Submitted to: Office of National Drug Control Policy Proceedings
Publication Type: Proceedings/Symposium
Publication Acceptance Date: July 11, 2003
Publication Date: October 6, 2003
Citation: WALTHALL, C.L., DAUGHTRY, C.S., VANDERBILT, V., HIGGINS, M., BOBBE, T., LYDON, J., KAUL, M.N. 2003. WHAT DO WE KNOW ABOUT THE SPECTRAL SIGNATURES OF ILLEGAL CANNABIS CULTIVATION? PROCEEDINGS OF THE OFFICE OF NATIONAL DRUG CONTROL POLICY PROCEEDINGS.
Interpretive Summary: Successful detection of outdoor illegal Cannabis cultivation with remote sensing would be of considerable help to law enforcement agencies. It is assumed that remote sensing will rely on the spectral signatures of Cannabis plant canopies as the primary indicator. The spectral reflectance of Cannabis was examined using laboratory, field and airborne measurements. Results thus far include: 1) leaf and canopy spectral reflectance of Cannabis exhibit characteristics of other green plants, 2) nadir spectral signatures do not have stable, unique absorption features suitable for a reference signature, 3) the "emerald green" (blue-green) color of Cannabis results from specular reflectance of blue sky light and small particle scattering from microscopic structures on the surface of Cannabis leaves, 4) spectral contrast between Cannabis and other plant canopies appears most significant for green, red edge and short wave infrared wavelengths, 5) spectral contrasts between Cannabis and tree species appear greater than spectral differences with other herbaceous species, 6) isolation of Cannabis canopy spectral signatures during land cover classification may be difficult using visible-near infrared systems, and 7) researchers investigating detection technologies must be kept aware of the trends of growers to conceal sites. Analysis of the essential elements of information associated with illegal Cannabis cultivation offers other possibilities for detection with remote sensing. Ultimately, remote sensing will be most effective when used with a probability-of-occurrence/Cannabis cultivation site prediction model from the Counter Drug ¿ Geographical Regional Assessment Sensor System (CD-GRASS).