Using GeoSpatial Data Analytics: A Friendly Guide to Estimate Population
April 19th, 2021

  A friendly introduction to remote sensing and how-to guide on handling and visualizing geospatial data using Rasterio and Folium. Applying all code on Uganda, Africa, by using WorldPop data. Authors:  Johnny Lau, Albert Um   Prerequisites ❌ Limited knowle

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Anomaly Detection on Mars  Using Deep Learning
March 28th, 2021

Anomaly detection on the surface of Mars has a few unique challenges. For example, finding publically available datasets like landing images, using deep convolutional networks and exploring the large variety of surface anomalies. Still, a team of 30+ engineers took on t

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Normalized Difference Vegetation Index — You Don’t Always Need Deep Learning for Satellite Imagery
March 21st, 2021

While looking for an ML solution to understand the relationship between climate change and forced displacement in Somalia, Deep Learning turned out to be non-resource-efficient. Instead, we used satellite imagery indices to understand image bands and the different combi

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7 Steps to Build a Quality Satellite Imagery Dataset for Agricultural Applications
March 14th, 2021

So, you have decided to use satellite imagery for agricultural purposes and prepare your own satellite imagery dataset? GREAT! You are in the right place.   By Jayasudan Munsamy, Alexander Epifanov, and Łukasz Murawski         Background This article

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Harnessing AI and Open Source Satellite Imagery to Address Global Problems
March 1st, 2021

Omdena successfully combines AI and ML methodologies with open source, low resolution satellite imagery to create actionable solutions for powerful insights.   Introduction Every day, millions of images are captured from space by an ever-growing number of satellite

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Crop Yield Prediction Using Deep Neural Networks and LSTM
February 28th, 2021

Crop yield prediction using deep neural networks to increase food security in Senegal, Africa. The case study covers leveraging vegetation indices with land cover satellite images from Google Earth Engine and applying deep learning models combined with ground truth data

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