Soc. Photogramm. Remote Sensing. Bethesda, MD. p. 145–152.Google Scholar
15. Nixon, P. R., Escobar, D. E., and Bowen, R. L. 1987. A multi-video false color imaging system for remote sensing applications. Proc. 11th Biennial Workshop on Color Aerial Photography and Videography in the Plant Sciences. Am. Soc. Photogramm. Remote Sensing, Falls Church, VA. p. 295–305, 340.Google Scholar
16. Scifres, C. J. 1980. Brush Management. Texas A & M Univ. Press. College Station, Texas.Google Scholar
17. Steel, R.G.D. and Torrie, J. H. 1980. Principles and Procedures of Statistics. McGraw-Hill Book Co., New York. 481 p.Google Scholar
18. Vlcek, J. 1983. Videography: some remote sensing applications. Proc. 49th Annu. Meet. Am. Soc. Photogramm., Am. Soc. Photogramm. Remote Sensing, Falls Church, VA. p. 63–69.Google Scholar