Lesson 1DSM vs DTM Making: Ways to Create Bare-Earth DTM in Partly Greened, Built Areas and River Path ModelingThis part explains DSM and DTM ideas and flows, focusing on bare-earth pull-out in greened and city areas. Learners will use filtering, editing, and river path modeling to get water-flow steady land surfaces.
DSM versus DTM definitions and usesGround point filtering in vegetationHandling buildings and urban artifactsManual terrain editing and breaklinesRiver channel and floodplain modelingLesson 2Orthomosaic Making: Seamlines, Light Blending, Color Balancing, and Handling Water/Reflective SurfacesThis part explains orthomosaic making from DSM or DTM, including seamline design, light balancing, and color fix. Learners will handle water, shadows, and shiny surfaces to make visually steady, exact mosaics.
Orthorectification using DSM or DTMSeamline placement and editingRadiometric balancing and blendingColor correction and tone mappingHandling water, shadows, and glareLesson 3Bundle Adjustment: Theory Overview, Role in Setting Relative Shape, Understanding Leftovers and Report MeasuresThis part brings in bundle adjustment theory and its role in setting relative camera shape. Learners will get normal equations, limits, and how to read leftovers, covariance, and software reports to judge solution steadiness.
Collinearity equations and observation modelWeighted least squares and constraintsRelative orientation and network geometryInterpreting residuals and outliersReading bundle adjustment quality reportsLesson 4Image Matching and Keypoint Linking: Aims, Tie Points, and Ways to Boost Tie QualityThis part details image matching and keypoint linking, including feature spotting, tie point making, and quality boost ways. Learners will tune matching settings and spot poor overlap, blur, or repeat texture problems.
Feature detection and descriptor choiceTie point matching and cleaningAlignment settings and accuracy levelsDealing with low overlap or motion blurManaging water, snow, and textureless areasLesson 5Image Bring-In, Details Check, and Pre-Processing: EXIF Checks, Lens Profile, Light FixesThis part covers safe image bring-in, details check, and pre-processing. Learners will check EXIF wholeness, lens profiles, and coordinate tags, then use light fixes and image pick to ensure strong later processing.
Organizing image datasets and backupsEXIF and GNSS metadata validationLens profile selection and verificationRadiometric and color correctionsImage quality screening and cullingLesson 6Vector Pull-Out and Planimetric Mapping: Breakline Making, Building Base Pull-Out, Road Middle Lines, and Water MappingThis part covers vector pull-out and planimetric mapping from orthomosaics and height data. Learners will draw breaklines, building bases, roads, and water mapping, and use shape rules and accuracy checks for mapping goods.
Digitizing and snapping best practicesBreakline creation from terrain modelsBuilding footprint and roofline mappingRoad centerlines and pavement edgesHydrography and drainage network tracingLesson 7Camera Calibration and Inner Orientation: Self-Calibration Settings, When to Fix vs Guess Focal Length and DistortionThis part covers camera calibration and inner orientation, including self-calibration settings and when to fix or guess them. Learners will get focal length, main point, and distortion models and their effect on accuracy.
Interior orientation and camera modelsRadial and tangential distortion termsSelf-calibration requirements and risksFixing versus estimating focal lengthUsing pre-calibrated metric camerasLesson 8Dense Point Cloud Making: Filtering, Noise Removal, Classifying Points (Ground, Green, Buildings)This part focuses on dense point cloud making from matched images. Learners will set depth map settings, handle noise, class points into ground and things, and ready a clean point cloud for surface modeling and editing.
Depth map generation parametersPoint density versus processing timeNoise filtering and outlier removalGround and non-ground classificationExport formats and data managementLesson 9Quality Checks at Each Step: Tie Point Leftovers, GCP Leftovers, RMSE on Check Points, Visual Compare, Cross-Sections and Profile ChecksThis part explains how to check quality at each processing step using number measures and visual checks. Learners will read leftovers, RMSE, and profiles to spot issues early and decide when to rerun or edit.
Tie point residuals and reprojection errorGCP and check point residual analysisRMSE computation and interpretationVisual inspection of orthos and 3D viewCross-sections and elevation profile checksLesson 10Processing Ways for Small Budgets: Cloud vs Local Processing, Open-Source (e.g., OpenDroneMap) vs Paid Software Trade-OffsThis part compares processing ways under small budgets, covering hardware picks, cloud vs local flows, and open-source vs paid tools. Learners will balance cost, speed, growth, and data safety for real jobs.
Estimating compute and storage needsCloud processing costs and constraintsLocal workstation and GPU considerationsOpen-source photogrammetry toolchainsCommercial software features and licensing
