Vegetation Satellite Imagery

A year ago i wrote an article on a similar concept called satellite imagery analysis with python where we examined the vegetation cover of a region with the help of satellite data.

Vegetation satellite imagery. Satellite maps of vegetation show the density of plant growth over the entire globe. The data collected with both technologies is commonly used for the classification and mapping of vegetation being cheaper and less time consuming than manual field surveys. The measurement of vegetation signatures using remote sensing sources has become a critical way to measure the effects of regional and global scale drought and agricultural production. These images are commonly used to assess and monitor vegetation over very large areas a task that would be extremely difficult using on the ground sampling techniques.

Aeroview software processes both satellite and multispectral imagery to provide precise per tree health analytics and highlight problem areas that could otherwise go. The most common measurement is called the normalized difference vegetation index ndvi. The idea was to understand the concept of satellite imagery data and how it could be analyzed to investigate real world environmental and humanitarian challenges. There are several global regional scale systems in place that report on drought food shortages and forecasting crop yields including the usgs famine early warning systems network fews net and group on earth observations geo global agricultural monitoring geoglam crop monitor.

The national aeronautics and space administration nasa operates satellites capable of photographing the entire surface of the earth every one or two days. Measuring vegetation from satellite imagery with ndvi.