GeoML Navigator-Geospatial Image Analysis

Example

Step-by-step guidance on importing drone imagery, setting up a project, and annotating features such as buildings, roads, and vegetation. This function includes instruction on the use of annotation tools and best practices to ensure high-quality data collection.

Scenario

An environmental consultant uses the guidance to annotate wetland areas for a conservation study, marking different types of vegetation and water bodies to assess environmental impact.

Example

Detailed tutorials on segmenting drone images using supervised and unsupervised classification methods. This function helps in distinguishing between different land covers and extracting relevant features from large datasets.

Scenario

A city planner segments images to identify zones of urban development and natural areas, using these insights to make decisions on land use and infrastructure development.

Example

Instructions on setting up YOLOv8 for object detection, including data preparation, model configuration, and training processes. Emphasizes on adjusting parameters for optimal accuracy and performance.

Scenario

A research team trains a model to detect and count vehicles in urban areas from drone footage, aiding in traffic management and planning.