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Screen #39 of 60 Batch 7 desktop • 1440x900px

Desktop LiDAR LAS/LAZ Point Cloud to GeoTIFF DEM Elevation Studio

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Specification & Codex Reference Prompt (Click to expand) (Geospatial GIS studio processing millions of LiDAR point clouds, classifying ground returns, and generating digital elevation models (DEM).)

Screen Role: Geospatial GIS studio processing millions of LiDAR point clouds, classifying ground returns, and generating digital elevation models (DEM).

Design Intent: A professional GIS and geospatial engineering studio UI at 1440x900 resolution in clean Light Mode. Off-white background (#F8FAFC). Center stage: 3D perspective topographic terrain model rendered from a 12-million-point LiDAR point cloud, colorized with a crisp elevation gradient palette (emerald green valleys, golden plateaus, and snow-white mountain peaks). Left control panel (340px wide, white container with 1px border): - Source Cloud: "alpine_survey_2026.laz (184 MB, 12,480,100 points)" - Classification Filter: Checkboxes for "[x] Ground (Class 2)", "[x] Low Veg", "[ ] High Veg", "[ ] Buildings" - Resolution Grid: [ 1.0 Meter per Pixel v ] - Target Output: [ 32-bit Floating GeoTIFF DEM v ] Top export button in solid indigo "Generate GeoTIFF Digital Elevation Model". Precision geospatial survey UI, zero emojis.

Component Architecture: Django Cotton components (<c-file_converter.* />) with Tailwind tokens matching Labb.io design language.

Direct route: /file-converter/studio/lidar/ Template: file_converter/screens/screen_39.html
Live Django Implementation (desktop)
Isolate →
GIS

LiDAR Point Cloud to GeoTIFF DEM Elevation Studio

LAS / LAZ Point Cloud → 32-bit Float Digital Elevation Model

Source Point Cloud
alpine_survey_2026.laz
184 MB • 12,480,100 points
ASPRS Classification Filter
1.0 Meter per Pixel
32-bit Floating GeoTIFF DEM
CRS: EPSG:32632 (UTM 32N) • Min: 420m • Max: 2,840m
Original Codex Reference Mockup Full PNG
Authoritative Reference for Screen #39