Spatial Informatics Group’s Environmental Mapping Solutions leverage satellite imagery, machine learning, artificial intelligence, and cloud computing to transform geospatial data into elegant, intuitive tools that provide decision makers with actionable information about their environment.
Our Environmental Mapping Solutions bring top-tier data sources and world-class academic insights to land managers all over the world. SIG’s Environmental Mapping team is global, with key people in Brazil, Peru, Colombia, Ecuador, Japan, Thailand, Cambodia, and the USA.
In keeping with SIG’s open science approach, many of these powerful tools are freely available online, transforming the capabilities of land management agencies around the globe.
SARFDAS is a powerful tool for detecting forest disturbances. It integrates state-of-the-art technologies, automation, and human-based verification in a clean web interface for more timely and accurate decision-making and field response. The system aids in effective resource allocation and fosters accurate responses to forest disturbances.
RLCMS leverages cloud computing, machine learning, and artificial intelligence to create yearly land cover maps. Used by entities in the Lower Mekong Region for cross-country comparative analyses of land use and land cover change, the system enables users to benchmark current conditions and sets a baseline for future reporting of progress in land governance.
se.plan is a free, online tool to identify places where the benefits of forest restoration greatly outweigh associated costs. With se.plan, users can generate maps depicting costs, benefits, and risks of restoration efforts on any particular site or region.
TerraOnTrack is a web application that allows traditional and indigenous communities in the Brazilian Amazon to identify and monitor threats and illegal activities on their territories. The system combines detailed maps, imagery, and governmental datasets with primary data contributed by community members via cell phones to synthesize timely and granular intelligence.
