Unleash the Power of AI Mapping with Mapflow: Latin American cases
Mapflow AI transforms how people understand the world from EO imagery: by speeding up geospatial analysis and mapping workflows. AI models are only as good as the data they're trained on. To ensure AI models reach their full potential, we continuously improve datasets used for Latin American mapping to reflect the region's diversity.
Mapflow 2024 Statistic of Use
In 2024, over 4,000 processings were completed on the Platform by users from nearly all Latin American countries. Over 20,000 square kilometers of area were processed in total.?The Forest model was the most popular choice for these processes.
Here's a glimpse into what some Latin American customers are doing with Mapflow.
Urban Mapping in Mexico
IGECEM (Instituto de Información e investigación geográfica, estadística y catastral del Estado de México), uses Mapflow to streamline urban area monitoring for cadastral purposes.
As cities grow, IGECEM leverages Mapflow to track urban sprawl. By analyzing changes in building coverage over time the Institute can gain valuable insights into city development patterns. A basic model aimed at detecting Build-Up areas?was tuned to Mexican urban patterns and was used by our customers for the mapping analysis of high-density urbanized areas.?
Given the complexity of the LA urban patterns, we develop, customize, and fine-tune our Buildings model to achieve the best result.?
Urban Green Patterns Research
Twenty-seven urban green patterns were generated using Mapbox satellite basemap and Mapflow. The tree cover for the main Latin American cities from Mexico to Santiago reflects a unique mix of human-nature interaction.
Bolivian Forest Mapping
The vast forests are vital to the planet's health. Accurately mapping Bolivia's diverse forests is crucial for conservation, sustainable development, and combating deforestation. By harnessing ML, Bolivia can gain a clearer picture of its precious forests.?
The large mapping project was performed with the Mapflow Platform. There 2,000+ sq. km were mapped by the extremely fast and precise ML Forest model using local files uploaded by users.
领英推荐
Implementation of such projects requires collaborative functionality that is realized in the Mapflow Custom. Users can run a new?Team account functionality to invite collaborators, share projects, and manage Mapflow limits.?
Powerlines Monitoring in Argentina
We conducted a pilot project tuning the cost-effective solution for linear infrastructure monitoring. Our AI Forest with Heights?model is trained on lidar data to perform on 0.5-1m satellite images with high accuracy (MAE 3–4 m depending on the area and input resolution).
In this project, the Combo pipeline option was implemented featuring Forest with Heights and Buildings AI models. It might be useful for complex mapping to optimize your time and costs for data processing.
New Global Satellite Coverage?
We partner with the Chinese satellite data provider towards the data streaming and analytical services. This partnership enlarges our EO service providing annually updated global mosaic of high-resolution images (0.5 - 0.75 cm).
Operational possibilities of Chinese satellites enabling it to receive several times per day new images over the area of interest at a very high resolution.?
Geoalert Local Partners Program
GeoAlert Partners Program joins data and solution providers to help efficiently proliferate AI-mapping technology in different industries.?
We are expanding our network and are looking for strategic sales partnerships. We offer a competitive discount structure and easy access to all partners’ data and solutions.
Together we maximize our experience and market possibilities!