Close-range spectral and active sensors and machine learning for Digital Agriculture

In the forthcoming years, agriculture will face challenges that require the assimilation and development of new technologies to increase productivity sustainably. Incorporating Digital Agriculture is one of the ways to face these challenges, including the use of close-range Remote Sensing and Artificial Intelligence (AI) techniques. In this special session, focus will be given in some experiences with multispectral, hyperspectral and laser scanning sensors collected by close-range aerial and terrestrial platforms with cultures of interest. The acquisition of high-resolution data from aerial and terrestrial perspectives allows the generation of high-resolution three-dimensional information, enabling the extraction of numerous variables of interest. These variables can be used to feed machine learning algorithms to generate information of interest for Agriculture, such as detection of pests, pathogens, nutritional deficiencies, prediction of production and soil quality.