{"product_id":"resepi-lite-xt-32-and-xt-32m2x-drone-lidar","title":"RESEPI LITE XT-32 and XT-32M2X Drone LiDAR","description":"\u003cdiv class=\"mxlitex\"\u003e\n  \u003cstyle\u003e\n    .mxlitex {\n      width: 100% !important;\n      max-width: 100% !important;\n      min-width: 0 !important;\n      margin: 0 !important;\n      padding: 0 !important;\n      color: #20262b;\n      font-family: inherit;\n      font-size: 16px;\n      line-height: 1.65;\n      overflow: visible !important;\n    }\n\n    .mxlitex,\n    .mxlitex * {\n      box-sizing: border-box !important;\n    }\n\n    .mxlitex * {\n      min-width: 0 !important;\n      max-width: 100% !important;\n      overflow-wrap: break-word;\n      word-break: normal;\n      hyphens: none;\n    }\n\n    .mxlitex section,\n    .mxlitex article,\n    .mxlitex figure,\n    .mxlitex div,\n    .mxlitex dl,\n    .mxlitex ul {\n      display: block !important;\n      width: 100% !important;\n      float: none !important;\n      clear: 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}\n\n      .mxlitex__card {\n        padding: 19px 17px !important;\n      }\n    }\n  \u003c\/style\u003e\n\n  \u003c!-- INTRODUCTION --\u003e\n  \u003csection class=\"mxlitex__hero\"\u003e\n    \u003cspan class=\"mxlitex__eyebrow\"\u003eInertial Labs RESEPI LITE Drone LiDAR\u003c\/span\u003e\n    \u003ch2\u003eAccuracy-Focused 3D Mapping With Two Distinct XT-32 Scanner Options\u003c\/h2\u003e\n    \u003cp\u003e\n      The RESEPI LITE XT-32 and XT-32M2X combine a 32-channel LiDAR scanner,\n      tactical-grade inertial navigation, single- or dual-antenna GNSS,\n      onboard computing, removable storage and optional RGB mapping imagery\n      in a field-deployable remote-sensing payload.\n    \u003c\/p\u003e\n    \u003cp\u003e\n      Both variants publish the same 2–3 cm system vertical accuracy and\n      ±1 cm scanner range accuracy. The decision is therefore not simply\n      “basic versus accurate.” It is a mission choice between the XT-32’s\n      tighter laser beam and focused short-to-mid-range performance, and the\n      XT-32M2X’s longer detection envelope, wider vertical view, third return\n      and lower payload weight.\n    \u003c\/p\u003e\n\n    \u003cspan class=\"mxlitex__pill\"\u003e2–3 cm published system accuracy\u003c\/span\u003e\n    \u003cspan class=\"mxlitex__pill\"\u003e±1 cm scanner range accuracy\u003c\/span\u003e\n    \u003cspan class=\"mxlitex__pill\"\u003eRTK and PPK workflows\u003c\/span\u003e\n    \u003cspan class=\"mxlitex__pill\"\u003eAerial, mobile and pedestrian mapping\u003c\/span\u003e\n\n    \u003ca class=\"mxlitex__button\" href=\"mailto:ops@maxsur.com?subject=RESEPI%20LITE%20XT-32%20or%20XT-32M2X%20Configuration\"\u003eRequest a Configured Quote\u003c\/a\u003e\n    \u003ca class=\"mxlitex__button mxlitex__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eCompare All MAXSUR Drone LiDAR Systems\u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- PRODUCT IMAGE --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxlitex__media mxlitex__media--transparent\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-XT-32-and-XT32-M2X-Drone-LiDAR-System-Front-of-Payload-Transparent.png?v=1783907317\" alt=\"RESEPI LITE XT-32 and XT-32M2X drone LiDAR payloads for public safety and government mapping\" width=\"1200\" height=\"900\" loading=\"lazy\"\u003e\n      \u003cfigcaption class=\"mxlitex__caption\"\u003eSelect XT-32 or XT-32M2X using the product options above. Camera and aircraft integration should be configured around the required deliverable.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- CHOOSE A VARIANT --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eChoose by Mission, Not by the Biggest Number\u003c\/span\u003e\n      \u003ch2\u003eXT-32 or XT-32M2X: What Is the Practical Difference?\u003c\/h2\u003e\n      \u003cp\u003e\n        The two systems share the same RESEPI processing foundation and the\n        same published accuracy class, but they collect the scene differently.\n        The comparison below is intended to prevent a common buying mistake:\n        assuming that greater maximum range automatically makes one scanner\n        better for every project.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxlitex__card mxlitex__variant\"\u003e\n      \u003cspan class=\"mxlitex__variant-tag\"\u003eXT-32\u003c\/span\u003e\n      \u003ch3\u003eFocused Accuracy for Localized Scenes and General Government Mapping\u003c\/h3\u003e\n      \u003cp\u003e\n        Choose the XT-32 when the agency primarily maps localized crime and\n        accident scenes, construction sites, municipal assets, campuses,\n        utility features or other projects where the 120 m detection envelope\n        and 100 m recommended AGL are sufficient.\n      \u003c\/p\u003e\n      \u003cp\u003e\n        Its narrower published beam divergence produces a smaller laser\n        footprint than the M2X configuration at a comparable distance. That\n        can be valuable when the mission emphasizes detailed surfaces and\n        smaller features rather than maximum altitude or vegetation returns.\n      \u003c\/p\u003e\n      \u003cul class=\"mxlitex__list\"\u003e\n        \u003cli\u003eUp to 100 m recommended AGL\u003c\/li\u003e\n        \u003cli\u003e0.05–120 m stated detection envelope\u003c\/li\u003e\n        \u003cli\u003eTwo returns per pulse\u003c\/li\u003e\n        \u003cli\u003e31° vertical field of view\u003c\/li\u003e\n        \u003cli\u003e0.021° horizontal and 0.047° vertical beam divergence\u003c\/li\u003e\n        \u003cli\u003e1.7 kg with the 24 MP camera; 1.3 kg without it\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__card mxlitex__variant mxlitex__variant--m2x\"\u003e\n      \u003cspan class=\"mxlitex__variant-tag\"\u003eXT-32M2X\u003c\/span\u003e\n      \u003ch3\u003eGreater Coverage, Triple Returns and More Flexibility in Vegetation\u003c\/h3\u003e\n      \u003cp\u003e\n        Choose the XT-32M2X when missions involve larger areas, wooded terrain,\n        emergency damage assessment, transportation corridors, broad public\n        properties or projects where a higher recommended altitude can reduce\n        the number of flight lines required.\n      \u003c\/p\u003e\n      \u003cp\u003e\n        The M2X expands the stated detection envelope to 300 m, adds a third\n        return, widens the vertical field of view to 40.3° and reduces payload\n        weight. Those characteristics make it the more versatile general\n        recommendation for agencies expecting a mixture of open terrain,\n        vegetation and larger-area projects.\n      \u003c\/p\u003e\n      \u003cul class=\"mxlitex__list\"\u003e\n        \u003cli\u003eUp to 150 m recommended AGL\u003c\/li\u003e\n        \u003cli\u003e0.05–300 m stated detection envelope\u003c\/li\u003e\n        \u003cli\u003eThree returns per pulse\u003c\/li\u003e\n        \u003cli\u003e40.3° vertical field of view\u003c\/li\u003e\n        \u003cli\u003eUp to 1.92 million measurements per second in triple-return mode\u003c\/li\u003e\n        \u003cli\u003e1.4 kg with the 24 MP camera; 1.0 kg without it\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- COMPARISON --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eSide-by-Side Model Selection\u003c\/span\u003e\n      \u003ch2\u003eThe Differences That Matter in the Field\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__compare\" aria-label=\"RESEPI LITE XT-32 and XT-32M2X comparison\"\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003ePublished system vertical accuracy\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e 2–3 cm\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e 2–3 cm\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eScanner range accuracy\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e ±1 cm\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e ±1 cm\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eRecommended AGL\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e Up to 100 m\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e Up to 150 m\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eStated detection envelope\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e 0.05–120 m\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e 0.05–300 m\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eLaser returns\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e Two returns\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e Three returns\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eVertical field of view\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e 31°\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e 40.3°\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eBeam divergence\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e 0.021° H \/ 0.047° V\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e 0.056° H \/ 0.1° V\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eWeight with 24 MP camera\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e 1.7 kg\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e 1.4 kg\u003c\/span\u003e\n      \u003c\/div\u003e\n      \u003cdiv class=\"mxlitex__compare-row\"\u003e\n        \u003cspan class=\"mxlitex__compare-label\"\u003eBest general fit\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value\"\u003e\u003cstrong\u003eXT-32:\u003c\/strong\u003e Localized scenes, detailed surfaces and cost-conscious general mapping\u003c\/span\u003e\n        \u003cspan class=\"mxlitex__compare-value mxlitex__compare-value--m2x\"\u003e\u003cstrong\u003eXT-32M2X:\u003c\/strong\u003e Larger areas, wooded terrain, higher-altitude collection and broader mission flexibility\u003c\/span\u003e\n      \u003c\/div\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__callout\"\u003e\n      \u003cp\u003e\u003cstrong\u003eMAXSUR guidance:\u003c\/strong\u003e The M2X is not “more accurate” on the published system specifications. It buys additional range, altitude, field of view, returns and lower weight. The standard XT-32 retains a tighter beam footprint and may be all the scanner an agency needs for localized, accuracy-focused work.\u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- PLATFORM OVERVIEW --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxlitex__media mxlitex__media--transparent\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-XT-32-and-XT32-M2X-Drone-LiDAR-System-Payload-back-transparent.png?v=1783907175\" alt=\"Rear view of RESEPI LITE XT-32 and XT-32M2X LiDAR systems showing processing and connection hardware\" width=\"1200\" height=\"900\" loading=\"lazy\"\u003e\n      \u003cfigcaption class=\"mxlitex__caption\"\u003eRESEPI combines the scanner with positioning, onboard processing, storage and field-control interfaces.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eMore Than a Laser Scanner\u003c\/span\u003e\n      \u003ch2\u003eA Complete Sensor-Fusion Payload for Repeatable Mapping\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003cp\u003e\n      RESEPI—the Remote Sensing Payload Instrument—integrates the LiDAR\n      scanner with an Inertial Labs tactical-grade inertial measurement unit,\n      high-accuracy GNSS, Linux-based computing and mission data logging.\n      The system supports RTK and PPK workflows and can be configured with\n      single- or dual-antenna GNSS.\n    \u003c\/p\u003e\n    \u003cp\u003e\n      A Wi-Fi interface and web-based controls simplify field operation, while\n      the included 256 GB removable USB storage helps move mission data into\n      the processing workflow. Optional camera and correction-communication\n      configurations allow MAXSUR to build the payload around the agency’s\n      required point-cloud, imagery, GIS or CAD deliverable.\n    \u003c\/p\u003e\n\n    \u003cdiv class=\"mxlitex__callout\"\u003e\n      \u003cp\u003e\u003cstrong\u003eWhy this matters:\u003c\/strong\u003e Final point-cloud quality depends on the scanner, trajectory, inertial measurements, GNSS conditions, calibration, control and processing. RESEPI packages those elements as a coordinated mapping system rather than leaving the user to synchronize unrelated components.\u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- APPLICATIONS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eTranslated for Government Missions\u003c\/span\u003e\n      \u003ch2\u003eWhere the XT-Series Fits MAXSUR Customers\u003c\/h2\u003e\n      \u003cp\u003e\n        These systems are not limited to traditional land surveying. Their\n        combination of portable aerial capture, 360° horizontal scanning and\n        multiple operating modes can support public-safety, emergency and\n        civil-government teams that need a measurable 3D record of a site.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxlitex__card\"\u003e\n      \u003ch3\u003eCrime and Accident-Scene Documentation\u003c\/h3\u003e\n      \u003cp\u003e\n        Capture roadways, terrain, structures, debris fields and surrounding\n        context from above while reducing the time personnel must remain in\n        traffic lanes, unstable areas or large outdoor scenes.\n      \u003c\/p\u003e\n      \u003cul class=\"mxlitex__list\"\u003e\n        \u003cli\u003eLarge collision and crime-scene mapping\u003c\/li\u003e\n        \u003cli\u003eMeasured point clouds for reconstruction and review\u003c\/li\u003e\n        \u003cli\u003eScene context beyond individual terrestrial scanner positions\u003c\/li\u003e\n        \u003cli\u003eOptional RGB imagery for colorization and mapping support\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__card\"\u003e\n      \u003ch3\u003eSearch, Rescue and Emergency Management\u003c\/h3\u003e\n      \u003cp\u003e\n        Map terrain, vegetation, access routes and damaged areas for field\n        planning, operational briefings and post-event assessment. The M2X’s\n        third return and larger coverage envelope are especially relevant when\n        wooded terrain or broad operating areas are expected.\n      \u003c\/p\u003e\n      \u003cul class=\"mxlitex__list\"\u003e\n        \u003cli\u003eWooded search areas and terrain definition\u003c\/li\u003e\n        \u003cli\u003eStorm, flood, wildfire and debris assessment\u003c\/li\u003e\n        \u003cli\u003eAccess-route and staging-area planning\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=\"mxlitex__card\"\u003e\n      \u003ch3\u003eGIS, Public Works and Civil Engineering\u003c\/h3\u003e\n      \u003cp\u003e\n        Build repeatable geospatial datasets for roads, drainage, corridors,\n        utilities, construction, volumetrics and public assets. The correct\n        scanner should be chosen around area size, required point density,\n        vegetation, flight restrictions and the downstream GIS or CAD product.\n      \u003c\/p\u003e\n      \u003cul class=\"mxlitex__list\"\u003e\n        \u003cli\u003eRoads, rights-of-way and municipal corridors\u003c\/li\u003e\n        \u003cli\u003eEarthwork, stockpiles and volumetric documentation\u003c\/li\u003e\n        \u003cli\u003eUtility and infrastructure mapping\u003c\/li\u003e\n        \u003cli\u003ePoint-cloud inputs for GIS, CAD and asset-management workflows\u003c\/li\u003e\n      \u003c\/ul\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__card\"\u003e\n      \u003ch3\u003eTactical and Pre-Incident Planning\u003c\/h3\u003e\n      \u003cp\u003e\n        Document campuses, correctional facilities, event sites and complex\n        public properties for ingress, egress, perimeter, terrain and obstacle\n        planning. The 360° scanner view can also support mobile and pedestrian\n        mapping configurations where aerial capture alone is insufficient.\n      \u003c\/p\u003e\n    \u003c\/article\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- XT32 VIDEO --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxlitex__media\"\u003e\n      \u003cvideo autoplay muted loop playsinline controls preload=\"metadata\" aria-label=\"RESEPI LITE XT-32 LiDAR point cloud tour of a transmission line corridor\"\u003e\n        \u003csource src=\"https:\/\/cdn.shopify.com\/videos\/c\/o\/v\/549c775378364632a85a998e622cd2d1.mp4\" type=\"video\/mp4\"\u003e\n        Your browser does not support embedded MP4 video.\n      \u003c\/source\u003e\u003c\/video\u003e\n      \u003cfigcaption class=\"mxlitex__caption\"\u003eExample XT-32 point-cloud tour of a transmission-line environment.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eXT-32 Example\u003c\/span\u003e\n      \u003ch2\u003eDetailed Capture Without Paying for Unneeded Range\u003c\/h2\u003e\n    \u003c\/div\u003e\n    \u003cp\u003e\n      The standard XT-32 is a strong match when the operating area can be\n      captured within its recommended altitude and range envelope. Its dual\n      returns, 32 channels, 360° horizontal coverage and tighter beam\n      divergence provide a practical foundation for public infrastructure,\n      localized forensic scenes, site documentation and routine government\n      mapping.\n    \u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- M2X VIDEO --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxlitex__media\"\u003e\n      \u003cvideo autoplay muted loop playsinline controls preload=\"metadata\" aria-label=\"RESEPI LITE XT-32M2X LiDAR point cloud tour of an electrical substation\"\u003e\n        \u003csource src=\"https:\/\/cdn.shopify.com\/videos\/c\/o\/v\/b9f4f365caee4fb280046e70e8f5d324.mp4\" type=\"video\/mp4\"\u003e\n        Your browser does not support embedded MP4 video.\n      \u003c\/source\u003e\u003c\/video\u003e\n      \u003cfigcaption class=\"mxlitex__caption\"\u003eExample XT-32M2X point-cloud tour of a complex electrical substation.\u003c\/figcaption\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eXT-32M2X Example\u003c\/span\u003e\n      \u003ch2\u003eBroader Coverage for Large and Complex Operating Areas\u003c\/h2\u003e\n    \u003c\/div\u003e\n    \u003cp\u003e\n      The M2X adds flexibility where the project footprint, vegetation or\n      flight plan makes additional altitude and returns useful. Its lower\n      payload weight can also preserve more aircraft capacity for practical\n      endurance, integration hardware or other mission requirements.\n    \u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- CAMERA --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eOptional RGB Mapping\u003c\/span\u003e\n      \u003ch2\u003eAdd Visual Context to the LiDAR Geometry\u003c\/h2\u003e\n    \u003c\/div\u003e\n    \u003cp\u003e\n      Both systems can be configured with a 24 MP RGB mapping camera using a\n      Sony E-mount 16 mm lens with an approximately 70° field of view. This\n      adds imagery for point-cloud colorization, site interpretation and\n      supporting mapping products.\n    \u003c\/p\u003e\n    \u003cp\u003e\n      Camera selection should be driven by the final deliverable. An agency\n      seeking a measurable LiDAR point cloud may not need the same imaging\n      configuration as an engineering team producing orthomosaics or a\n      forensic unit building a combined LiDAR-and-photogrammetry record.\n      MAXSUR can configure the camera, software and control workflow together.\n    \u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- SOFTWARE --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eFrom Raw Mission Data to a Usable Deliverable\u003c\/span\u003e\n      \u003ch2\u003eRESEPI Processing and Quality Control\u003c\/h2\u003e\n    \u003c\/div\u003e\n\n    \u003carticle class=\"mxlitex__step\"\u003e\n      \u003cspan class=\"mxlitex__step-number\"\u003e1\u003c\/span\u003e\n      \u003ch3\u003eCheck the Mission in the Field\u003c\/h3\u003e\n      \u003cp\u003eIncluded field-check capability helps the operator confirm that data was recorded before the aircraft and personnel leave the project location.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__step\"\u003e\n      \u003cspan class=\"mxlitex__step-number\"\u003e2\u003c\/span\u003e\n      \u003ch3\u003eProcess the Trajectory and Point Cloud\u003c\/h3\u003e\n      \u003cp\u003eUse the RESEPI software workflow for pre-processing and supported post-processing of the LiDAR, GNSS and inertial data.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__step\"\u003e\n      \u003cspan class=\"mxlitex__step-number\"\u003e3\u003c\/span\u003e\n      \u003ch3\u003eVerify Accuracy and Alignment\u003c\/h3\u003e\n      \u003cp\u003eReview control, checkpoints, coordinate systems, flight-line consistency and project conditions before releasing the data as an operational, forensic or engineering product.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003carticle class=\"mxlitex__step\"\u003e\n      \u003cspan class=\"mxlitex__step-number\"\u003e4\u003c\/span\u003e\n      \u003ch3\u003eExport to the Customer’s Workflow\u003c\/h3\u003e\n      \u003cp\u003eDeliver point clouds, surfaces, imagery or derived products into the organization’s preferred GIS, CAD, photogrammetry, reconstruction or asset-management environment.\u003c\/p\u003e\n    \u003c\/article\u003e\n\n    \u003cdiv class=\"mxlitex__callout\"\u003e\n      \u003cp\u003e\u003cstrong\u003eImportant:\u003c\/strong\u003e Published scanner and system accuracy are not a substitute for a documented field and processing procedure. Flight geometry, GNSS quality, corrections, control, calibration, processing and operator proficiency all affect the final result.\u003c\/p\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- AIRCRAFT --\u003e\n  \u003csection\u003e\n    \u003cfigure class=\"mxlitex__media\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/Long-range-and-heavy-lift-drone-for-police-surveillance-missions.jpg?v=1769654163\" alt=\"Long-range and heavy-lift drones for RESEPI LITE LiDAR mapping missions\" width=\"1400\" height=\"900\" loading=\"lazy\"\u003e\n    \u003c\/figure\u003e\n\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eGet the LiDAR Airborne\u003c\/span\u003e\n      \u003ch2\u003eMatch the Payload to the Right Professional Drone\u003c\/h2\u003e\n      \u003cp\u003e\n        MAXSUR offers medium-lift, heavy-lift, DFR and ultra-long-range drone\n        platforms. Aircraft selection should account for payload weight,\n        available power, mounting interface, center of gravity, desired\n        endurance, wind conditions, transportability and NDAA requirements.\n      \u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003ca class=\"mxlitex__button mxlitex__button--blue\" href=\"https:\/\/www.maxsur.com\/collections\/drones\"\u003eExplore MAXSUR Drone Platforms\u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- XT32 SPECIFICATIONS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eXT-32 Technical Specifications\u003c\/span\u003e\n      \u003ch2\u003eRESEPI LITE XT-32 System Details\u003c\/h2\u003e\n      \u003cp\u003eThe datasheet is placed here so technical buyers can review the manufacturer’s full test notes and configuration details beside the specifications.\u003c\/p\u003e\n      \u003ca class=\"mxlitex__button mxlitex__button--blue\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-XT-32-Drone-LiDAR-Datasheet-rev-1.7-Jul-1-2026-Available-at-MAXSUR.pdf?v=1783906387\" target=\"_blank\" rel=\"noopener\"\u003eDownload the XT-32 Datasheet\u003c\/a\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group\"\u003e\n      \u003ch3\u003eSystem\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSystem vertical accuracy\u003c\/dt\u003e\n\u003cdd\u003e2–3 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePrecision\u003c\/dt\u003e\n\u003cdd\u003e2–4 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePrecision after 1σ noise removal\u003c\/dt\u003e\n\u003cdd\u003e1.5–2.5 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eRecommended AGL\u003c\/dt\u003e\n\u003cdd\u003eUp to 100 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eWeight\u003c\/dt\u003e\n\u003cdd\u003e1.7 kg with camera; 1.3 kg without camera\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eDimensions\u003c\/dt\u003e\n\u003cdd\u003e20.8 × 17 × 14.2 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eExample maximum flight time\u003c\/dt\u003e\n\u003cdd\u003e33 minutes on DJI M300 under manufacturer configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSystem computer\u003c\/dt\u003e\n\u003cdd\u003eQuad-core processor, 1 GB RAM and 8 GB eMMC\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePower consumption\u003c\/dt\u003e\n\u003cdd\u003e26 W\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group\"\u003e\n      \u003ch3\u003eXT-32 LiDAR Scanner\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eLaser range capabilities\u003c\/dt\u003e\n\u003cdd\u003e80 m at 10% reflectivity on channels 9–24; 50 m at 10% reflectivity on channels 1–8 and 25–32; stated envelope 0.05–120 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eRange accuracy\u003c\/dt\u003e\n\u003cdd\u003e±1 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVertical field of view\u003c\/dt\u003e\n\u003cdd\u003e31°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVertical scan angle\u003c\/dt\u003e\n\u003cdd\u003e-16° to +15°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eBeam divergence\u003c\/dt\u003e\n\u003cdd\u003e0.021° horizontal; 0.047° vertical\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eLaser channels\u003c\/dt\u003e\n\u003cdd\u003e32\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eReturns\u003c\/dt\u003e\n\u003cdd\u003e2\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePulse rate\u003c\/dt\u003e\n\u003cdd\u003e640,000\/sec single return; 1,280,000\/sec dual return\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group\"\u003e\n      \u003ch3\u003eCamera, Navigation and Software\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eMapping camera\u003c\/dt\u003e\n\u003cdd\u003e24 MP RGB camera; Sony E-mount 16 mm lens; approximately 70° field of view; maximum trigger interval listed as 2 seconds\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eExternal camera support\u003c\/dt\u003e\n\u003cdd\u003eYes, for supported configurations\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eIMU\u003c\/dt\u003e\n\u003cdd\u003eInertial Labs tactical-grade IMU\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eConstellations\u003c\/dt\u003e\n\u003cdd\u003eGPS, GLONASS, Galileo, BeiDou, QZSS, NavIC\/IRNSS, SBAS and available L-Band\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVelocity accuracy\u003c\/dt\u003e\n\u003cdd\u003eLess than 0.03 m\/s\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePosition accuracy\u003c\/dt\u003e\n\u003cdd\u003e1 cm + 1 ppm RTK; 0.5 cm PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSoftware support\u003c\/dt\u003e\n\u003cdd\u003eField checks and pre-processing included; post-processing supported\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- M2X SPECIFICATIONS --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eXT-32M2X Technical Specifications\u003c\/span\u003e\n      \u003ch2\u003eRESEPI LITE XT-32M2X System Details\u003c\/h2\u003e\n      \u003cp\u003eReview the complete manufacturer datasheet for performance conditions, test assumptions and dimensional drawings.\u003c\/p\u003e\n      \u003ca class=\"mxlitex__button mxlitex__button--red\" href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-XT-32M2X-Drone-LiDAR-Datasheet-rev-1.7-Jul-1-2026-Available-at-MAXSUR.pdf?v=1783906376\" target=\"_blank\" rel=\"noopener\"\u003eDownload the XT-32M2X Datasheet\u003c\/a\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group mxlitex__spec-group--m2x\"\u003e\n      \u003ch3\u003eSystem\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSystem vertical accuracy\u003c\/dt\u003e\n\u003cdd\u003e2–3 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePrecision\u003c\/dt\u003e\n\u003cdd\u003e2–4 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePrecision after 1σ noise removal\u003c\/dt\u003e\n\u003cdd\u003e1.5–2.5 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eRecommended AGL\u003c\/dt\u003e\n\u003cdd\u003eUp to 150 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eWeight\u003c\/dt\u003e\n\u003cdd\u003e1.4 kg with camera; 1.0 kg without camera\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eDimensions\u003c\/dt\u003e\n\u003cdd\u003e20.8 × 16.5 × 14.2 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eExample maximum flight time\u003c\/dt\u003e\n\u003cdd\u003e33 minutes on DJI M300 under manufacturer configuration\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSystem computer\u003c\/dt\u003e\n\u003cdd\u003eQuad-core processor, 1 GB RAM and 8 GB eMMC\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePower consumption\u003c\/dt\u003e\n\u003cdd\u003e26 W\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group mxlitex__spec-group--m2x\"\u003e\n      \u003ch3\u003eXT-32M2X LiDAR Scanner\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eLaser range capabilities\u003c\/dt\u003e\n\u003cdd\u003e80 m at 10% reflectivity on all channels; stated envelope 0.05–300 m\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eRange accuracy\u003c\/dt\u003e\n\u003cdd\u003e±1 cm\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVertical field of view\u003c\/dt\u003e\n\u003cdd\u003e40.3°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVertical scan angle\u003c\/dt\u003e\n\u003cdd\u003e-20.8° to +19.5°\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eBeam divergence\u003c\/dt\u003e\n\u003cdd\u003e0.056° horizontal; 0.1° vertical\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eLaser channels\u003c\/dt\u003e\n\u003cdd\u003e32\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eReturns\u003c\/dt\u003e\n\u003cdd\u003e3\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePulse rate\u003c\/dt\u003e\n\u003cdd\u003e640,000\/sec single return; 1,280,000\/sec dual return; 1,920,000\/sec triple return\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cdiv class=\"mxlitex__spec-group mxlitex__spec-group--m2x\"\u003e\n      \u003ch3\u003eCamera, Navigation and Software\u003c\/h3\u003e\n      \u003cdl class=\"mxlitex__spec-list\"\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eMapping camera\u003c\/dt\u003e\n\u003cdd\u003e24 MP RGB camera; Sony E-mount 16 mm lens; approximately 70° field of view; maximum trigger interval listed as 2 seconds\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eExternal camera support\u003c\/dt\u003e\n\u003cdd\u003eYes, for supported configurations\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eIMU\u003c\/dt\u003e\n\u003cdd\u003eInertial Labs tactical-grade IMU\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eConstellations\u003c\/dt\u003e\n\u003cdd\u003eGPS, GLONASS, Galileo, BeiDou, QZSS, NavIC\/IRNSS, SBAS and available L-Band\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__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=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eVelocity accuracy\u003c\/dt\u003e\n\u003cdd\u003eLess than 0.03 m\/s\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003ePosition accuracy\u003c\/dt\u003e\n\u003cdd\u003e1 cm + 1 ppm RTK; 0.5 cm PPK\u003c\/dd\u003e\n\u003c\/div\u003e\n        \u003cdiv class=\"mxlitex__spec-row\"\u003e\n\u003cdt\u003eSoftware support\u003c\/dt\u003e\n\u003cdd\u003eField checks and pre-processing included; post-processing supported\u003c\/dd\u003e\n\u003c\/div\u003e\n      \u003c\/dl\u003e\n    \u003c\/div\u003e\n\n    \u003cp class=\"mxlitex__note\"\u003e\n      Published values are based on Inertial Labs test conditions. System\n      accuracy and precision figures are associated with controlled aerial\n      mission assumptions identified in the respective datasheets. Maximum\n      detection range, recommended operating altitude and final deliverable\n      accuracy are different concepts. Actual results depend on configuration,\n      target reflectivity, atmosphere, flight parameters, GNSS quality,\n      corrections, calibration, control and processing.\n    \u003c\/p\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- RELATED --\u003e\n  \u003csection\u003e\n    \u003cdiv class=\"mxlitex__section-head\"\u003e\n      \u003cspan class=\"mxlitex__eyebrow\"\u003eComplete the Mapping Capability\u003c\/span\u003e\n      \u003ch2\u003eRelated MAXSUR Resources\u003c\/h2\u003e\n      \u003cp\u003eBuild the payload into a complete, repeatable government mapping program.\u003c\/p\u003e\n    \u003c\/div\u003e\n\n    \u003ca class=\"mxlitex__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 mapping, emergency management and government GIS\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxlitex__link-copy\"\u003e\n        \u003ch3\u003eAll Drone LiDAR Systems\u003c\/h3\u003e\n        \u003cp\u003eCompare compact, high-density, long-range and expandable LiDAR payloads for public-sector missions.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxlitex__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=\"LiDAR and photogrammetry mapping targets for forensic and government control points\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxlitex__link-copy\"\u003e\n        \u003ch3\u003eSurvey and Mapping Targets\u003c\/h3\u003e\n        \u003cp\u003eAdd visible control and checkpoints for repeatable LiDAR, photogrammetry, forensic, GIS and CAD workflows.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n\n    \u003ca class=\"mxlitex__link-card\" href=\"https:\/\/www.maxsur.com\/collections\/uas-training-and-program-support\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/UAS-Training-and-Program-Support-for-Law-Enforcement.jpg?v=1783442300\" alt=\"UAS and LiDAR training for law enforcement and government mapping programs\" width=\"1000\" height=\"625\" loading=\"lazy\"\u003e\n      \u003cdiv class=\"mxlitex__link-copy\"\u003e\n        \u003ch3\u003eUAS Training and Program Support\u003c\/h3\u003e\n        \u003cp\u003eDevelop mission planning, RTK and PPK, control, processing, quality assurance and repeatable agency procedures.\u003c\/p\u003e\n      \u003c\/div\u003e\n    \u003c\/a\u003e\n  \u003c\/section\u003e\n\n  \u003c!-- FINAL CTA --\u003e\n  \u003csection class=\"mxlitex__cta\"\u003e\n    \u003cspan class=\"mxlitex__eyebrow\"\u003eConfigured and Supported by MAXSUR\u003c\/span\u003e\n    \u003ch2\u003eChoose the Scanner Around the Required Outcome\u003c\/h2\u003e\n    \u003cp\u003e\n      Tell us what must be documented, the typical project size, terrain and\n      vegetation, required accuracy, aircraft restrictions, imagery needs and\n      final GIS, CAD, forensic or engineering deliverable. MAXSUR can help\n      configure the XT-32 or XT-32M2X with the correct aircraft, camera,\n      mounting interface, corrections, mapping targets, software, training,\n      spares and support.\n    \u003c\/p\u003e\n\n    \u003ca class=\"mxlitex__button\" href=\"mailto:ops@maxsur.com?subject=MAXSUR%20RESEPI%20LITE%20XT-32%20and%20XT-32M2X%20Consultation\"\u003eContact MAXSUR\u003c\/a\u003e\n    \u003ca class=\"mxlitex__button mxlitex__button--outline\" href=\"https:\/\/www.maxsur.com\/collections\/lidar\"\u003eExplore All Drone LiDAR\u003c\/a\u003e\n  \u003c\/section\u003e\n\u003c\/div\u003e","brand":"MAXSUR","offers":[{"title":"XT32","offer_id":45990772310050,"sku":"IL-PRD250456-002","price":36000.0,"currency_code":"USD","in_stock":true},{"title":"XT32 M2X","offer_id":45990772342818,"sku":"IL-PRD250646-001","price":37000.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0874\/5416\/files\/RESEPI-LITE-XT-32-and-XT32-M2X-Drone-LiDAR-System-Front-of-Payload.jpg?v=1783907834","url":"https:\/\/www.maxsur.com\/products\/resepi-lite-xt-32-and-xt-32m2x-drone-lidar","provider":"MAXSUR","version":"1.0","type":"link"}