ESA title


  • ACTIVITYDemonstration Project
  • STATUSOngoing
  • THEMATIC AREAEnvironment, Wildlife and Natural Resources

Objectives of the service

Background Image credit: Sergio Izquierdo

The Illegal Logging Detection and Prediction (ILDAP) application detects illegal logging activities and anticipates possible future illegal logging instances. By analyzing various patterns, such as settlement developments or road construction, ILDAP predicts illegal logging activities as well as the functionality of dispatching near real-time alerts to users ensuring timely and effective responses. The ILDAP application harnesses Artificial Intelligence (AI), Geographic Information Systems (GIS), and the latest remote sensing data analytics, providing users with strategic and impactful insights. Beyond its core functions, it can help ensure the preservation of biodiversity and carbon stocks, making it a valuable tool for landowners, managers, project developers, NGOs and their sponsors. 

Users and their needs

In the ever-expanding global environmental monitoring market, long-standing challenges persist for customers. These challenges include getting accurate and timely reporting of illegal logging, resource and funding constraints, corruption, operational inefficiencies, weak government policies, and lack of concrete evidence to support interventions against illegal logging activities. ILDAP’s innovative solutions address several of these problems. Our customers receive actionable insights and near-real-time alerts enabling them to intervene and combat illegal logging activities through advanced detection, predictive capabilities, and more accurate reporting for the monetization of forest assets. 
With ILDAP, the shift towards proactive forest management and the mitigation of environmental crimes is here to connect forest managers, local communities, indigenous people (IPLC), forest conservation project developers, and sponsors in a single transparent source.

Service/ system concept

The system is divided into four distinct feature groups. 

The first feature is dedicated to logging detection, a central purpose of ILDAP. 

Thanks to the detection, alerts can be generated using Sentinel 1 radar data, which is capable of penetrating clouds. In tropical regions with extensive cloud cover, this capability is invaluable. The system issues alerts to users based on changes in forest structure (scattering), which are displayed on the ILDAP portal. Users can manually validate the alerts through field observations or drones with predetermined, computer generated flight parameters. This enables them to confirm illegal logging activities faster and accurately, facilitating more effective mitigation.

The second feature pertains to prediction. It involves mapping risks for illegal logging based on several topographical, weather, vegetation, and economic parameters. These parameters are processed using machine learning AI methods capable of handling large amounts of training datasets. Predictions allow users to take preventative measures, and more concisely allocate resources, such as engaging with local communities or increasing patrols in the area.

The third feature encompasses deforestation trends and contextual layers. Here, users can compare historical data, conduct annual comparisons, gain insights into trends, and assess the rate of change in deforestation and other relevant forestry and environmental information. This group aims to foster a comprehensive understanding of the area of interest.

The final feature facilitates the communication of insights through reports and visualizations on a web platform, catering to the needs of project developers and sponsors. Operational messages and alerts are directly dispatched to field personnel, either via the platform, email or WhatsApp depending on their preferences.

Space Added Value

The utilization of satellite remote sensing enables automated impact reports on illegal logging, offering numerous advantages including: (a) rapid insights, (b) expansive global monitoring, (c) accuracy and precision down to the hectare, (d) and cost-effectiveness. ILDAP significantly improves upon conventional products in the environmental monitoring market by introducing unparalleled illegal logging prediction capabilities (a feature virtually unprecedented for customers until now) and integration within contextual workflows for optimum utilization.

Current Status

As of autumn 2023, the pilot platform is ready for operational testing. Some of our key accomplishments over the past months are:

  • Deforestation detections over the past 3 months is more than 10x the amount of detections over free online platforms, with no false positives

  • The first prediction model is undergoing testing to identify accuracies and tailor output representation to use cases

  • The user interface for the platform is now ready and is being rolled out slowly to ensure operational certainty .

Space4Good and co-creation partners conduct in-field tests and on-site user feedback. 
Space4Good aims to extend its pilot campaign to other areas and organisations. For more information or if you have interest to partner, please contact

ILDAP picture


Prime Contractor(s)

Status Date

Updated: 18 January 2021