Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

Authors

  • H Zhang Department of Biological and Agricultural Engineering, Texas A&M University, College Station
  • Y. Lan Agricultural Engineer, USDA-ARS-SPARC-APMRU
  • R. Lacey
  • W. C. Hoffmann
  • Y. Huang

Abstract

Aerial multispectral images are a good source of crop, soil, and ground coverage information. Spectral reflectance indices provide a useful tool for monitoring crop growing status. A series of aerial images were obtained by an airborne MS4100 multispectral imaging system on the cotton and soybean field. Ground hyperspectral data were acquired with a ground-based integration system at the same time. The Normalized Difference Vegetative Index(NDVI), Simple Ratio (SR), and Soil Adjusted Vegetation Index (SAVI) calculated from both systems were analyzed and compared. The information derived from aerial multispectral images has shown the potential to monitor the general growth status of crop field. The vegetation indices derived from both systems were significantly different (p-value was 0.073 at α= 0.1 level) at the early growing stage of crops. The correlation coefficients of the image NDVI and ground
NDVI were 0.3029 for soybean field and 0.338 for cotton field. SAVI and SR were not correlated.
Keywords: airborne multispectral image, hyperspectral reflectance, vegetation index, remote sensing, crop growth condition
DOI: 10.3965/j.issn.1934-6344.2009.03.033-040


Citation: H Zhang, Y Lan, R Lacey, W C Hoffmann, Y Huang. Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data. Int J Agric & Biol Eng, 2009; 2(3): 33

Author Biography

Y. Lan, Agricultural Engineer, USDA-ARS-SPARC-APMRU

Yubin Lan, Ph.D., Agricultural Engineer USDA-ARS-SPARC-APMRU 2771 F&B Road College Station, TX 77845 Email: yubin.lan@ars.usda.gov Tel: (979)260-3759 Fax:(979)260-9386

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Published

2009-09-30

How to Cite

Zhang, H., Lan, Y., Lacey, R., Hoffmann, W. C., & Huang, Y. (2009). Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data. International Journal of Agricultural and Biological Engineering, 2(3), 33–40. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/171

Issue

Vol. 2 No. 3 (2009): IJABE

Section

Information Technology, Sensors and Control Systems

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