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Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

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Elliott, L.M., Mason, D. C., Allainguillaume, J. and Wilkinson, M.J. (2009) Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops. Journal of Applied Remote Sensing, 3. 033562 . ISSN 1931-3195

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To link to this article DOI: 10.1117/1.3269615

Abstract/Summary

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Environmental Systems Science Centre
ID Code:1644
Uncontrolled Keywords:agriculture; classification; ecology; sub-pixel OILSEED RAPE; MULTISPECTRAL DATA; WILD RELATIVES; NATIONAL-SCALE; NAPUS L.; B-RAPA; TRANSFORMATION; HYBRIDIZATION; MOVEMENT
Publisher:Society of Photo-optical Instrumentation Engineers (SPIE)
Publisher Statement:Copyright 2009 (year) Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

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