Post by simranratry20244 on Feb 12, 2024 0:51:37 GMT -6
In recent decades, satellite images have allowed us to monitor and study a wide range of natural and human phenomena , such as climate, agriculture, deforestation, urbanization and pollution, among others. In addition, they have been a key tool for planning and decision-making in various areas, such as natural resource management, urban planning, prevention and response to natural disasters, national security and public health. Programs such as Landsat , run by the United States government together with NASA, have put satellites into orbit since 1972, and Copernicus , launched by the European Commission and the European Space Agency (ESA) in 2014, have made images available to companies and scientists. satellites of the planet.
In fact, both programs currently have web pages where anyone can access this data. It is not difficult to imagine that, in combination with artificial intelligence (AI), this large amount of data provided by satellites can be used to create solutions that can be of great help to both companies and government entities. In this post, we will see how Google Earth Engine can be a good tool for this. AI applications with Colombia Telemarketing Data satellite images The application of machine learning and deep learning techniques based on satellite images allows us to create predictive models for a wide variety of applications such as: Detection of changes on the earth's surface . Satellite image data is processed to monitor changes in the Earth's surface, such as deforestation and urbanization. Artificial intelligence is used to analyze this data and build models that predict future changes. Land Cover Analysis . Using satellite images and deep learning models such as convolutional networks, models can be created to automatically cldonkeyify different types of land cover , such as forests, urban areas, and bodies of water. Crop analysis and yield prediction.
In this case, satellite images are used to monitor crop growth, with calculations such as NDVI (vegetation index). They, through artificial intelligence models, allow us to predict the yield of the harvest. Forest fire detection . Here satellite images are used to detect forest fires, and AI can analyze them and predict the spread of the fire. But how are these large amounts of satellite data handled? One of the tools that stands out the most is Google Earth Engine. Processing satellite images with Google Earth Engine Google Earth Engine is a cloud computing platform for satellite image processing developed since 2010 by Google. It is one of the most comprehensive tools currently available, allowing users to explore, visualize and analyze multiple catalogs with large amounts of satellite imagery (includes Landsat and Copernicus) and other geospatial data. In this way, researchers and companies can carry out studies and analyzes on the earth's surface with a minimum resolution of 10 meters per pixel. Specifically, with Google Earth Engine, users can access a library of more than 30 years of high-resolution satellite images and millions of data points, as well as a wide range of analysis tools to investigate environmental trends, monitor change and model future scenarios.