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Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001, eLife digest Most plants absorb water and nutrients from the soil via structures called roots. The shape, size, and structure of a plant's root system can change over its lifetime as the plant responds to changes in their local environment. For example, if water is scarce, a plant may develop a very deep root system that is more efficient at capturing water. Understanding how root systems respond to environmental cues may help us to identify the genes and processes involved. In this study, Rellán-Álvarez et al. report a new live-imaging platform for analyzing root architecture and its regulation. This platform is called Growth and Luminescence Observatory for Roots (or GLO-Roots for short) and uses ‘luminescent’ markers that allow growing roots to be visualized when plants are grown in thin, soil-filled, transparent pots. GLO-Roots can track the growth of the plant roots as well as the activity of genes that respond to environmental stress. Rellán-Álvarez et al. developed a software tool called GLO-RIA (GLO-Roots Image Analysis) to analyze the resulting images. GLO-RIA performs several different types of image analysis, including one that detects the position, length, and direction of roots, as well as their shape and depth. Rellán-Álvarez et al. tested the GLO-Roots techniques in various ways, for example, by analyzing the effects that different conditions have on the growth of the roots of the model plant known as Arabidopsis thaliana. Depriving the plants of a nutrient called phosphorous caused the roots to grow more horizontally than when phosphorus is plentiful, presumably to allow the plants to expand their search for phosphate in the upper layers of the soil, where this nutrient is usually more abundant. On the other hand, a shortage of water caused the roots to grow more vertically to access water stored deeper in the soil. GLO-Roots can also be used to measure the water content of soil at different depths and how this influences the architecture of the root. Further experiments on tomato plants and a grass species called Brachypodium distachyon revealed the different architectures of their root systems. Rellán-Álvarez et al. propose that this system could be used to study the roots of other plant species in a variety of environmental conditions. This will provide a more detailed understanding of the ways that different plants adapt in response to changes in their environment. DOI: http://dx.doi.org/10.7554/eLife.07597.002