ArcGIS Coastline Shift Prediction
Budget: $10 – $30 USD
I have already digitised a UK shoreline from 1846-2024 and will share the geodatabase with you. Using ArcGIS Pro, I’d like a straightforward machine-learning model that focuses mainly on sediment changes to forecast the shoreline positions for 2044 and 2064.
Scope (kept lean to match the limited budget):
• Build a basic yet reproducible model inside ArcGIS Pro that ingests the time-stamped shoreline vectors and outputs two new feature classes—Predicted_2044 and Predicted_2064.
• Generate clear map layouts of both predicted shorelines and export them as high-resolution PNG or PDF.
• Produce simple graphs or charts that illustrate the predicted rate of change and any confidence bands you calculate.
I will supply:
• The digitised shoreline dataset (1846-2024)
• Background layers (DEM, aerial imagery) if useful
• Notes on known erosion hot spots and sediment supply shifts
Deliverables:
1. ArcGIS Pro project (.aprx) containing the trained model and resulting layers.
2. Two map exports.
3. A concise chart pack (PNG or PDF) summarising key metrics.
No lengthy report is needed—just the model, maps, and charts so I can validate the approach.
Scope (kept lean to match the limited budget):
• Build a basic yet reproducible model inside ArcGIS Pro that ingests the time-stamped shoreline vectors and outputs two new feature classes—Predicted_2044 and Predicted_2064.
• Generate clear map layouts of both predicted shorelines and export them as high-resolution PNG or PDF.
• Produce simple graphs or charts that illustrate the predicted rate of change and any confidence bands you calculate.
I will supply:
• The digitised shoreline dataset (1846-2024)
• Background layers (DEM, aerial imagery) if useful
• Notes on known erosion hot spots and sediment supply shifts
Deliverables:
1. ArcGIS Pro project (.aprx) containing the trained model and resulting layers.
2. Two map exports.
3. A concise chart pack (PNG or PDF) summarising key metrics.
No lengthy report is needed—just the model, maps, and charts so I can validate the approach.
Related categories:
Python
Cartography & Maps
Geolocation
Remote Sensing
Geospatial
Statistical Analysis
Data Visualization
ArcGIS