Author
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DU, QIAN - MS STATE UNIV, MS |
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FRENCH, J. VICTOR - TX A&M UNIV., CITRUS CTR |
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SKARIA, MANI - TX A&M UNIV., CITRUS CTR |
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YANG, CHENGHAI - TX A&M UNIV., EXPT STATIO |
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Everitt, James |
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Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Proceedings Publication Acceptance Date: 6/20/2004 Publication Date: 10/30/2004 Citation: Du, Q., French, J., Skaria, M., Yang, C., Everitt, J.H. 2004. Citrus pest stress monitoring using airborne hyperspectral imagery. International Geoscience and Remote Sensing Symposium Proceedings. Piscataway, New Jersey. 2004 CD-ROM. Interpretive Summary: Hyperspectral imagery has the potential to provide more accurate detection and identification. This research was designed to evaluate airborne hyperspectral imagery for detecting citrus pest stress conditions. Preliminary results showed that hyperspectral imagery combined with advanced analysis techniques was able to detect and quantify the severity of the stress. Therefore, hyperspectral data can be a useful data source for citrus pest management. Technical Abstract: This paper reports on the preliminary results using airborne remote sensing images for citrus pest stress monitoring in the Lower Rio Grande Valley of South Texas. In order to accommodate the in-field spectral variability, unsupervised classification is applied. In addition, fully constrained linear unmixing is performed at the sub-pixel level to quantify the stress severity. The results using multispectral and hyperspectral images are compared, which demonstrate the potential improvement that hyperspectral imaging can provide. In conjunction with variable rate technology in pesticide adoption, tree-specific stress information derived from remote sensing imagery will support a well-targeted pest management plan for cost effectiveness and environmental friendliness |
