Unit 09 - Model tuning

Let’s improve our NDVI model created in Unit 08 - Modeler. The model operates in a current computation region, it would be better to define region based on user input, eg. by city area. Then NDVI would be computed only within user defined area.

NDVI values range from +1.0 to -1.0. Areas of barren rock, sand, or snow usually show very low NDVI values (for example, 0.1 or less). Sparse vegetation such as shrubs and grasslands or senescing crops may result in moderate NDVI values (approximately 0.2 to 0.5). High NDVI values (approximately 0.6 to 0.9) correspond to dense vegetation such as that found in temperate and tropical forests or crops at their peak growth stage. Let’s classify NDVI into 3 major classes:

  • Class 1: from -1.0 to 0.2
  • Class 2: from 0.2 to 0.6
  • Class 3: from 0.6 to 1.0

The desired output will be vector map with NDVI classes. Let’s also eliminate too small areas.

From GRASS perspective computation will be performed by several steps/modules:

  1. Erase cloud mask from input city region (v.overlay: not operator)
  2. Set computation region based on modified input city region (g.region)
  3. Set mask (r.mask)
  4. Compute NDVI values (i.vi)
  5. Reclassify NDVI values into classes (r.recode)
  6. Set nice color table for raster map classes (r.colors)
  7. Convert raster classes into vector areas (r.to.vect)
  8. Remove small areas (join them with adjacent areas by v.clean)

New modules can be added to the existing model in standard way by grass-module-add Add command (GRASS module) to the model. New commands are added to the end of a computation workflow which is not desired in this case. Good news: we can reorder commands (items) in Items tab.