Advanced hyperspectral and thermal imaging technologies coupled to artificial intelligence methods are currently proposed as a new revolution in remote sensing for physiological condition assessment. Nevertheless, the understanding of these "signals" is critical, particularly because they are the result of photon-vegetation interactions well studied since the last century. Progress made in the last 20 years in the context of plant trait retrievals using hyperspectral and thermal imaging methods will be discussed, presenting advances and current limitations for the early -pre-visual- detection of stress.

Prof. Pablo J.  Zarco-Tejada is jointly appointed between the School of Agriculture and the Melbourne School of Engineering, University of Melbourne. Leader of the HyperSens Laboratory, he is primarily focusing on remote sensing, precision agriculture and vegetation stress detection using hyperspectral and thermal images acquired by manned and unmanned aircraft systems. He is MSc in Remote Sensing (UK), PhD in Earth and Space Science (Canada), later appointed as Faculty member at the University of California, Davis, USA, and former Director of the Institute for Sustainable Agriculture (IAS-CSIC, Spain). Since 2012, he has been Senior Scientist at the Joint Research Centre (JRC) of the European Commission leading the development of algorithms for the assessment of physiological condition through thermal and hyperspectral remote sensing imagery. Author of over a hundred papers published in international journals, he is Associate Editor of Remote Sensing of Environment (RSE), the European Journal of Agronomy (EJA), Remote Sensing (RS), and has been recipient of awards during his scientific career in Spain, United Kingdom and Canada.