WinSCANOPY Pro can acquire and analyse hemispherical (180° FOV) or regular (small or medium FOV) multispectral images containing NIR and Visible data channels. It can compute the NDVI index and other spectral based vegetation indices.
WinSCANOPY Pro can read the NIR + Vis images produced by the multispectral NDVI camera and computes the spectral index [NDVI, ENDVI, EVI…] values for each image pixels. The whole image can be analysed or specific regions of it (circular regions such as the 180 FOV hemisphere or rectangular regions). It also computes total, average, minimum 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 in the image.
Different false color schemes are available to display and visualize the image’s NDVI or color index values.
WinSCANOPY Pro can compute six spectral indices (ENDVI, EVI2, MSAVI, WDRVI, Green Chlorophyll from NDVI cameras) and other Color based indexes such as Greenness (from color cameras). User can also create their own index 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 program
To study urban vegetation, it is sometime 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 sometimes 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.
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