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Forest Conservation Using AI based Drones

Forest Conservation Using AI based Drones

AI-based drones are revolutionizing forest conservation by providing more efficient , accurate methods for monitoring and protecting forests. Their ability to detect threats, monitor forest health, and support sustainable practices is necessary for preservation of forests.

Revolutionizing Forest Conservation with Advanced Geo-Spatial Tools

Drones with advanced technologies i.e artificial intelligence (AI) enabling them to collect and analyze data more effectively than traditional methods. Technologies including LIDAR, Drones, Satellite Imageries will be used for conservation and digital footprints

Forests Coordinates using Differential GPS

AI algorithms process high-resolution satellite images to identify deforested areas, tree-cutting signs, and forest cover changes. Drones fly over forests to capture images. This is helpful to collect information in remote areas.

AI Algorithms for Change Detection and Anomaly Identification

Machine Learning Models: AI utilizes machine learning algorithms that process the collected data, learning patterns of tree cutting or forest disturbances. AI can detect changes that indicate illegal logging by comparing images or sensor data from different times.

Anomaly Detection: AI models look for anomalies, such as abnormal logging patterns or sudden vegetation changes, which suggest illegal tree-cutting.

Real-Time Alerts and Automated Monitoring

Instant Alerts: Once AI detects illegal logging, it automatically sends alerts to forest authorities, providing the GPS coordinates of the activity. This allows authorities to act immediately, reducing the chances of further damage.

Pilot Studies in Punjab Forests

The GIS Lab in Punjab is conducting pilot studies in three selected zones of the Punjab Forests using AI-based sensor technologies. These studies are aimed at testing the effectiveness and scalability of AI-driven tree cutting detection and further refining the system for broader deployment.

Study Areas and Objectives

Zonal Deployment: The pilot studies will be conducted across three forest zones in Punjab to evaluate how well the AI system performs in different forests.

AI-Based Sensor Integration: The GIS Lab will deploy sensors, drones, and satellite-based monitoring to track activities going on against forest health.

Testing and Refinement

The pilot studies will help fine-tune the AI algorithms, sensor deployment strategies, and alert systems to ensure the technology can work efficiently in diverse environmental forest types.

Smart AI Technology to Prevent Illegal Tree-Cutting Activities

Illegal tree cutting, or illegal logging is threatening ecosystems, biodiversity, and the environment. It helps to mitigate deforestation, loss of habitat for wildlife, and changes in climate patterns.

Early Detection and Prevention:

AI technology allows for the early detection of illegal tree cutting activities before they convert into large-scale deforestation.

Cost-Effective Monitoring:

Traditional forest monitoring requires physical patrols, satellite reconnaissance, or all of which are costly and labor-intensive