GIS Spatial Data Processing Using Google Earth Pro Training Course

Participants can select spatial data sources and document their suitability for defined uses.

• Authoritative basemap, boundary, elevation and imagery source selection criteria
• Open data licences, attribution statements and redistribution restrictions
• Portal searches using ISO 19115 metadata fields and keywords
• Data inventories recording owner, update cycle, scale and limitations
• Download workflows for Shapefile, GeoJSON, CSV, GeoTIFF and KML files
• Source fitness assessed against purpose, spatial coverage and attribute completeness

Participants can configure and use the Google Earth Pro workspace for efficient spatial inspection.

• Google Earth Pro panels, layers, places and temporary places management
• Tour the 3D viewer, status bar, ruler and search tools
• Layer visibility, draw order and terrain settings for readable maps
• Search coordinates, addresses, place names and longitude-latitude expressions
• Bookmark project locations using folders, placemarks and descriptive properties
• Keyboard shortcuts and navigation controls for efficient map inspection

Participants can identify coordinate system issues and verify location accuracy before processing data.

• Longitude-latitude coordinates entered as decimal degrees and degrees-minutes-seconds
• UTM zones, hemispheres and coordinate precision interpreted correctly
• WGS 84 versus local projected coordinate reference systems
• Datum mismatch symptoms identified through displaced boundaries and imagery
• Transformations documented when combining survey, cadastral and GPS datasets
• Coordinate checks performed against known control points and source metadata

Participants can create organised KML and KMZ projects with consistent feature properties and styles.

• KML 2.2 structure: Document, Folder, Placemark, Style and Geometry elements
• Create point, line and polygon features with meaningful names
• Apply labels, icons, line widths and polygon transparency consistently
• Feature descriptions formatted with source notes, dates and hyperlinks
• Save working layers as KMZ packages with embedded resources
• Organise thematic folders for field assets, risks and reference data

Participants can prepare and import common tabular and vector datasets into Google Earth Pro.

• CSV columns prepared for identifiers, coordinates, dates and measurements
• Import delimited tables using latitude-longitude field mapping and templates
• Map point symbology from categorical attributes and numeric value ranges
• Shapefile imports checked for projection, field truncation and geometry errors
• GeoJSON conversion routes assessed before import to Google Earth Pro
• Imported features reconciled against counts, extents and original records

Participants can digitise consistent point, line and polygon features from imagery and reference layers.

• Draw facilities, routes, exclusion zones and service areas from imagery
• Trace boundaries at an appropriate scale without false precision
• Capture attributes using controlled vocabulary, identifiers and collection dates
• Edit vertices, split paths and correct topology-like visual defects
• Record digitising assumptions within layer descriptions and metadata notes
• Compare operator interpretations using agreed feature-capture specifications

Participants can align image overlays and state the uncertainty of visual georeferencing results.

• Image overlays positioned using recognizable control points and transparency
• Scan distortion assessed before aligning historical maps and engineering plans
• Adjust overlay scale, rotation and opacity to inspect registration quality
• Ground control point distribution checked across corners and interior areas
• Document georeferencing uncertainty, source scale and residual visual offsets
• Separate reference overlays from analytical layers and final presentation maps

Participants can use Google Earth Pro measurement and terrain functions for preliminary site assessments.

• Ruler measurements for length, area, radius and elevation profiles
• Estimate site footprints and access distances using stated measurement assumptions
• Elevation profile interpretation for routes, drainage and line-of-sight screening
• Use 3D terrain views to identify ridges, slopes and obstructions
• Compare planned corridors against settlements, rivers and protected areas
• Record measurement units, imagery date and observer judgement limitations

Participants can identify and document visible change using historical imagery and time-enabled features.

• Historical imagery slider used to identify land-cover and construction change
• Compare image dates, seasonal conditions, sun angles and resolution
• Distinguish real change from shadows, cloud, mosaicking and geolocation shifts
• Create dated placemarks documenting observed change and supporting evidence
• Time-enabled KML features configured with TimeStamp and TimeSpan elements
• Build monitoring narratives from repeat imagery and ancillary inspection records

Participants can assess spatial data quality and record corrections through traceable quality controls.

• Positional, attribute, temporal, logical and completeness quality dimensions
• Validation rules flag missing identifiers, invalid coordinates and duplicate records
• Attribute domains standardise asset types, status codes and priority classes
• Detect outliers through range checks, map inspection and frequency tables
• Error logs assign correction actions, owners, dates and verification status
• Publish data-quality statements describing fitness, limitations and update requirements

Participants can assess spatial relationships and communicate preliminary analytical findings responsibly.

• Spatial predicates: intersects, contains, within, touches and nearest features
• Proximity screening identifies assets near floodplains, pipelines and schools
• Manual buffer visualisation communicates preliminary setback and exposure zones
• Overlay comparisons reveal conflicts between proposed sites and constraints
• Attribute filters isolate priority locations by status, risk and ownership
• State analytical limits when Google Earth Pro lacks formal geoprocessing

Participants can structure attributes and create targeted thematic subsets for operational reporting.

• Structured attribute schema supports filtering, sorting and audit-ready reporting
• Google Earth Pro search and folder organisation retrieve target records
• Filter design combines asset condition, inspection date and responsible unit
• Create thematic subsets for management review, field dispatch and escalation
• Cross-check query results against source registers and map feature counts
• Export selected layers while preserving identifiers and source traceability

Participants can prepare field data structures and integrate verified observations into master layers.

• Field data dictionaries define mandatory observations, domains and photo naming
• GPS waypoint accuracy, collection method and timestamp captured consistently
• Prepare offline KML packs for inspection routes and priority sites
• Photo links attached to placemarks using stable folder conventions
• Reconcile returned field observations with master layers and exception logs
• Version labels distinguish planned, observed, verified and superseded features

Participants can interpret imagery and elevation data while documenting confidence and limitations.

• Raster pixels, bands, resolution and resampling implications for interpretation
• Terrain, satellite imagery and scanned plans matched to suitable uses
• Elevation units, vertical datum caveats and terrain exaggeration settings
• Assess slope and drainage visually before engineering or humanitarian screening
• Image interpretation uses tone, texture, pattern, shape and association
• Document confidence levels for remotely interpreted features and boundaries

Participants can create readable spatial outputs for reports, briefings and decision meetings.

• Cartographic hierarchy establishes purpose, audience, focal features and supporting context
• Apply consistent colours, labels, symbols and transparency across thematic layers
• Legend wording distinguishes observed data, estimates, boundaries and proposed works
• Compose print layouts with title, north arrow, scale, sources and date
• Create annotated screenshots for reports, briefings and incident updates
• Review maps against readability, disclosure risk and decision requirements

Participants can package spatial outputs for controlled sharing with appropriate documentation and restrictions.

• KML, KMZ, CSV and image exports selected by recipient requirement
• Package folders, linked files and style assets for reliable transfer
• Email attachment limits and shared-drive permissions assessed before distribution
• Network Links configured cautiously for centrally updated KML content
• Data classifications applied to sensitive sites, beneficiaries and critical infrastructure
• Release notes record version, source changes, restrictions and contact owner

Participants can identify and manage hand-offs between Google Earth Pro and desktop GIS software.

• QGIS used to inspect layers requiring projection or attribute repair
• Reproject vector data to WGS 84 before Google Earth import
• Convert Shapefile and GeoJSON datasets into validated KML outputs
• Join tabular indicators to boundary features using stable identifiers
• GDAL-style conversion concepts: format, projection, fields and geometry validation
• Define hand-off criteria between Google Earth Pro and desktop GIS

Participants can define a controlled workflow for repeatable spatial data processing and review.

• Spatial data processing workflow maps inputs, transformations, outputs and approvals
• Scope statements specify decision question, area, timeframe and accuracy needs
• Processing logs preserve reproducibility for imports, edits, analyses and exports
• Quality assurance checkpoints cover schema, geometry, symbology and final files
• Stakeholder review criteria address usability, confidentiality and operational relevance
• Create a delivery plan with roles, milestones and acceptance criteria

Participants can build, review and present a complete Google Earth Pro spatial data project for a defined decision question.

• Define a spatial decision question and acceptance criteria from case requirements
• Compile authoritative source data, metadata records and licensing evidence
• Process, import and style layers within a structured KML project
• Assess change, proximity or suitability using documented visual analysis methods
• Produce a decision map, data-quality statement and processing log
• Present findings, assumptions, limitations and recommended follow-up actions