Geospatial Data Science

Lessons and portfolio activities

1. 2.1
   What Makes Data Geospatial?Concept · 60–80 minutes
2. 2.2
   Coordinate Reference SystemsConcept + Lab · 90–120 minutes
3. 2.3
   Scale, Resolution and Spatial SupportConcept + Design Lab · 90–120 minutes
4. 2.4
   Geospatial Formats and MetadataProfessional Decision Lab · 90–120 minutes
5. 2.P1
   Accept, Review or Reject?Chapter Practicum · 120–150 minutes
6. 2.5
   GeoPandas and Spatial TablesTechnical Lab · 90–120 minutes
7. 2.6
   Geometry with ShapelyTechnical Lab · 90–120 minutes
8. 2.7
   Spatial Joins, Overlay and Nearest NeighboursProfessional Practicum · 120–150 minutes
9. 2.8
   Spatial Indexing and PerformanceTechnical Lab · 90–120 minutes
10. 2.9
    Topology, Geometry Cleaning and Data IntegrityProfessional Practicum · 120–150 minutes
11. 2.10
    QGIS for Professional Spatial QAProfessional Practicum · 120–150 minutes
12. 2.P2
    Vector Handover ReviewChapter Practicum · 120–150 minutes
13. 2.11
    What Is a Raster Really?Concept + Visual Lab · 75–90 minutes
14. 2.12
    Rasterio: Read, Inspect and Write Spatial GridsTechnical Lab · 100–120 minutes
15. 2.13
    Crop, Mask, Reproject and ResampleConcept + Technical Lab · 120–140 minutes
16. 2.14
    Raster Alignment and Grid IntegrityProfessional Practicum · 130–150 minutes
17. 2.15
    Raster–Vector IntegrationScientific Practicum · 120–150 minutes
18. 2.16
    Large Raster ProcessingTechnical Performance Lab · 100–120 minutes
19. 2.17
    Terrain Analysis with DEM and DSMScientific Application Lab · 110–140 minutes
20. 2.P3
    Build an Analysis-Ready Raster StackChapter Practicum · 240–300 minutes
21. 2.18
    UAV Remote Sensing FundamentalsConcept Lesson · 70–90 minutes
22. 2.19
    Mission Design: Altitude, GSD and OverlapConcept + Calculation Lab · 90–110 minutes
23. 2.20
    Sensors, Illumination and Radiometric QualityScientific Measurement Lab · 100–120 minutes
24. 2.21
    Georeferencing: GNSS, GCP, RTK and PPKConcept + QA Lab · 100–120 minutes
25. 2.22
    Structure from Motion and Photogrammetric ReconstructionConcept + Workflow Lab · 110–130 minutes
26. 2.23
    Point Clouds, DSM, DTM and OrthomosaicsScientific Product Lab · 110–130 minutes
27. 2.24
    UAV Product QA and Error DiagnosisProfessional Practicum · 130–150 minutes
28. 2.25
    UAV Multispectral Processing PipelineIntegrated Technical Practicum · 140–170 minutes
29. 2.P4
    Evaluate a UAV Survey Before Scientific AnalysisChapter Practicum · 420–600 minutes
30. 2.26
    Optical Remote SensingConcept and Product-Selection Lab · 150–180 minutes
31. 2.27
    Vegetation and Spectral IndicesSpectral-Index Interpretation Lab · 160–190 minutes
32. 2.28
    SAR FundamentalsSAR Reasoning and Comparability Lab · 170–210 minutes
33. 2.29
    Hyperspectral Remote SensingImaging-Spectroscopy Evidence Lab · 170–210 minutes
34. 2.30
    LiDAR and Point CloudsPoint-Cloud and Structural-Metric Lab · 170–210 minutes
35. 2.P5
    Build a Defensible Satellite Evidence PackageChapter Practicum · 420–540 minutes
36. 2.31
    Spatial AutocorrelationSpatial-Dependence Reasoning Lab · 170–210 minutes
37. 2.32
    Spatial Sampling and BiasSpatial Sampling-Design Studio · 170–210 minutes
38. 2.33
    Interpolation and GeostatisticsGeostatistical Reasoning and Validation Lab · 190–240 minutes
39. 2.34
    Spatial Regression ConceptsSpatial-Model Diagnosis Studio · 190–240 minutes
40. 2.P6
    Design and Defend a Spatial Inference PlanChapter Practicum · 420–540 minutes
41. 2.35
    SQL for Geospatial ScientistsRelational Evidence Lab · 170–210 minutes
42. 2.36
    PostGIS FundamentalsSpatial SQL Reasoning Lab · 190–240 minutes
43. 2.37
    Managing Large Spatial DataData-Architecture Decision Studio · 180–220 minutes
44. 2.P7
    Build a Governed Spatial Database HandoverChapter Practicum · 360–480 minutes
45. 2.38
    Xarray and RioxarrayLabelled-Array Reasoning Lab · 150–190 minutes
46. 2.39
    EO Data CubesEO Cube Construction Lab · 170–220 minutes
47. 2.40
    Dask and Lazy ComputationBounded-Computation Planning Lab · 160–210 minutes
48. 2.41
    COG, Zarr and Cloud-Native FormatsCloud-Format Decision Studio · 170–220 minutes
49. 2.42
    STACReproducible EO Discovery Lab · 170–220 minutes
50. 2.P8
    Build a Reproducible Cloud-Native EO Evidence CubeChapter Practicum · 420–540 minutes
51. 2.43
    Web Maps and Spatial ServicesWeb-Delivery Architecture Lab · 170–220 minutes
52. 2.44
    Interactive MappingAccessible Interactive-Map Studio · 190–240 minutes
53. 2.45
    OGC Standards and InteroperabilityInteroperability Verification Lab · 180–230 minutes
54. 2.P9
    Deliver an Accessible Environmental Monitoring MapChapter Practicum · 420–540 minutes
55. 2.46
    ArcGIS Professional EcosystemProfessional GIS Architecture Studio · 210–270 minutes
56. 2.P10
    Design a Portable Coastal-Meadow GIS ArchitectureChapter Practicum · 480–600 minutes
57. 2.47
    Image Segmentation FundamentalsImage Segmentation Laboratory · 180–230 minutes
58. 2.48
    Deep Learning for Geospatial ImagesGeospatial Deep-Learning Design Studio · 210–270 minutes
59. 2.49
    Geospatial Deep Learning QAGeospatial Model Assurance Review · 210–270 minutes
60. 2.P11
    Audit a Meadow Segmentation ProductChapter Practicum · 480–600 minutes
61. 2.50
    APIs and Automated Data AcquisitionEnvironmental API Acquisition Laboratory · 180–240 minutes
62. 2.51
    Command-Line Geospatial ToolsGeospatial Command-Line Laboratory · 170–220 minutes
63. 2.52
    Docker for Geospatial ReproducibilityContainer Reproducibility Studio · 190–250 minutes
64. 2.53
    Workflow Automation and CIGeospatial Automation and CI Laboratory · 210–270 minutes
65. 2.P12
    Productionise the Coastal-Meadow PipelineChapter Practicum · 540–720 minutes
66. Capstone
    UAV and Satellite Analysis PipelineModule Capstone · 24–40 hours