Vegetation Studies

One of the major applications for remote sensing technology is vegetation studies. Remote sensing using a field spectroradiometer can be applied to:

  • Management of land and water resources
  • Disaster assessment
  • Yield production
  • Canopy studies
  • Crop yield forecasting
  • Vegetation identification
  • Crop condition assessment

The cells in plant leaves effectively scatter light because of the high contrast in the index of refraction between water-rich cell contents and inter-cellular air spaces. Plants that are engaged in photosynthesis use blue and red light as energy sources. They reflect little light back from these wavelengths. The underlying principle for using NIR is that plants with different nutrient levels reflect light differently in specific wavelengths.

Many researchers are using a portable agricultural spectroradiometer such as the PSR+ to study vegetation in situ and confirm, modify, and better understand hyperspectral remote sensing data from satellites such as Landsat 8, or plane flyovers.

Because it is fast and non-destructive, remote sensing is a popular technology for reliably measuring biophysical and biochemical vegetation variables. By capturing and analyzing data such as leaf area index (LAI) and canopy chlorophyll content, vegetation can be modeled and compared to vegetation indices to reveal health, stress, infestation, pollution, climate changes, drought, fertilization, and a range of other conditions.

All SPECTRAL EVOLUTION portable spectroradiometers and spectrometers include DARWin SP Data Acquisition software with pull-down menu access to the USGS spectral library for vegetation and nineteen vegetation indices. These include NDVI (Normalized Difference Vegetation Index), SR (Simple Ratio), SAVI (Soil Adjusted Vegetation Index), ARVI (Atmospherically Resistant Vegetation Index), and more.

In addition, our EZ-ID sample identification software with Custom Library Builder module allows you to match target scans against a known sample in a commercial library or you can build your own custom spectral library.

Vegetation Indices ARVI, EVI, IPVI, PRI, WBI, PAR, GRVI, FVI, Red/green, Green NDVI, MSAVI2, Sum Green, NDVI705, NDWI, NDNI, and CCI.