{"product_id":"resepi-lite-os1-64-ndaa-compliant-drone-lidar-mapping-payload-system","title":"RESEPI LITE OS1-64 NDAA Compliant Drone LiDAR Mapping Payload System","description":"\u003cdiv class=\"mxos1\"\u003e\n\u003cstyle\u003e\n  .mxos1__training-copy .mxos1__list li {\n  color: rgba(255, 255, 255, 0.9) !important;\n}\n\n.mxos1__training-copy .mxos1__list li::before {\n  color: #35a9e0 !important;\n}\n    .mxos1{width:100%!important;max-width:100%!important;min-width:0!important;margin:0!important;padding:0!important;color:#20262b;font-family:inherit;font-size:16px;line-height:1.65;overflow:visible!important}\n    .mxos1,.mxos1 *{box-sizing:border-box!important}.mxos1 *{min-width:0!important;max-width:100%!important;overflow-wrap:break-word;word-break:normal}\n    .mxos1 section,.mxos1 article,.mxos1 figure,.mxos1 div,.mxos1 dl,.mxos1 ul{width:100%!important;display:block!important;float:none!important;clear:both!important}.mxos1 section{margin:0 0 38px!important}\n    .mxos1 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5px!important;color:#10293f;font-weight:800}.mxos1__spec-row dd{display:block;margin:0!important;color:#3c474f}.mxos1__note{color:#66727b;font-size:13px}\n    .mxos1__link-card{display:block!important;margin:0 0 18px!important;color:#20262b!important;text-decoration:none!important;background:#fff;border:1px solid #d9e0e5;border-radius:10px;overflow:hidden}.mxos1__link-card img{padding:0!important;border-bottom:1px solid #d9e0e5}.mxos1__link-copy{padding:19px 18px!important}.mxos1__link-copy h3{margin-bottom:8px}.mxos1__link-copy p:last-child{margin-bottom:0;color:#66727b}\n    @media(max-width:480px){.mxos1{font-size:15px}.mxos1 h2{font-size:26px}.mxos1 h3{font-size:20px}.mxos1__hero,.mxos1__cta{padding:23px 18px!important}.mxos1__card,.mxos1__legacy{padding:19px 17px!important}.mxos1__legacy img{width:100%!important}}\n  \u003c\/style\u003e\n\n  \u003csection class=\"mxos1__hero\"\u003e\n    \u003cspan class=\"mxos1__eyebrow\"\u003eRESEPI LITE with Ouster OS1-64 REV7\u003c\/span\u003e\n    \u003ch2\u003eNDAA-Compliant 64-Channel Drone LiDAR for Dense Scenes and Complex Geometry\u003c\/h2\u003e\n    \u003cp\u003eThe RESEPI LITE OS1-64 combines Ouster digital LiDAR with Inertial Labs precision navigation, onboard processing and optional RGB imaging in a compact government-ready payload. Its 64 laser channels, 360-degree horizontal coverage and 45-degree vertical field of view are especially valuable when the mission requires a dense representation of buildings, vehicles, poles, facades and other vertical features.\u003c\/p\u003e\n    \u003cp\u003eFor law enforcement, emergency management and civil government, the OS1-64 is best positioned as the high-throughput member of the RESEPI LITE family: a strong fit for urban scenes, tactical sites, public facilities, damaged structures and mobile mapping where scene density and rapid collection matter more than chasing the longest advertised range.\u003c\/p\u003e\n\n    \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/NDAA-Compliant-Badge-White-Letters-Blue-Hash-Red-Stripes.png?v=1783886988\" alt=\"NDAA compliant\" width=\"340\" height=\"120\" style=\"width:170px!important;margin:18px 0!important;\"\u003e\n\n    \u003cspan class=\"mxos1__pill\"\u003e64 laser channels\u003c\/span\u003e\n    \u003cspan class=\"mxos1__pill\"\u003e2.621 million points\/sec\u003c\/span\u003e\n    \u003cspan class=\"mxos1__pill\"\u003e45° vertical field of view\u003c\/span\u003e\n    \u003cspan class=\"mxos1__pill\"\u003e1.0 kg without camera\u003c\/span\u003e\n\n    \u003ca class=\"mxos1__button\" href=\"mailto:ops@maxsur.com?subject=RESEPI%20LITE%20OS1-64%20Drone%20LiDAR\"\u003eRequest a Configured Quote\u003c\/a\u003e\n    \u003ca class=\"mxos1__button mxos1__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eCompare Drone LiDAR Systems\u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cfigure class=\"mxos1__media\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-Ouster-OS164-Drone-LIDAR-Front-Transparent.png?v=1783915251\" alt=\"Front view of the NDAA-compliant RESEPI LITE Ouster OS1-64 drone LiDAR payload\" width=\"1200\" height=\"900\" loading=\"lazy\"\u003e\n      \u003cfigcaption class=\"mxos1__caption\"\u003eA compact RESEPI LITE payload built around the 64-channel Ouster OS1-64 REV7 scanner.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eWhat Sets the OS1-64 Apart\u003c\/span\u003e\n      \u003ch2\u003eDesigned to Collect More Geometry Around the Aircraft\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003cp\u003eMany airborne LiDAR systems are selected primarily for range or downward-looking terrain work. The OS1-64 takes a different approach. Its 64 channels, broad vertical field of view and high dual-return measurement rate help build a dense record of the environment surrounding the sensor.\u003c\/p\u003e\n\n    \u003cp\u003eThat makes the payload particularly useful when the point cloud must preserve walls, curbs, vehicles, poles, fences, roofs, facades and other geometry that may be underrepresented by a narrower scan pattern.\u003c\/p\u003e\n\n    \u003cdiv class=\"mxos1__callout\"\u003e\n      \u003cp\u003e\u003cstrong\u003eSimple model-selection rule:\u003c\/strong\u003e Choose the OS1-64 when dense structures and vertical scene detail are the priority. Consider an XT-32 or XT-32M2X configuration when tighter published scanner range accuracy, more returns or higher-altitude area coverage matter more.\u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cfigure class=\"mxos1__media\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-Ouster-OS164-Drone-LIDAR-Back-Transparent.png?v=1783915468\" alt=\"Rear view of the RESEPI LITE Ouster OS1-64 sensor-fusion payload\" width=\"1200\" height=\"900\" loading=\"lazy\"\u003e\n      \u003cfigcaption class=\"mxos1__caption\"\u003eRESEPI integrates the scanner with inertial navigation, GNSS, onboard computing, storage and field-control software.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eRESEPI Sensor Fusion\u003c\/span\u003e\n      \u003ch2\u003eA Complete Georeferenced Mapping Payload\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003cp\u003eRESEPI combines the Ouster scanner with an Inertial Labs GPS-aided inertial navigation system, tactical-grade IMU, single- or dual-antenna GNSS, Linux-based processing core and data-logging software.\u003c\/p\u003e\n\n    \u003cp\u003eThe payload can be controlled by a hardware button or through a wirelessly connected device using a web interface. RTK and PPK workflows support accurate positioning, while the optional 24 MP RGB camera adds imagery for colorized point clouds and complementary photogrammetry.\u003c\/p\u003e\n\n    \u003cdiv class=\"mxos1__stat-list\"\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e3-5 cm\u003c\/strong\u003e\n        \u003cspan\u003ePublished system vertical accuracy under specified test conditions\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e2.621M pts\/sec\u003c\/strong\u003e\n        \u003cspan\u003eMaximum published dual-return pulse rate\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e90 m\u003c\/strong\u003e\n        \u003cspan\u003ePublished range to suitable 10% reflectivity targets on all channels\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e75 m\u003c\/strong\u003e\n        \u003cspan\u003eRecommended maximum operating altitude AGL\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e1.0 kg\u003c\/strong\u003e\n        \u003cspan\u003ePayload weight without the optional camera\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxos1__stat\"\u003e\n        \u003cstrong\u003e41 W\u003c\/strong\u003e\n        \u003cspan\u003ePayload power consumption\u003c\/span\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003csection class=\"mxos1__legacy\"\u003e\n    \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/LiDAR-Scanner-with-Reflection-of-Crime-Scene-Resepi-Ouster-Sensor.png?v=1783914465\" alt=\"Ouster digital LiDAR sensor integrated into a RESEPI payload for crime scene and government mapping\" width=\"1200\" height=\"800\" loading=\"lazy\"\u003e\n\n    \u003cspan class=\"mxos1__eyebrow\"\u003eDigital LiDAR Meets Precision Navigation\u003c\/span\u003e\n    \u003ch2\u003eOuster Scanning Integrated With Inertial Labs RESEPI\u003c\/h2\u003e\n\n    \u003cp\u003eOuster's digital LiDAR architecture packages high-resolution 3D scanning into a compact sensor suited to robotics, industrial perception and mobile mapping. Inertial Labs adds the navigation, timing, data logging and processing foundation required to turn those measurements into a georeferenced mapping product.\u003c\/p\u003e\n\n    \u003cp\u003eInside the RESEPI LITE OS1-64, the two technologies serve different but complementary roles: the Ouster sensor captures dense environmental geometry, while the Inertial Labs INS and processing core determine where those measurements belong in space.\u003c\/p\u003e\n\n    \u003cp\u003eThe result is a versatile payload for aerial, vehicle, handheld and robotic collection—particularly attractive when a government team needs one scanner architecture to capture structures, sites and surrounding context from more than one platform.\u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eMission-Focused Applications\u003c\/span\u003e\n      \u003ch2\u003eDense 3D Data for Public Safety and Civil Government\u003c\/h2\u003e\n      \u003cp\u003eThe OS1-64's greatest operational value is its ability to represent complex scenes quickly and from a wide range of viewing angles.\u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxos1__card\"\u003e\n      \u003ch3\u003eCrime and Accident-Scene Documentation\u003c\/h3\u003e\n      \u003cp\u003eThe wide scan geometry can capture roadway context, vehicles, structures, signs, barriers, poles and other vertical features around a large outdoor scene.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eMajor collision and roadway documentation\u003c\/li\u003e\n        \u003cli\u003eLarge outdoor crime scenes\u003c\/li\u003e\n        \u003cli\u003eBuilding, vehicle and perimeter context\u003c\/li\u003e\n        \u003cli\u003eColorized point clouds with the optional RGB camera\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__card\"\u003e\n      \u003ch3\u003eTactical and Pre-Incident Planning\u003c\/h3\u003e\n      \u003cp\u003eDense geometry can improve understanding of routes, facades, overhead obstructions, walls, fences and other features that matter during planning.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eCorrectional facilities and government campuses\u003c\/li\u003e\n        \u003cli\u003eSchools, stadiums and public-event sites\u003c\/li\u003e\n        \u003cli\u003eIngress, egress and perimeter planning\u003c\/li\u003e\n        \u003cli\u003eVertical obstacles and line-of-sight context\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__card\"\u003e\n      \u003ch3\u003eEmergency Management and Structural Damage\u003c\/h3\u003e\n      \u003cp\u003eAfter storms, fires, floods or infrastructure failures, the OS1-64 can document damaged structures and surrounding access conditions in one spatial dataset.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eDebris fields and damaged facilities\u003c\/li\u003e\n        \u003cli\u003eRoad, bridge and access-route assessment\u003c\/li\u003e\n        \u003cli\u003ePublic infrastructure and critical sites\u003c\/li\u003e\n        \u003cli\u003ePre-event and post-event comparison\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__card\"\u003e\n      \u003ch3\u003eGIS, CAD and Public Works\u003c\/h3\u003e\n      \u003cp\u003eThe scanner can support municipal mapping programs that need a dense record of sites, structures and vertical assets for analysis or design.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eMunicipal GIS and asset inventories\u003c\/li\u003e\n        \u003cli\u003eConstruction progress and volumetrics\u003c\/li\u003e\n        \u003cli\u003eBuildings, curbs, poles and roadside features\u003c\/li\u003e\n        \u003cli\u003ePoint-cloud inputs for CAD and engineering workflows\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__card\"\u003e\n      \u003ch3\u003eMobile, Handheld and Robotic Mapping\u003c\/h3\u003e\n      \u003cp\u003eThe 360-degree scanner is naturally suited to collection from ground platforms as well as drones, extending the usefulness of the payload beyond a single aircraft.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eVehicle-mounted mobile mapping\u003c\/li\u003e\n        \u003cli\u003ePedestrian and handheld collection\u003c\/li\u003e\n        \u003cli\u003eAutonomous and robotic platforms\u003c\/li\u003e\n        \u003cli\u003eSupplemental ground capture around aerial projects\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eOptional RGB Mapping\u003c\/span\u003e\n      \u003ch2\u003eAdd Colorization and Image-Based Deliverables\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxos1__card mxos1__card--dark\"\u003e\n      \u003ch3\u003e24 MP RGB Mapping Camera\u003c\/h3\u003e\n      \u003cp\u003eThe optional 24 MP camera uses a Sony E-mount 16 mm lens with an approximately 70-degree field of view. It adds visual context to the LiDAR geometry and can support complementary image products.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eColorized point clouds\u003c\/li\u003e\n        \u003cli\u003eCrime-scene and damage-assessment imagery\u003c\/li\u003e\n        \u003cli\u003eOrthomosaics and photogrammetric models\u003c\/li\u003e\n        \u003cli\u003eClearer GIS, CAD and stakeholder deliverables\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003cdiv class=\"mxos1__callout\"\u003e\n      \u003cp\u003e\u003cstrong\u003eRecommended software division:\u003c\/strong\u003e Use the appropriate Inertial Labs workflow for RESEPI trajectory and LiDAR processing. Add PIX4D when the mission also requires orthomosaics, photogrammetric models, DSMs, contours or image-based CAD deliverables.\u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eFrom Collection to Deliverable\u003c\/span\u003e\n      \u003ch2\u003eA Practical OS1-64 Mapping Workflow\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxos1__step\"\u003e\n      \u003cspan class=\"mxos1__step-number\"\u003e1\u003c\/span\u003e\n      \u003ch3\u003eDefine the Geometry That Matters\u003c\/h3\u003e\n      \u003cp\u003eIdentify the structures, vertical assets, terrain, scene boundaries, accuracy requirements and final deliverables before planning the flight or mobile route.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__step\"\u003e\n      \u003cspan class=\"mxos1__step-number\"\u003e2\u003c\/span\u003e\n      \u003ch3\u003ePlan for Dense Coverage\u003c\/h3\u003e\n      \u003cp\u003eSelect altitude, speed, path spacing and viewing geometry that place sufficient measurements on facades, vehicles, poles and other target features.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__step\"\u003e\n      \u003cspan class=\"mxos1__step-number\"\u003e3\u003c\/span\u003e\n      \u003ch3\u003eCheck the Data in the Field\u003c\/h3\u003e\n      \u003cp\u003eUse included field-check capabilities to identify missing coverage before the scene, aircraft and personnel are demobilized.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxos1__step\"\u003e\n      \u003cspan class=\"mxos1__step-number\"\u003e4\u003c\/span\u003e\n      \u003ch3\u003eProcess and Deliver\u003c\/h3\u003e\n      \u003cp\u003eComplete pre-processing and supported post-processing, then prepare the point cloud, colorization, GIS, CAD, photogrammetry or operational products.\u003c\/p\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003csection class=\"mxos1__training\"\u003e\n    \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Drone-Training-Program-Development-for-Law-Enforcement.jpg?v=1767411084\" alt=\"MAXSUR AirOps LiDAR training for public safety and government mapping teams\" width=\"1400\" height=\"900\" loading=\"lazy\"\u003e\n    \u003cdiv class=\"mxos1__training-copy\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eMAXSUR AirOps Training\u003c\/span\u003e\n      \u003ch2\u003eTurn High Point Density Into Better Deliverables\u003c\/h2\u003e\n      \u003cp\u003eMore points are only useful when the mission is planned and processed correctly. MAXSUR can train operators to connect the OS1-64's scan geometry to repeatable public-safety and government workflows.\u003c\/p\u003e\n      \u003cul class=\"mxos1__list\"\u003e\n        \u003cli\u003eAircraft and payload integration\u003c\/li\u003e\n        \u003cli\u003eFlight speed, altitude, overlap and scan geometry\u003c\/li\u003e\n        \u003cli\u003eRTK, PPK, base stations and corrections\u003c\/li\u003e\n        \u003cli\u003eGround control and accuracy verification\u003c\/li\u003e\n        \u003cli\u003eField checks and point-cloud quality assurance\u003c\/li\u003e\n        \u003cli\u003ePIX4D, GIS and CAD handoff\u003c\/li\u003e\n        \u003cli\u003eSOP development and recurring proficiency\u003c\/li\u003e\n      \u003c\/ul\u003e\n      \u003ca class=\"mxos1__button\" href=\"https:\/\/www.maxsur.com\/collections\/uas-training-and-program-support\"\u003eExplore UAS Training and Program Support\u003c\/a\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eTechnical Specifications\u003c\/span\u003e\n      \u003ch2\u003eRESEPI LITE OS1-64 System Details\u003c\/h2\u003e\n      \u003cp\u003eFinal configuration should be selected around the aircraft, imaging option, operating platform, control workflow and required deliverables.\u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003ca class=\"mxos1__button mxos1__button--blue\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-OS1-64-Spec-Sheet-rev-1.6-Jul-1-2026-Available-at-MAXSUR.pdf?v=1783914910\" target=\"_blank\" rel=\"noopener\"\u003e\n      Download the RESEPI LITE OS1-64 Datasheet\n    \u003c\/a\u003e\n\n    \u003cdiv class=\"mxos1__spec-group\"\u003e\n      \u003ch3\u003eSystem Performance\u003c\/h3\u003e\n      \u003cdl class=\"mxos1__spec-list\"\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eSystem vertical accuracy\u003c\/dt\u003e\n\u003cdd\u003e3-5 cm under published Inertial Labs test conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePrecision\u003c\/dt\u003e\n\u003cdd\u003e4-6 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePrecision after single 1-sigma noise removal\u003c\/dt\u003e\n\u003cdd\u003e2-4 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eRecommended maximum AGL\u003c\/dt\u003e\n\u003cdd\u003eUp to 75 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eWeight\u003c\/dt\u003e\n\u003cdd\u003e1.0 kg without camera; 1.4 kg with camera\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eDimensions\u003c\/dt\u003e\n\u003cdd\u003e20.6 x 16.5 x 14.2 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eExample maximum flight time\u003c\/dt\u003e\n\u003cdd\u003e33 minutes on DJI M300 under manufacturer test conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eExternal storage\u003c\/dt\u003e\n\u003cdd\u003e256 GB USB included\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eSystem computer\u003c\/dt\u003e\n\u003cdd\u003eQuad core, 1 GB RAM and 8 GB eMMC\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eOperational voltage\u003c\/dt\u003e\n\u003cdd\u003e9-45 V\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePower consumption\u003c\/dt\u003e\n\u003cdd\u003e41 W\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxos1__spec-group\"\u003e\n      \u003ch3\u003eOuster OS1-64 REV7 LiDAR Scanner\u003c\/h3\u003e\n      \u003cdl class=\"mxos1__spec-list\"\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eRange capability\u003c\/dt\u003e\n\u003cdd\u003e90 m to suitable 10% reflectivity targets on all channels; 0.5-200 m overall range envelope in the specified mode\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eRange accuracy\u003c\/dt\u003e\n\u003cdd\u003e±2.5 cm under the manufacturer's stated static-target method\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eHorizontal field of view\u003c\/dt\u003e\n\u003cdd\u003e360°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eVertical field of view\u003c\/dt\u003e\n\u003cdd\u003e45°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eVertical scan angle\u003c\/dt\u003e\n\u003cdd\u003e-22.5° to +22.5°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eBeam divergence\u003c\/dt\u003e\n\u003cdd\u003e0.18° horizontal; 0.18° vertical, varying with measurement range\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eLaser channels\u003c\/dt\u003e\n\u003cdd\u003e64\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eMaximum returns\u003c\/dt\u003e\n\u003cdd\u003e2\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePulse rate\u003c\/dt\u003e\n\u003cdd\u003e2,621,000 points\/sec in dual-return mode\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxos1__spec-group\"\u003e\n      \u003ch3\u003eOptional Camera\u003c\/h3\u003e\n      \u003cdl class=\"mxos1__spec-list\"\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eCamera\u003c\/dt\u003e\n\u003cdd\u003e24 MP RGB mapping camera\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eLens\u003c\/dt\u003e\n\u003cdd\u003eSony E-mount 16 mm lens with approximately 70° field of view\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eMaximum trigger interval\u003c\/dt\u003e\n\u003cdd\u003e2 seconds\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eExternal camera support\u003c\/dt\u003e\n\u003cdd\u003eAvailable on select configurations\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxos1__spec-group\"\u003e\n      \u003ch3\u003eGPS-Aided Inertial Navigation\u003c\/h3\u003e\n      \u003cdl class=\"mxos1__spec-list\"\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eIMU\u003c\/dt\u003e\n\u003cdd\u003eInertial Labs tactical-grade Kernel IMU\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eGNSS\u003c\/dt\u003e\n\u003cdd\u003eSingle- or dual-antenna configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eSupported constellations\u003c\/dt\u003e\n\u003cdd\u003eGPS, GLONASS, Galileo, BeiDou, QZSS, NavIC\/IRNSS, SBAS and available L-Band configurations\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eFrequencies\u003c\/dt\u003e\n\u003cdd\u003eL1, L2 and L5, dependent on receiver configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eOperation modes\u003c\/dt\u003e\n\u003cdd\u003eRTK and PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eOutput rates\u003c\/dt\u003e\n\u003cdd\u003eUp to 200 Hz INS; up to 2,000 Hz IMU\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePitch \/ roll accuracy\u003c\/dt\u003e\n\u003cdd\u003e0.03° RTK; 0.004° PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eHeading accuracy\u003c\/dt\u003e\n\u003cdd\u003e0.1° RTK; 0.02° PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eVelocity accuracy\u003c\/dt\u003e\n\u003cdd\u003e\u0026lt;0.03 m\/s\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePosition accuracy\u003c\/dt\u003e\n\u003cdd\u003e1 cm + 1 ppm RTK; 0.5 cm PPK under specified conditions\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxos1__spec-group\"\u003e\n      \u003ch3\u003eSoftware\u003c\/h3\u003e\n      \u003cdl class=\"mxos1__spec-list\"\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003eField checks\u003c\/dt\u003e\n\u003cdd\u003eIncluded\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePre-processing\u003c\/dt\u003e\n\u003cdd\u003eIncluded\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxos1__spec-row\"\u003e\n\u003cdt\u003ePost-processing\u003c\/dt\u003e\n\u003cdd\u003eSupported\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cp class=\"mxos1__note\"\u003ePublished values are based on Inertial Labs and scanner test conditions. Actual range, accuracy, point density and deliverable quality depend on target reflectivity, altitude, speed, atmospheric conditions, GNSS quality, calibration, collection geometry, processing and control practices.\u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003csection\u003e\n    \u003cdiv class=\"mxos1__section-head\"\u003e\n      \u003cspan class=\"mxos1__eyebrow\"\u003eComplete the Mapping Workflow\u003c\/span\u003e\n      \u003ch2\u003eRelated MAXSUR Resources\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003ca class=\"mxos1__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Drone-LiDAR-for-Crime-Scene-Mapping.jpg?v=1783441385\" alt=\"Drone LiDAR systems for crime scene, emergency management and government mapping\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxos1__link-copy\"\u003e\n        \u003ch3\u003eAll Drone LiDAR Systems\u003c\/h3\u003e\n        \u003cp\u003eCompare RESEPI payloads by point production, range, accuracy, returns, field of view, weight and mission fit.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxos1__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/mapping-targets\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/LiDAR-targets-for-crime-scene-forensics.jpg?v=1783441142\" alt=\"Survey and mapping targets for LiDAR, photogrammetry and forensic documentation\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxos1__link-copy\"\u003e\n        \u003ch3\u003eSurvey and Mapping Targets\u003c\/h3\u003e\n        \u003cp\u003eEstablish control, verify project accuracy and connect aerial data with survey, GIS, CAD and forensic workflows.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxos1__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/pix4d-photogrammetry-mapping-software\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/products\/Pix4D-dsm-contours-ortho-Layers-from-drone-mapping-missions.png?v=1783912521\" alt=\"PIX4D photogrammetry, orthomosaic, point cloud and mapping software\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxos1__link-copy\"\u003e\n        \u003ch3\u003ePIX4D Photogrammetry and Mapping Software\u003c\/h3\u003e\n        \u003cp\u003eAdd orthomosaics, photogrammetric models, DSMs, contours and CAD-oriented imagery to the LiDAR workflow.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003csection class=\"mxos1__cta\"\u003e\n    \u003cspan class=\"mxos1__eyebrow\"\u003eConfigured and Supported by MAXSUR\u003c\/span\u003e\n    \u003ch2\u003eChoose the OS1-64 for Dense Structures and Complex Scenes\u003c\/h2\u003e\n    \u003cp\u003eTell MAXSUR what must be documented, the collection platform, target geometry, required accuracy and final GIS, CAD, forensic or emergency-management deliverable. We can help determine whether the OS1-64's high point throughput is the right fit—or whether another RESEPI scanner better serves the mission.\u003c\/p\u003e\n\n    \u003ca class=\"mxos1__button\" href=\"mailto:ops@maxsur.com?subject=RESEPI%20LITE%20OS1-64%20Drone%20LiDAR%20System\"\u003eContact MAXSUR\u003c\/a\u003e\n    \u003ca class=\"mxos1__button mxos1__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eCompare Drone LiDAR Systems\u003c\/a\u003e\n  \u003c\/section\u003e\n\n\u003c\/div\u003e","brand":"MAXSUR","offers":[{"title":"Default Title","offer_id":45991341555746,"sku":"IL-PRD250459-002","price":37000.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-Ouster-OS164-Drone-LIDAR-Front.jpg?v=1783915251","url":"https:\/\/www.maxsur.com\/products\/resepi-lite-os1-64-ndaa-compliant-drone-lidar-mapping-payload-system","provider":"MAXSUR","version":"1.0","type":"link"}