Coarse-to-Fine Multi-Platform Point Cloud Fusion 🚀 Different platforms (airborne, vehicle, handheld) produce point clouds with huge variations in viewpoint and features. Traditional loosely-coupled optimization often underutilizes matching info—global adjustments only reach suboptimal results, and overall alignment remains off. 🙅‍♂️ Our latest study in The Photogrammetric Record presents “Coarse-to-Fine Multi-Platform Point Cloud Fusion”, tackling multi-source registration challenges and poor global optimization performance! 😎 🛠 Our approach: Coarse-to-Fine We propose a cross-platform point cloud fusion framework based on multi-feature global optimization: 1️⃣ Coarse step | Pose graph preconstruction 🗺️ Split mobile platform point clouds into blocks Use bounding boxes flightline info for fast pose graph preconstruction 2️⃣ Fine registration | Local pairwise optimization 🔍 Extract multiple types of feature points Select high-quality points using matrix info Construct error equations with different distance metrics to solve relative poses Remove mismatches via Frobenius norm 🧹 3️⃣ Tight coupling | Global optimization 🌐 Design residuals with zero-expected errors for smooth constraints Solve all error equations iteratively in a tightly-coupled manner, improving overall point cloud consistency 📈 📊 Experiments Tested on two real sites (Chengdu highway 🛣️ & Shenyang urban 🏙️), RMSE results: 🏆 Site 1: Accuracy 50.6%! 🏆 Site 2: Accuracy 44.7%! From heavily vegetated highways to dense urban areas, the fusion results are visibly smooth. 📝 Paper Info 🔗 DOI: onlinelibrary.wiley.com/doi/… #PointCloudFusion #3DReconstruction #LiDAR #Surveying #RemoteSensing #Research #AlgorithmOptimization #MultiSourceData

📊 Bitcoin Consolidates Around Key Levels — 81EX Maintains Stable, Synchronized Market Display After an early-year rally, Bitcoin has entered a sideways consolidation phase, repeatedly oscillating around the $90,000 range. Macro expectations, technical indicators, and short-term capital flows collectively influence market rhythm, resulting in rapid sentiment shifts. At this stage, data stability, update consistency, and depth transparency matter more than price movements themselves, as users rely heavily on platform synchronization to avoid distorted judgment. 🌍 During phases where the market repeatedly tests both directions, 81EX maintains data integrity through a stable market-sync mechanism, ensuring users receive clear signals and continuous feedback even in periods of volatility: 🔹 Multi-source price validation reduces deviation 🔹 Continuous updates even under high-frequency volatility 🔹 Depth synchronization minimizes misjudgment caused by delay 💡 Even when price action repeatedly oscillates, information must remain consistent and transparent. Through stable display rhythm and synchronized market feeds, 81EX ensures users maintain logical clarity in uncertain environments supporting decisions based on verified data rather than emotional fluctuations. #81EX #81EXexchange #GlobalCompliance #SecureTrading #BitcoinMarket #VolatilityStructure #MarketSync #MultiSourceData #TrendAssessment

🔥 Read our Paper 📚 Research on Fine Estimation of People Trapped after Earthquake on Single Building Level Based on Multi-Source Data 🔗 mdpi.com/2076-3417/13/9/5430 👨‍🔬 by Shizhe Xie et al. #peopletrapped #multisourcedata

Dario Peduto - Multi-source data-based risk assessment of a road interacting with a slow-moving landslide-affected area. youtu.be/TLAXrUnGJhs Landslide Scientific Assessment Conference: Slope Dynamics #Landslides #RiskAssessment #MultiSourceData #Geohazards #EngineeringGeology

🔥 Read our Paper 📚 A Study on the Relationship between Urban Spatial Structure Evolution and Ecological Efficiency in Shandong Province 🔗 mdpi.com/2076-3417/14/2/818 👨‍🔬 by Mingyang Yu,Shuai Xu,Fangliang Zhou andHaiqing Xu. 🏫 Shandong Jianzhu University #multisourcedata #inverseSshapefunction #spatialstructureevolution #ecologicalefficiency #SBMmodel

#latestpaper 🏘️Measurement Method and Influencing Mechanism of #Urban Subdistrict Vitality in #Shanghai Based on #MultisourceData by Yishao Shi, Jianwen Zheng and Xiaowen Pei brnw.ch/21wLKkQ #urbansubdistrictvitality

8) Adaptability: The network is interoperable & integrates various data sources, providing a composite signal that enhances accuracy and reliability. Essential for systems across different environments and platforms. 🔄 #Adaptability #MultiSourceData

Leverage Multi-Source Data in ArcGIS Pro Intelligence: A MAXAR 3D Data and FMV Use Case: ow.ly/LqFe50IyKn6 #ArcGIS #multisourcedata @Esri_Defense @GISPublicSafety

A Combined #RandomForest and #OBIA Classification Scheme for Mapping #Smallholder #Agriculture at Different Nomenclature Levels Using #MultisourceData (Simulated #Sentinel2 Time Series, VHRS and #DEM) 👉mdpi.com/2072-4292/9/3/259/h… #RemoteSensing #SpectralIndices #Satellites #UAVs