Deforestation detection
It is a machine learning–based monitoring tool that detects and quantifies historical forest loss using satellite imagery within a user-defined area, generating multi-year reports to support environmental monitoring and regulatory compliance.
It is a machine learning–based monitoring tool designed to accurately detect and quantify historical forest loss. By analyzing satellite imagery within a user-defined geofence, the system generates a detailed multi-year report assessing the likelihood of past deforestation events, enabling precise environmental monitoring and regulatory compliance verification.
Water production and storage, and water use efficiency
Main theme:
Asian
Region:
2000 - 2400
Precipitation (mm):
Low
Application difficulty:
1, 2, 8, 5, 10, 13, 15, 14, 12 and 17
SDGs impacted:
Electric
Energy used:
70 - 90
Efficiency (%):
Urban/Rural
Sector:
Validates sustainable practices: It allows farmers to generate official reports proving their land is deforestation-free, which is essential for participating in sustainable supply chains that protect forests.
Protects on-farm forests: Farmers can monitor their properties for illegal logging or encroachment, enabling them to act as the first line of defense in preserving native vegetation.
Supports targeted reforestation: It helps identify previously deforested or degraded areas on their land, facilitating the planning and implementation of effective tree-planting and ecosystem restoration projects.
Prevents unintentional expansion: By providing a clear historical record of farm boundaries, it helps farmers manage land responsibly and avoid encroaching on protected forests or neighboring reserves.
Expected environmental impact:
Free
Estimated value:
Links of interest: