SATELLITE IMAGERY- A.I. MAPPING & DETECTION MODELS

The Concept: 

Traditional digital mapping requires an impressive amount of work and a private army of cartographers to map even a single city. The process is straight forward but the time-consuming work makes it costly. Hence, there has been a growing interest in the idea of AI-assisted mapping, powered by deep learning image recognition algorithms. Through Map flow AI models, these can be achieved with much accuracy. The core of the Map flow are the Mapping Models-enables to detect and extract features in satellite and aerial images powered by semantic segmentation and other deep learning techniques. 

 AI Mapping Models: 

1. BUILDINGS: Extract roof contours (roof prints) from high-resolution satellite imagery

 

2. HIGH DENSITY HOUSING : Extraction and instance detection of the building roof prints in the areas of high-density housing 

3. FORESTS : Extract segmentation masks of forested areas from high-resolution RGB images 

4. ROADS : Extract road mask from high-resolution satellite imagery 

5. CONSTRUCTION : The model highlights areas in the satellite image that contain construction sites and buildings under construction 

6. AGRICULTURAL FIELDS : Extraction and instance separation of agriculture fields from high-resolution satellite imagery

MapFlow Documentation- https://docs.mapflow.ai/userguides/pipelines.html