WinSCANOPY: Canopy Structure and Solar Radiation Analysis
Image Analysis for Plant Science
Regent Instruments Inc. since 1991




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is an extended version of WinSCANOPY Pro which can acquire and analyse hemispherical (180° FOV) or regular (small or medium FOV) NIR + Vis images. From them it can compute NDVI and other color based indexes depending upon which camera is used.

The Hardware

When selecting the NDVI option at purchase time, the conventional color camera (with 3 color channels, RGB for Red green and Blue) is replaced by one which has a NIR (Near Infra Red) channel and two visible channels (G and B). The camera comes with a high quality fish-eye lens (for 180 FOV hemispherical NDVI analyses which can be used with or without the OMount) which can be replaced by lower FOV lenses (which cannot be used with the OMount). Operation is simple, like an ordinary camera.

Note about the NDVI cameras: They cannot produce regular color images. This is due to the fact that one of its color channels is replaced by the NIR channel. If you want both NDVI and color images, two systems must be purchased (one with the NDVI option and one without).

Note about Color indexes (Greenness,…): To compute such indexes a regular color camera is required, it cannot be done with the NDVI camera.

The Software

WinSCANOPY Pro NDVI takes the NIR + Vis images produced by the NDVI camera and computes the NDVI values for each image pixels. The whole image can be analysed this way or specific regions of it (circular regions such as the 180 FOV hemisphere or rectangular regions). It also computes average, min and maximum NDVI values (and eventually other statistic values based on user demands). The operator can also browse the image and display NDVI values at specific mouse cursor positions of interest in the image.

Different false color schemes are available to visually display the image’s NDVI or color index values.

WinSCANOPY Pro NDVI can also compute ENDVI index (Enhanced NDVI, from NDVI cameras) and other Color indexes such as Greenness (from color cameras). User can also create their own indexes by combining RGB, NIR and HSI (Hue, Saturation and Intensity) channels values.

Images can be used as is or calibrated against uniform reflectance (over the spectrum) targets for greater precision.

The computed index images (NDVI, ENDVI, Greenness…) can be exported for analysis, documenting, printing or review in other programs.


To study urban vegetation, most of the time it is easier to identify and separate it from surrounding buildings and objects using the NIR channel*1. Also in forestry and urban environement application it is possible to get three levels of pixels classification (sky, leaves and branches) and compute the branch area index separately from the leaf area index*2.

*1 Osmond P. Application of Near-Infrared Hemispherical Photography to Estimate Leaf Area Index of Urban Vegetation., University of New South Wales, Sydney, Australia. The seventh International Conference on Urban Climate, 29 June - 3 July 2009, Yokohama, Japan

*2 Chapman L. Potential Applications of Near Infra-Red Hemispherical Imagery in Forest Environments. Agricultural and Forest Meteorology 143 (2007) 151-156.