"Fascinating Voids: Alexander von Humboldt and the Myth of Chimborazo"

When Alexander von Humboldt reached the village of Calpi in the Andes on 22 June 1802, he was greeted with reverence and enthusiasm. Triumphal arches adorned with cotton, cloth, and silver decorated his path. The natives performed a dance in festive dress. A singer praised the explorer's expedition, which had departed three years earlier from the Spanish port of La Coruña. Like Odysseus on the isle of the Phaeacians, the traveler listened to a local rhapsodist singing about his heroic deeds. Before his adventure ended, it had already spun a popular myth. This episode, which Humboldt recorded in his diary, occurred at a significant moment. One day later, the “Second Discoverer of America” rose to even greater fame on an excursion marking in more ways than one the climax of his enterprise. Humboldt set out to climb Chimborazo (6,310 m/20,702 ft.), the mountain then thought to be the highest in the world. He was accompanied by the French botanist Aimé Bonpland (1773–1858) and the Creole nobleman and future activist Carlos Montúfar (1780–1816), as well as native guides and assistants. They climbed to heights never reached before, setting a new record and catapulting Humboldt to fame on both continents.

Mapping material distribution in a heterogeneous sand tank by image analysis

Water flow and solute transport through soils are strongly influenced by the spatial arrangement of soil materials with different hydraulic and chemical properties. Knowing the specific or statistical arrangement of these materials is considered as a key toward improved predictions of solute transport. Our aim was to obtain two-dimensional material maps from photographs of exposed profiles. We developed a segmentation and classification procedure and applied it to the images of a very heterogeneous sand tank, which was used for a series of flow and transport experiments. The segmentation was based on thresholds of soil color, estimated from local median gray values, and of soil texture, estimated from local coefficients of variation of gray values. Important steps were the correction of inhomogeneous illumination and reflection, and the incorporation of prior knowledge in filters used to extract the image features and to smooth the results morphologically. We could check and confirm the success of our mapping by comparing the estimated with the designed sand distribution in the tank. The resulting material map was used later as input to model flow and transport through the sand tank. Similar segmentation procedures may be applied to any high-density raster data, including photographs or spectral scans of field profiles.