1 / 15

"Remote Sensing to Detect Mite Infestations in Stone Fruit Orchards"

"Remote Sensing to Detect Mite Infestations in Stone Fruit Orchards". Adam Hale and Minghua Zhang Land, Air and Water Resources – UC Davis 2/14/07. Project Objectives. Use aerial images to detect and track mite infestations in stone fruit orchards during the growing season

naoko
Download Presentation

"Remote Sensing to Detect Mite Infestations in Stone Fruit Orchards"

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 Detect Mite Infestations in Stone Fruit Orchards" Adam Hale and Minghua Zhang Land, Air and Water Resources – UC Davis 2/14/07

  2. Project Objectives • Use aerial images to detect and track mite infestations in stone fruit orchards during the growing season • Investigate the possibility of saving growers money by lowering monitoring costs

  3. Project Tasks Collection of Data - Field Level Data - Aerial Images Analysis of Data

  4. Field Data Gathered • Noted the level of mites on selected trees • Based upon the UC IPM for stone fruit guide • Used a remote spectrometer to collect reflectance data

  5. Mite Ratings Low(1-20%) - an occasional mite on occasional leaf; hard to find. Low/Moderate (21-39%) - mites easier to find but no colonies or webbing and few eggs. Moderate(40-60%) - some leaves without mites, other leaves with small colonies; eggs easy to find but very little webbing. Moderate/High (61-79%) - mites on most leaves, colonies with eggs, and webbing on some leaves. High (80-100%) - lots of mites on most leaves; eggs and webbing abundant. UC ANR Integrated Pest Management for Stone Fruits, Publication 3389. 1999

  6. Spectral Reflectance Curve

  7. N Aerial Images – Kearney Ag. Center Manning Avenue True Color Image Color Infrared Image Study Area

  8. Frequency of Observed Mite Rating

  9. Mite Level 7/21/06 - Images

  10. 8/4/06 - Images Mite Level

  11. Mite Level 8/12/06 - Images

  12. Mite Level 8/21/06 - Images

  13. Results • Spectrometer shows that there is a difference between healthy and unhealthy trees • Image analysis shows that there is a possibility to use remote sensing to detect mite infestations

  14. Economics • While this aspect of the project needs further research this study hopes to determine: • If there is a savings on monitoring costs • Image analysis vs Field scouts • If remote sensing analysis can be quicker and more efficient at observing mite outbreaks than current methods

  15. Feedback • Is the mite rating scale appropriate? • What is your threshold limit? • Do you think this method of mite detection would be useful in your field? • Would you be willing to participate during the coming season?

More Related