How Spectral Resolution Works in Remote Sensing

Radiometric Resolution: The Power of Pixel Sensitivity! 🛰️✨ Ever wondered how satellites can tell the difference between light and “slightly lighter” areas on Earth? 👀 That’s the work of Radiometric Resolution! 🌍 Radiometric resolution refers to how finely a sensor can detect variations in energy (brightness or reflectance) coming from the Earth’s surface. 🎚️ Think of it like this: ✅A low radiometric resolution (8-bit) sensor can record 256 shades of brightness. ✅A high radiometric resolution (12-bit or 16-bit) sensor can record thousands of subtle shades, capturing finer details — like the difference between dry soil and slightly moist soil 🌾, or light vs. dense vegetation 🌳. In short, the higher the radiometric resolution, the more “sensitive” your satellite eyes become! 👁️🌈 #RemoteSensing #RadiometricResolution #SatelliteImagery #EarthObservation #GIS #GeospatialIntelligence #ClimateMonitoring #Geoinformatics

🚀 How real is real? This morning we pulled fresh satellite data—and what you’re seeing isn’t CGI. It’s live, raw signals from space. Take a look: Humberto and Imelda, locked in a Fujiwhara-type interaction, where Humberto’s stronger circulation is tugging Imelda away from the U.S. coastline. Instead of landfall, Imelda is being redirected. Meanwhile, rainfall/flooding risk is shifting — South Carolina is still in the mix, but the forecasts are trending toward a lower chance of extreme inland flooding. This is exactly the kind of event students using Signal Hunters get to explore firsthand. They don’t just see satellite imagery — they capture, decode, and analyze it in real time, translating space signals into weather insight. 👉 Learn more about the Signal Hunters STEM program here: https://lnkd.in/eJQfY9mG In the comments I’ll drop full-resolution RGB and infrared images so you can inspect the detail yourself. Let’s make science live, not just taught. #SpaceKitz #SignalHunters #SatelliteScience #STEM #WeatherSatellites #Fujiwhara #NOAA #RealData

Scientists have launched the first batch of a novel type of radiation monitor into the atmosphere as part of an innovative project to enhance space weather models. https://lnkd.in/eaWWEXky #weatherforecasting #data

Did you know that every time you use GPS on your phone or rely on banking systems, you're using geodesy without even realising it? This hidden science ensures GNSS satellites can provide accurate positioning and synchronised time across cities and continents. The geodetic supply chain is the invisible infrastructure that makes modern navigation possible. From mapping our roads to orienting Earth in space, this complex system works behind the scenes so you can simply open your phone and get where you need to go. Next time you use Uber or check your location, remember the incredible science making it all possible! #Geodesy #HiddenScience #EverydayTechnology #SouthAfricanScience #STEM

Knowing where satellites are, where they’re going, and when they’ll be there is table stakes for mission ops. Using public Two-Line Elements (TLEs) and an SGP-class orbit propagator, I built a MATLAB visualization that animates a GPS constellation in ECI, rotates Earth correctly via GMST, and computes line-of-sight (LoS) to a Norfolk, VA ground station with a 20° elevation mask. Visible spacecraft are connected in real time with green vectors; red markers show instantaneous ECI positions, full orbit information extracted from the TLE in blue. What this enables (ops view) -Pass prediction & contact planning: Who’s above 20° and for how long. -Antenna scheduling & handovers across sites. -Rapid what-ifs for outage recovery or site diversity. -Constellation health checks (e.g., Do we keep PDOP under target from this site and time?). Under the hood (tech notes) -Inputs: TLEs; time of interest in UTC. -Propagation: Mean motion from TLE + SGP-style Kepler solve. -Frames: ECI drawing; ECEF/ENU for elevation tests; WGS-84 station coordinates. -Earth: Textured ellipsoid, −GMST transform (ECEF→ECI), north-up texture. -LoS: ECI station vector recomputed each frame; elevation via ENU projection. What I’d add next - Higher-fidelity dynamics: J2/J3, drag, SRP, third body; switch to a full SGP4/SDP4 library or high-order numerical propagation for non-GNSS assets. - Terrain/obstruction masks: True horizon from DEMs for realistic elevation limits. - DOP metrics: Live GDOP/PDOP/HDOP heatmaps and “best 4” geometry picks. Multi-site ops: Site selection, diversity gain, and automatic pass scheduling. - Freshness guards: TLE age checks + auto-refresh; compare with broadcast ephemerides for GNSS. - Export & automation: Pass reports (CSV/ICS), REST hooks, and CI-packaged tooling for 24/7 operations. References: Fundamentals of Astrodynamics, 2nd Ed. (Bate, Mueller, White, Saylor) and standard SGP4 documentation. #spaceoperations #astrodynamics #MATLAB #TLE #SGP4 #GNSS #GPS #ECI #ECEF #groundstation #visualization #SSA #aerospace #aerospaceengineering

Software architecture for processing data from a large sensor array The development of the software architecture required for processing the multiple measurement parameters from a large array of positioning sensors in a complex control and monitoring system. The case study employed is that of the inductive edge sensors (LVDT) used for alignment of the segmented primary mirror of a large astronomical telescope. The purpose of this document is to highlight the methods used for the creation and optimisation of large data structures, the processing and filtering of the data using multithreaded tasks whilst maintaining data integrity, and the data exchange methods between subsystems for integration into a global control system. The process is based on that undertaken by the author whilst developing the closed loop alignment control software for the 91 segment primary mirror array of the Southern African Large Telescope. #SALT #LabVIEW #mirroralignment #LVDT #inductivesensors #actuators

Geospatial Technologies essential keywords, daily Tips 🌎 : Keyword : Hyperspectral Imagery Category :Key Concepts in Remote Sensing **Hyperspectral Imagery** 🌐🔍 Hyperspectral imagery refers to the collection and processing of data from the visible, near-infrared, and short-wave infrared parts of the electromagnetic spectrum. 🌌 This type of imagery captures the reflected radiation from the Earth's surface at hundreds to thousands of narrow spectral bands, allowing for a higher spectral resolution than traditional multispectral or panchromatic imaging. 📈 By analyzing the spectral signatures of various materials, hyperspectral imagery enables the detection and identification of subtle changes in the environment, such as soil moisture, vegetation health, and mineral composition. The application of hyperspectral imagery has numerous benefits in various fields, including natural resource management, environmental monitoring, and military operations. 🚀 For instance, hyperspectral sensors can be used to monitor crop health, detect water pollution, or identify potential mineral deposits. 🌎 By leveraging the capabilities of hyperspectral imagery, geospatial professionals can gain a deeper understanding of the Earth's surface and make more informed decisions in their respective domains. #GIS #Geospatial #HyperspectralImagery #RemoteSensing #EarthObservation #SpatialAnalysis #TechGeoMapping #EssentialKeywords

Scientists have launched the first batch of a novel type of #radiation monitor into the #atmosphere as part of an innovative project to enhance #space #weather #models - the proof of concept launch took place concurrently on 17 October at Met Office sites in Camborne and Lerwick in the UK, as well as at De Bilt in the Netherlands operated by Dutch forecasters KNMI. Developed by the University of Surrey, the monitors were attached to weather observation balloons and released from ground level to go up more than 100,000 feet, capturing live observations of radiation levels as they travelled through the Earth’s atmosphere and towards the stratosphere. https://lnkd.in/eC7d96tM

🌲 GNSS under canopy — Why Your Starting Point Changes Everything! Ever wondered why your GNSS takes ages to get an RTK FIXED under trees? 😩🌳 When you power up your receiver directly under forest canopy, convergence can be painfully slow. Here’s why 👇 🌲 Signal attenuation — leaves and branches absorb GNSS signals 🔀 Multipath — reflections from vegetation distort them 📉 Fewer visible satellites — poorer geometry, weaker precision But there’s a simple trick 👇 ✨ Start your initialization in a clearing! Once the integer ambiguities are resolved, you can move into the forest — and the all-band receiver will reacquire RTK FIXED almost instantly. ⚡ 💡 Field tip: Always start your GNSS measurements in an open area to save time and improve accuracy. 💬 What about you — how do you optimize your GNSS performance under canopy? 🔗 geobsys.com #GNSS #fullconstellation #centipede #RTK #allband #precisionundercanopy #septentrio #mosaicx5 #geostix #IGN

💥💥 New Publication! Hot off the press!💥💥 Excited to share a new open-access article titled 'Prediction and mapping of boreal forest fire fuel loads using high-resolution satellite stereo imagery' by Lauri Korhonen, Matti Maltamo, Syed Adnan & Petteri Packalen. Just published in International Journal of Remote Sensing. 🛰️🛰️ Conventional satellite imagery is great for forest resources monitoring, but it is hard to infer forest vegetation height and structure from these "flat" 2D images. A new breed of satellites have additional 3D (stereo) vision capability - they can also sense vertical vegetation structure. Example satellites are the WorldView series, Pléiades series and Planet's SkySat constellation. We used data from such a satellite and showed that one can infer vegetation height and several other important forest parameters from it (see fig. 2 in the paper). We also demonstrated a new method ("DTM independent metrics") which makes our prediction methods applicable across the globe 🌍🌍. The paper is here: https://lnkd.in/dvng4pJZ. 😊🛰️🌲🌳💚📊🌎😊