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Satellite-aided Field Forestry Applications

Imagery Solutions

Aerial photographs, either color infrared or black and white, that have been digitized and rectified are one option. While they offer high resolution and may be quite recent, the cost of rectification can be significant. A more affordable option is a digital orthophoto (DOQ) which has already been rectified. Although DOQs are usually only available in black and white, they are widely available and GIS-ready. However, in Minnesota, most DOQs date back to the early 1990s.

Aerial images acquired by digital cameras or other multispectral electronic sensors are a third option. They are already in digital format (although they may or may not be rectified), and the better systems include several spectral bands in the visible and the near infrared. At this time, the cost of this option may be beyond what can be justified for many forestry applications.

A fourth option is digital, high-resolution satellite imagery which is now approaching the spatial resolution of digital photographs. It provides four bands of multispectral imagery in a GIS-compatible format. Generally, it can be acquired within a short time, making it a good option when up-to-date information is needed. However, current costs of about $3,000 for a township size area may preclude its use. For more information on high-resolution satellite imagery, see Fact Sheet 3: Using High-Resolution Satellite Imagery to Monitor Natural Resources.

When multispectral imagery (with red and near infrared spectral bands ) from digital cameras or satellite sensing systems is available, the normalized difference vegetation index can be a useful image transformation. NDVI is sensitive to the amount of green vegetation and enhances differences between vegetation and other cover types.

Sample satellite imagery products

Black & White
Color
Color Infrared
NDVI
PC

Forest Regeneration Survey >>

Satellite-aided Field Forestry Applications

k-Nearest Neighbor (kNN)

Forest Disturbance Mapping

Oak Wilt Detection

Urban Forest Mapping

TCMA Classification Comparison: MLC vs. kNN

In this section...

Hardware Solutions

Software Solutions

Imagery Solutions

Forest Regeneration Surveys

Corner Location and Line Running