leafmealone-london-upstairsTriggered by the NASA paper, 'Ozone-Induced Foliar Injury', LEAFMEALONE LONDON UPSTAIRS is a project with a formation of analytic formulas that are applied to leaf pictures, input via smart phone cameras, to deduce whether they can be categorized as ozone damaged. The leaf pictures, crowd sourced by interested parties, will then be stored with additional metadata such as houry local ozone readings, time, weather and geolocation and returned to the provider. The app will apply a series of algorithms aimed at automating the detection of ozone air pollution..
This project is solving the Leaf Me Alone challenge. Description
Syndromes to be factored into the metadata analytics : Is it a bright sunny day? Are there high temperatures? April -September in the Northern Hemisphere? Is it a hot, dry year? Is there diminished visibility? Is there mountainous terrain? Is there radiational or thermal inversions? Is there tropospheric ozone regional “hotspot”? low pollution controls country i.e. China and India Smog occurs faster and reaches higher wet, cool year, ozone n be greatly reduced injury to the plants Files with multiple layers stitch together with multiple images multiple pages. The page templates allow lays of transparencies applied to images as layer masks and produce a layered PDF with one composite layer in imagemagick.
License: Academic Free License 3.0 (AFL-3.0)
Source Code/Project URL: http://github.com/san-bil/spaceapps