Geospatial Annotation For AI & Machine Learning

Contour Annotation, Aerial View & Drone Imagery Annotation Services

Geospatial models are created by annotating satellite images, drone images, etc. Annotating roads, forests, agricultural areas, deserts, etc., is among the steps involved in developing geospatial machine learning models. Geospatial data is widespread in several industries, including shipbuilding yards, harbors, solar panels, etc. Being a trusted geospatial annotation company, Cogito promises high-end geospatial annotation services to develop AI training data for identifying different geo-characters, such as land covers, water bodies, and agricultural areas, and predicting geo-events, e.g., storms, floods, and earthquakes.

satellite imagery dataset

Satellite Imagery Dataset

A satellite image of an entire city can be segmented accurately to identify buildings, roads, water bodies, and other lands. A few other applications include cloud detection, water body monitoring, and tracking the changes in land use and settlement over time.

drone imagery dataset

Drone Imagery Dataset

A semantic segmentation model can be used to develop AI training data for geospatial annotations — which is further used to train drones for autonomous flights and their safe takeoff & landing. Besides detecting and recognizing obstacles and objects of interest, drones can also learn to detect and identify other drones.

infrared imagery​ dataset

Infrared Imagery​ Dataset

By combining RGB imagery with infrared channels, image labeling can be applied to enhance standard detection models in settings ranging from nighttime imagery to small object detection at sea or in complex environments to better crop classification based on infrared profiles.

Use Cases of Geospatial Annotation

field and forest analysis

Field & Forest Analysis

We analyze aerial photographs of agricultural fields captured by drones and tag them with semantic segmentation techniques. Artificial intelligence in forests can help guards to keep an eye on the conserved species of flora and fauna. Illegal deforestation or forest fires, all such activities can also be detected with AI-enabled systems. Annotating such actions in the images can help experts train the machine learning model for accurate detection and forest management.

construction and mining

Construction & Mining

From project planning to construction monitoring, AI & machine learning can improve efficiency. Artificial intelligence is beginning to gain traction among large construction & mining sites with regard to enhancing the safety of human workers.. Cogito's expertise in data annotation for geospatial datasets can help you analyze and label spatial data like GPS & satellite images. The operational processes in construction and mining can significantly speed up using AI.

urban area management

Urban Area Management

AI is being used by civil engineers and architects to plan and manage urban areas using geospatial machine learning. These AI & Machine Learning models can be trained well via geospatial data annotations for city planning, township management, and development. The street routes are labeled using accurate geospatial data annotation methods in drone training. A city can set out a better development path by leveraging AI, big data analytics, and machine learning.

disaster management

Disaster Management

Cogito claims to be a leading geospatial annotation company in the AI & machine learning space with a decade of industry exposure. AI can predict natural disasters and save thousands of lives using quality training data. Analyzing and labeling pre- and post-disaster aerial images of disaster-hit locations allows for efficient disaster management — which can assist rescue teams in managing, monitoring, and setting out immediate and workable disaster recovery plans.

logistics and transport management

Logistics & Transport Management

With GIS (Geographic Information Systems) transportation planning, it is possible to plan traffic volumes, create traffic schedules, and ensure the reliability of the transportation system. Geospatial data annotation can procure the pathway to opportunities to map out the entire network of waterways & highways. It can also aid to assess the size & structure of transport networks, freight terminals, existing road & sea routes, and new lanes for smooth transportation.

aerospace and defence

Aerospace & Defence

By leveraging geospatial data, aerospace and defence (A&D) companies can develop technology marvels to straighten out their line of existing products and processes. A&D companies can integrate artificial intelligence, machine learning methods, and quality geospatial annotation data across their value stream to design, build, and procure products as well as processes at an insanely high speed and quality while also ensuring precision in use and application.

Our Geospatial Annotation Process

Our Geospatial annotation service acquires data from various sources, e.g., sensors, GPS, mobile devices, social media, and satellite imagery. These data sources are then analyzed to determine trends and phenomena within the context of complex relationships among places and people using data visualizations.

Annotating spatial data is quite versatile, as it can be applied to anything observed on the earth. A cartogram, a map, a statistic, or a graph presenting drifts and historical evolutions are suitable for such visualization. Geospatial data annotation experts at Cogito label the spatial images in line with industry requirements — which can be further utilized to create AI geospatial training data for machine learning models.

Why Outsource to Cogito?

Data generated by drones and remote sensing systems, in general, are typically complex. Often, it requires data from multiple sensors synchronized together. In some cases, LiDAR or thermal displays are used to visualize faraway objects and substances. Outsource geospatial annotation tasks to Cogito — our geospatial annotation experts have decade-old mastery in efficiently annotating any pixel of aerial imagery using smart annotation tools.