A number of platforms are available for the sensing of crop conditions. They vary from proximal (tractor-mounted) to satellites orbiting the Earth. A lot of interest has recently emerged from the access to unmanned aerial vehicles (UAVs) or drones that are able to carry sensors payloads providing data at very high spatial resolution. This study aims at comparing the performance of a UAV and satellite imagery acquired over a corn nitrogen response trial set-up. The nitrogen (N) response trial consisted of two fields (one loam, one clay) and two sowing dates at the L’Acadie experimental farm of Agriculture and Agri-Food Canada in the Montérégie region of Quebec, Canada. Eight unreplicated N treatment rates (from 0 to 200 kg N ha^-1) were applied, with our without irrigation, in order to create a gradient of crop development stages and N status at the time of imagery acquisition. A Pleiades-1 satellite imagery acquisition was performed on July 8^th, 2013. The image presented panchromatic (0.5 m; 470 to 830 nm) and multispectral (2 m, R+G+B+NIR; 430 to 940 nm) features. Four days later, on July 11^th, 2013, an image was acquired with a UAV responder (with object and path GPS tracking) carrying a Mini-MCA (Tetracam Inc, Chatsworth, CA) payload (6 bands multispectral (R+G+B+NIR+RedEdge1+RedEdge2; 450 to 850 nm). The CCD counted 1.3 megapixels with a 8 bit unsigned radiometric precision. The UAV was operated by ING Robotic Aviation (Sherbrooke, Quebec, Canada). On the day of UAV imagery acquisition, a ground-truthing campaign was performed. Leaf area index (LAI), chlorophyllmeter (SPAD), destructive biomass data were measured on 96 points. The images were subjected to radiometric and geometrical corrections and transformed to reflectance data. Soil-adjusted (SAVI) and normalized difference (NDVI) vegetation indices (VIs) were calculated for both the Pleiades-1 and UAV images and matched to the ground-truthing database to perform the statistical comparisons. Relationships were established between VIs and the LAI, SPAD and biomass biophysical descriptors measured on the ground for both the satellite and the UAV imagery. Results will be discussed in terms of the potential value of the higher spatial resolution provided by the UAV.