Verify 1,600 Building Records
Budget / Salary€250–750
TypeFreelance project
LocationRemote
Posted1 hour ago
I need help refining a spreadsheet of 1,600 commercial and residential buildings. Your task is to confirm three key data points for each record and document your work so I can easily audit it later.
What you will do
• Measure the footprint of every building in square metres, drawing polygons directly in Google Earth.
• Pinpoint the most likely construction year, relying first on Google Earth historical imagery—the primary source I trust—then supplementing with short GPT-assisted searches or other verified sources only when imagery alone is inconclusive.
• Capture the current tenant or business name exactly as it appears on Google Maps.
How to document
• Enter each value in the supplied spreadsheet.
• Add a brief comment only for construction-year estimates, noting the imagery date or reference link that guided your decision.
• Flag any uncertainty for every data type using the colour-coded column provided (e.g., high, medium, low confidence).
Quality expectations
Accuracy is critical; I will spot-check random samples. Any record missing a footprint polygon, year estimate, tenant name, or uncertainty flag will be considered incomplete. Please maintain consistent units (m²) and cite all image dates or external URLs used.
If you are detail-oriented, comfortable navigating Google Earth and Google Maps, and can turn around reliable data quickly, I’d love to work with you.
What you will do
• Measure the footprint of every building in square metres, drawing polygons directly in Google Earth.
• Pinpoint the most likely construction year, relying first on Google Earth historical imagery—the primary source I trust—then supplementing with short GPT-assisted searches or other verified sources only when imagery alone is inconclusive.
• Capture the current tenant or business name exactly as it appears on Google Maps.
How to document
• Enter each value in the supplied spreadsheet.
• Add a brief comment only for construction-year estimates, noting the imagery date or reference link that guided your decision.
• Flag any uncertainty for every data type using the colour-coded column provided (e.g., high, medium, low confidence).
Quality expectations
Accuracy is critical; I will spot-check random samples. Any record missing a footprint polygon, year estimate, tenant name, or uncertainty flag will be considered incomplete. Please maintain consistent units (m²) and cite all image dates or external URLs used.
If you are detail-oriented, comfortable navigating Google Earth and Google Maps, and can turn around reliable data quickly, I’d love to work with you.
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