1 / 13

Remote Sensing to Estimate Chlorophyll Concentration Using Multi-Spectral Plant Reflectance

Remote Sensing to Estimate Chlorophyll Concentration Using Multi-Spectral Plant Reflectance. P. R. Weckler Asst. Professor M. L. Stone Regents Professor N. Maness Professor R. Jayasekara Research Engineer

betsy
Download Presentation

Remote Sensing to Estimate Chlorophyll Concentration Using Multi-Spectral Plant Reflectance

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Remote Sensing to Estimate Chlorophyll Concentration Using Multi-Spectral Plant Reflectance P. R. Weckler Asst. Professor M. L. Stone Regents Professor N. Maness Professor R. Jayasekara Research Engineer C. Jones Research Engineer

  2. Objective • Estimate Chlorophyll concentration using chlorophyll content and biomass

  3. Sensors • Passive Sensor - OSU Plant Reflectance sensor • Active Sensor - Patchen Weedseeker™ PHD 600 Sensor -Ntech Greenseeker™ Sensor • Multi-SpectralCamera

  4. Sensing Equipment

  5. Sensors

  6. Experimental Plots Spinach Plot with Reflectance Targets Vegetation Through Multi-spectral Camera

  7. Results

  8. Results

  9. Results

  10. Conclusions • The NDVI readings gathered by the handheld sensors and the multispectral camera were sensitive to changes in plant biomass and plant chlorophyll content in spinach. • This study reaffirmed the correlation between %VC and dry biomass found by Lukina et al. (1999, 2000) and Ter-Mikaelian and Parker (2000). • High correlation was observed between the %VC of the spinach as measured with digital imagery and the spinach biomass as measured in the laboratory (r2 = 0.73 to 0.98).

  11. Conclusions • The findings of Lukina et al. (1999, 2000) and Sembiring (1998) were also supported regarding NDVI readings producing a stronger estimate of chlorophyll content then of chlorophyll concentration. • NDVI derived from processing images from a multispectral camera correlated well with handheld sensor NDVI. • The multispectral camera provided accurate %VC information that correlated well with biomass results.

  12. Further Studies • Low correlations when predicting chlorophyll concentration from estimates of biomass and NDVI may suggest further investigation in following areas: - canopy stacking - background interference with sensors

  13. QUESTIONS? Acknowledgments Dr. Jerry Brusewitz Ted Kersten D. Chrz Bruce Bostian Oklahoma Vegetable Research Station,Bixby,Oklahoma

More Related