EO / GEOINT Analyst

Observational Grammar OG-001 Observational Grammar (OG) is the idea that sensors — satellites, radar, spectrometers, thermal cameras — can form a language of evidence about reality that operates independently of human bias, market incentives, or bureaucratic approval chains. Just as grammar gives structure to language, OG gives structure to what instruments can claim about the physical world. It is M33's foundational concept: build systems that let reality set the table, then let markets and decisions work within those constraints, rather than the other way around. SAR Fundamentals SEN-005 Synthetic Aperture Radar (SAR) is a radar imaging system carried on aircraft or satellites that creates high-resolution images of the Earth's surface by emitting microwave pulses and measuring what bounces back. Unlike optical sensors that rely on sunlight, SAR generates its own illumination — so it works at night. Unlike optical sensors that are blocked by clouds, SAR's microwave frequencies pass through clouds, rain, and smoke. SAR does not see color or reflected light. It sees surface roughness, moisture content, and geometric structure. This makes it essential for flood mapping, deforestation monitoring, ground deformation measurement, and any application where persistent, all-weather observation is required. Sentinel-2 SAT-002 Sentinel-2 is a pair of optical satellites operated by the European Space Agency (ESA) as part of the Copernicus Earth observation programme. Each satellite carries a Multispectral Instrument (MSI) that captures images in 13 spectral bands — from visible light through near-infrared to shortwave infrared — at resolutions of 10, 20, and 60 meters. With two satellites in orbit (Sentinel-2A and 2B), the combined revisit time is approximately 5 days at the equator and 2-3 days at mid-latitudes. The data is free and open access. Sentinel-2 is the most widely used optical satellite for land monitoring, agriculture, forestry, water resources, and disaster response worldwide. Analysis-Ready Data DAT-004 Analysis-Ready Data (ARD) is satellite imagery that has been processed to a standard where it can be used directly for analysis without additional preprocessing. This means the image has been geometrically corrected (pixels are in the right geographic locations), radiometrically calibrated (pixel values represent meaningful physical quantities like surface reflectance rather than arbitrary digital numbers), atmospherically corrected (the atmosphere's distortion has been removed), and often cloud-masked (unusable pixels are flagged). ARD is the difference between receiving raw ingredients and receiving a prepared, measured, recipe-ready mise en place. Data Provenance SEC-001 Data provenance is the complete, verifiable record of where a piece of data came from, every transformation it underwent, and who or what performed those transformations. In satellite imagery and remote sensing, provenance is not a nice-to-have audit trail — it is the difference between evidence and hearsay.