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Athomatized cloud based processing of Sentinel-1 and decision making spatial functions. Connecting satellites, farmers, managers, scientist and donors

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SILVA-CRAS

Project: System for decision-making within the framework of forest conservation agreements at the property level in the Caquetá foothills of the colombian Amazon, Conservation and Governance Program -Patrimonio Natural, funded by USAID.

Develop a remote semi-automated monitoring system for deforestation monitoring, functional, scalable, robust and cost-efficient; producing automated deforestation reports, and providing information of the location and extension of deforestation events in the Piedmont of Caquetá.

Josef Kellndorfer, Ph.D., President and Senior Scientist, Earth Big Data, LLC

Carlos Pedraza, Ms.C., Spatial analyst and Monitoring Expert, iScioLab and Earth Big Data, LLC

Fecha revisión: Pendiente

This repositiry is to share change detection routines for deforestation quaterly reports based on Sentinel-1 imagery. This repository is designed to articule teams from The colombian forest and carbon monitoring system, Patrimonio Natural and the developers of the solution.

Radar remote sensing, cloud processing, big data, authomatization, decision making, change detection, deforestation,

Specific:

To integrate into the C&G (Conservation and Governance) Program decision-making proccess and key performance indicator assessment.

Estimate the deforestation's reduction along with the route for its technological adoption, as a tool to improve the proccesses of monitoring compliance for the conservation agreements signed under the Conservation and Governance Program.

Instalación de Software y Datos

Please refer to the INSTALLATION and DATA-HOW TO documents.

The time series data was pre-processed with Ssoftware for Earth Big Data Processing, Prediction Modeling and Oorganization (SEPPO) EARTH BIG DATA using cloud-based processing routines through Amazon Web Services (AWS). SEPPO enables the complete processing of large volumes of SAR data (and other remote sensing products) to efficiently build time series data. The data format guide EBD_README explains data structures and filenaming conventions for data sets produced by EARTH BIG DATA, LLC.

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