Novel methods and technologies to improve monitoring and understanding of land use land cover dynamics based on satellite Earth Observation. The case of forest monitoring in Colombia
Thesis
The general objective of this project is to develop and apply innovative approaches related to satellite Earth Observation sensors, develop analytical methods and technologies to manage and process Big Data, providing consistent, transparent, robust, and cost-efficient monitoring systems for projects aimed to reduce deforestation and forest degradation. This project will also design a robust, consistent, and cost-efficient forest monitoring system, that will integrate multiple analytical approaches to provide spatially explicit value-added products to actors and users involved in initiatives to reduce forest degradation and deforestation. Specific objectives of the project are: 1. Develop and apply a methodology to assess the compliance to zero deforestation agreements, applied to 2615 livestock farms associated with the Sustainable Colombian Livestock project through the processing of Advanced Land Observations Satellites (ALOS) Phased Array Type L-band Synthetic Aperture Radar (PALSAR) imagery. 2. Design and evaluate a cloud-based computing infrastructure to ingest remote sensing big data (big volume, big velocity, big variety)for forest monitoring. The assessment of the digital infrastructure or cloud will be based on technical specifications and financial resources needed to be fully operational. 3. Develop and integrate in the cloud-based digital infrastructure, analytical approaches and algorithms to generate specific value-added forest products for multiple actor and users involved in initiatives associated to reduction of forest degradation and deforestation.
