How SunTec.ai Improved GIS Accuracy by 40% Through Image Annotation.pdf

Discover how SunTec.ai helped an academic institution annotate over 1,200 historical maps, resulting in a 40% boost in water‐body detection accuracy for geospatial AI mapping. Dive into how manual expertise combined with digital restoration and precision annotation brought new life to vintage cartographic data.

1. Learn how
SunTec.ai ‘Improved
GIS Model Accuracy
by 40% Through Data
Annotation

2. THE CLIENTA leading academic institution studying natural water
resources, focusing on water conservation and developing
AI-powered geospatial mapping solutions through data
annotation to track environmental changes.

3. THE REQUIREMENTS
Image annotation of over 1200 historical maps to
accurately label water bodies such as rivers, lakes, and
reservoirs.
Enhancing faded maps for clearer data annotation,
ensuring detailed and precise labeling.
Creating a robust dataset for training AI/ML models using
accurately annotated historical map images.

4. PROJECT CHALLENGES 1.Low-quality, faded maps with obscured water body details,
requiring manual image annotation for accuracy.
2.Tight deadlines for processing a large volume of data
annotation, demanding efficiency without compromising
quality.
3.Complex cartographic styles and overlapping water bodies
necessitate careful manual annotation to preserve
accuracy.
4.Intricate geometries in water systems that required precise
boundaries for data annotation.

5. Page 06OUR SOLUTION We developed
customized image
annotation guidelines
specific to
geographic data to
ensure consistency
across the project.
The team used digital
restoration techniques
to enhance map
clarity, facilitating
better data
annotation.We employed the
CVAT tool for
polygon-based
image annotation,
supported by custom
automation scripts for
efficiency.
We implemented
multi-stage quality
checks to validate
data annotation,
ensuring that the final
dataset was both
accurate and
consistent.

6. 40%
enhancement in
object detection
accuracy for
water bodies,
through high-
quality data
annotation.
Improved
classification
and recognition
of different
water bodies
across
historical maps.
Faster model
development,
enabling timely
research insights
and supporting
the client’s
conservation
efforts.PROJECT OUTCOMES

7. Contact us at [email protected] and learn more about our image annotation and
data annotation services.
Read the complete case study here. STRUGGLING WITH AI/ML DATASET QUALITY? Phone: [phone]
WEBSITE: https://www.suntec.ai/