Goto

Collaborating Authors

 geographical magazine


Mapping the world's fungal networks with machine learning - Geographical Magazine

#artificialintelligence

Life is underpinned by fungi. Fungal filaments extend through the soil in networks of mycelia, but we know relatively little about them and questions abound, including where on Earth they are and in what diversity and abundance. Vast and powerful, mycelial networks sequester carbon, hold soils together and supply as much as 80 per cent of all nutrients to terrestrial plants. In just one hectare of grassland, the extent of fungi is equivalent to around 12 million times the length of the Amazon River. But just like the distributions of plant species, those of fungi are almost certainly shifting in response to climate change.

  Industry: Government (0.33)

Deep learning identifies more than 1.8 billion trees in the Sahara, Sahel and sub-humid zones - Geographical Magazine

#artificialintelligence

A combination of high-resolution satellite imaging and'deep learning' has identified more than 1.8 billion trees across the West African Sahara, Sahel and sub-humid zone – significantly more trees than were previously thought to exist in the region. The collaboration between NASA and several geoscience departments across the world used 11,128 satellite images from four satellites to count individual trees across 1.3 million square kilometres. The deep-learning approach has, for the first time, allowed researchers to identify individual trees across the dryland expanse. Because of the absence of closed canopies, many parts of the Sahara and the Sahel have previously been mapped with zero per cent tree cover. 'You need high-resolution satellite images to be able to detect individual trees and not just to make estimations based on identified areas of canopy cover,' says Martin Brandt from the University of Copenhagen.


Artificial intelligence to predict water scarcity conflicts - Geographical Magazine

#artificialintelligence

Researchers from the Netherlands-based Water, Peace and Security partnership (WPS) have announced the creation of a global forecasting tool that can predict where conflicts arising from water insecurity are most likely to break out. The system uses artificial intelligence to create patterns from a wide rage of geographical and socio-economic data and can identify potential conflict'hotspots' up to a year in advance. Keep an eye on the world Get Geographical's latest news delivered straight to your inbox every Friday, plus a collection of free eBooks on the subjects that matter to you! Susanne Schmeier, a senior lecturer in water law and diplomacy at the HE Delft Institute for Water Education, which leads the WPS, explains that predicting these types of conflicts isn't as simple as it might first appear. 'There is increasingly a discourse that links water scarcity and security with conflict instability,' she says, 'but at the same time our understanding is quite limited as to what actually links them.' It isn't simply a case of conflicts increasing every time a water security incident occurs.