RLCMS

Regional Land Cover Mapping System

Solution Application

Open Source

Monitoring Changes with Machine Learning

Collaborating with NASA’s SERVIR Southeast Asia (SEA) and the Asian Disaster Preparedness Center (ADPC), Spatial Informatics Group developed AI technology to create yearly land cover maps for various uses, such as monitoring land use, land cover change, crop mapping, and more. At the onset of the project, focus was mainly on building tools for the Lower Mekong Region, but use of the RLCMS has expanded since its completion. Built with Google Earth Engine, the tool utilizes satellite imagery and user customization to produce maps appropriate to the user’s needs, and can be updated over time.

Technical Data

System Capabilities

System Support

RLCMS Application

Select views

Draw an area

View Analysis

Filling Technological Gaps

Prior to the development of these tools, creating land-use maps was both time-consuming and expensive, leaving officials with data that was outdated or otherwise not of use. SIG and SERVIR-SEA’s goal was to make their software easy to use and accessible to ensure the best possible data for yearly analysis.

Developing the RLCMS

Following the creation of the tool, Lower Mekong officials are able to create detailed, large scale land cover maps for each year quickly and much more easily than before. The system not only supports this region, but has been used in a variety of projects since its initial release, including SIG’s project to map crops in Cambodia. Thanks to its customizable nature, RLCMS is sure to become an important piece of software in a variety of land management situations, and will continue to provide important information for years to come.

RLCMS in Practice and Beyond

Following the creation of the tool, Lower Mekong officials are able to create detailed, large scale land cover maps for each year quickly and much more easily than before. The system not only supports this region, but has been used in a variety of projects since its initial release, including SIG’s project to map crops in Cambodia.

Thanks to its customizable nature, RLCMS is sure to become an important piece of software in a variety of land management situations, and will continue to provide important information for years to come.