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Using Google Earth Engine for Geology
Google Earth Engine (GEE) is a cloud-based geospatial analysis platform. It combines a multi-petabyte catalogue of satellite imagery and geospatial
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GIS and Remote Sensing Consultants in Kenya
Almost every sector in Kenya now depends on location-based information. Water engineers need groundwater potential maps. Mining and exploration companies
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Best Free GIS Software for Geoscience
Many geologists assume that serious spatial work requires a costly commercial licence. That was largely true twenty years ago. Today,
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Remote Sensing for Geology in Kenya
Satellites circle the Earth every day, capturing images that geologists can use to study landscapes far larger than any field
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Remote Sensing for Mineral Exploration
Exploration is a numbers game with a high failure rate. The cost of walking, sampling, and drilling over a large
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Stereonet Analysis in Structural Geology
A stereonet is a graphical method of representing three-dimensional orientation data on a two-dimensional circle. Imagine a transparent hemisphere, like
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Machine Learning for Mineral Prospectivity Mapping
Mineral prospectivity mapping (MPM) is the process of combining multiple spatial datasets to produce a map showing how likely each
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GIS for Geologists: Practical Workflows
Geology is a spatial science. Rocks, faults, soils, drill holes, samples, boreholes and mineral occurrences all have a location, and
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Remote Sensing for Mineral Exploration
Mineral exploration begins with a simple problem: how do you decide where to spend limited money on ground work, drilling
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How AI Is Changing Geological Interpretation
GeoAI (geospatial artificial intelligence) is the application of artificial intelligence, particularly machine learning and deep learning, to spatial and earth
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GeoAI in Disaster Risk Management: Predicting Landslides, Floods, and Erosion
Natural hazards rarely strike without warning signs — the challenge has always been recognizing those signs across large, complex landscapes
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What Is GeoAI? How Machine Learning Is Changing Geoscience
Geoscience has always been a data-heavy discipline — satellite imagery, drill logs, geophysical surveys, geochemical assays, and terrain models generate
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