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Duncan Srsic

Duncan Srsic

Geospatial Data Analyst - Remote Sensing and Agriculture

USA flag
Columbus, Ohio, Usa
$25.00/hrEntry LevelInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Geospatial Tiled ImageryGeospatial Tiled Imagery

Top Label Types

Polygon
Segmentation
Mapping
Land Cover Classification

Freelancer Overview

I am a Geographic Information Science graduate with hands-on experience in data labeling, annotation, and management of large geospatial and remote sensing datasets. My work at the AgSensing Lab involved validating and verifying remote sensing data, applying both manual and unsupervised classification workflows, and generating unique classifications using spectral indices for agricultural and natural systems. I am proficient with tools such as ArcGIS Pro, Pix4D, and Python, and have extensive experience processing DEMs, LiDAR, point clouds, and orthomosaic imagery. I have contributed to high-impact projects, including modeling agricultural water demand using NASA Earth Observation data, and am skilled at creating scientific maps, technical documentation, and clear data visualizations. My background enables me to ensure high-quality, accurate training data for AI and machine learning applications, particularly in the domains of geospatial analysis, computer vision, and environmental sciences.

Entry LevelEnglish

Labeling Experience

Geospatial Lab Assistant

Internal Proprietary ToolingGeospatial Tiled ImageryPolygonSegmentation
Labeled and validated satellite and aerial imagery to train machine learning models, ensuring feature accuracy and spatial consistency. Applied advanced cartographic techniques to create polygons and other shape-based annotations in challenging remote sensing data. Conducted quality assurance, detected errors, and addressed complex edge cases in ambiguous imagery. • Proficient human-in-the-loop workflows for geospatial AI training • Applied detailed QA for consistency across map tiles and time frames • Used contextual clues to interpret feature boundaries under uncertainty • Maintained audit trails and documentation for annotation decisions

Labeled and validated satellite and aerial imagery to train machine learning models, ensuring feature accuracy and spatial consistency. Applied advanced cartographic techniques to create polygons and other shape-based annotations in challenging remote sensing data. Conducted quality assurance, detected errors, and addressed complex edge cases in ambiguous imagery. • Proficient human-in-the-loop workflows for geospatial AI training • Applied detailed QA for consistency across map tiles and time frames • Used contextual clues to interpret feature boundaries under uncertainty • Maintained audit trails and documentation for annotation decisions

2022 - 2024

Education

T

The Ohio State University

Graduate Sciences (partial), Ecological Engineering

Graduate Sciences (partial)
2024 - 2024
T

The Ohio State University

Bachelor of Science, Geographic Information Science

Bachelor of Science
2020 - 2024

Work History

A

AgSensing Lab

Lab Assistant

Columbus
2022 - Present
T

Target

Grocery Associate

Columbus
2025 - 2026