Developers are increasingly working with multi-spectral imagery, which enables applications to “see” beyond the visible RGB spectrum. Google’s Gemini models revolutionize access to this technology, eliminating the need for complex custom models. Multi-spectral sensors capture various electromagnetic bands, including near-infrared (NIR) and short-wave infrared (SWIR), providing vital insights into vegetation health, water detection, and material identification. By creating “false-color composite” images that map invisible wavelengths onto RGB channels, developers can leverage Gemini for remote sensing tasks more easily. This process involves selecting key spectral bands, normalizing data, and prompting the model with contextual information. The Gemini 2.5 model demonstrates its efficacy in accurate land cover classification by utilizing these additional inputs. This innovation dramatically reduces the barriers to analyzing satellite data, empowering developers in precision agriculture, urban planning, and environmental monitoring. Start exploring public satellite data and teach your applications to perceive the world with enhanced capabilities.
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