The red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional status. One of the most important advantages of the red-edge inflection point (REIP) , in contrary to common used vegetation indices (e.g., Normalized Difference Vegetation Index , NDVI) is its ability to identify differences among highly dense crops. However, the application of the REIP has been limited to the lack of suitable sensors that allow its retrieval at a spatial resolution appropriate for precision agriculture. A platform that is about to be launched and that will fill this gap is the Vegetation and Environmental New Micro Spacecraft (VENmS), with superspectral resolution of 11 different bands, four of them along the red-edge region and with spatial resolution of 5.3 m. The aim of the current study is to analyze the VENmS potential for LAI retrieval of wheat and potato using the REIP and other common vegetation indices. Data were acquired during two seasons for each crop. Canopy reflectance data was collected from 1.5 meters height using an Analytical Spectral Devices (ASD) Field Specâ Pro spectrometer. LAI data were collected immediately after the spectral measurements using a ceptometer (AccuPAR LP-80). The vegetation indices were calculated using both original ASD spectral resolution (narrow bands), as well as by VENmS resampled bands. Considering all the data together and the wheat alone, the REIP showed better relationship to LAI than NDVI (R2 values of 0.63 versus 0.44, and 0.86 versus 0.61, respectively). For all the studied cases, VENmS resampled indices showed the same level of accuracy when comparing it to narrow band indices. Based on these results, VENmS resampled superspectral data is as applicable as narrowband spectral data for predicting LAI of wheat and potato crops.
