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Snow Data from Space

Daily Maps of Snow Cover, Snow Height and Snow-Water-Equivalent.

COSMOS by ExoLabs

A picture is worth a thousand words.
A satellite image is worth a million dollars.

ExoLabs provides tailored software solutions, data products and scientific know-how based on geospatial and remote sensing data to support the private and public sector in gaining insights and efficiency at reduced costs. 


Our uniqueness lies in integral and agile data processing from many sources, in particular in the field of near real-time satellite data processing on a global scale.

Start: Unsere Technologie
Start: Nachrichten

The Hiking Club partners with ExoLabs

April 2024

The Hiking Club has integrated ExoLabs’ estimated current snow depth and 48-hour new snow forecast layers into the map in their trip planning app. Snow uncertainty will be a thing of the past on famous multi-day trails in the Alps, like the Tour du Mont Blanc, Walker’s Haute Route, and Alta Via 1 Dolomites.

Products

Snow Data from Space

COSMOS: Daily Maps of Snow Cover, Snow Height and Snow-Water-Equivalent

At ExoLabs we developed and are still actively improving a pipeline from satellite imagery to three main characteristics of snow: 

  • Snow Cover: A global map of probabilities that a respective pixel is covered in snow.

  • Snow Depth: Regional maps of the height of snow cover. 

  • Snow-Water-Equivalent: Snow can be dry or wet, compact or loose. Snow density combined with snow depth provides the critical information of how much water would be within a cube of snow, if melted. 

These models build on top of each other and are unique in their temporal (daily) and spatial (20 m) resolution. The high influence of topography on snow distribution is considered in a novel approach, which full potential is yet to be discovered. 

Forest Data from Space

ExoSilva: Daily Maps of Forest Health

The main objective of SILVA is to detect forest disturbances in near real-time with daily updates in a high spatial resolution of 20 m for the entire area of Switzerland. In addition, annual re-analysis data on forest height and disturbances is provided for economic and political interpretation. All this information is directly accessible via multiple services for interested parties.

Surface Data from Space

AutoMap: Download, pre-process, merge and classify thousands of satellite images with a few clicks.

Originated as tailored solution for an industry partner, AutoMap is the general use-case adaption for the bulk-processing of earth observation satellite data. It enables users to harness the freely available satellite data provided by NASA and ESA, without dealing with clouds, in the sky or the web, process optimisations or storage limitations. Further, it allows users to easily perform their very own, individually optimised, land cover classifications.

Unique Pre-Trained Classifiers

ADELE: Deep Learning for Land Use and Land Cover Changes

Our pre-trained classifiers support the Swiss government to identify 99 different land use / land cover categories within its territory. These classifiers are trained on a unique training set and can be adapted to various use-cases.

Services

Environment

Snow Mapping
Forest Monitoring
Crop Assessment
Change Detection

The earth is rapidly changing and satellites are the best tool to measure that globally. The quantification of these changes on different scales enable regional, national and international policy-makers to make educated decisions to improve efficiency and sustainability.

Infrastructure

Site Information
Planning Assistance
Hazard Monitoring 
Asset Management

As cities become bigger, rural areas fight with an increasing outflow. Urban planning and regional development based on geo-information, statistical models and remote-sensing data help public sector entities to manage and obtain their resources as effectively as possible.

Resources

Condition Analysis
Quantification 
Monitoring
Estimations and Trends

The world's population is affected by changing environmental conditions. Acquiring accurate metrics for strategic management of resources is crucial for an efficient use of ecosystem goods and services and to become more resilient.

Insurance

Exposure Management
Index Insurance
Risk Reduction
Loss Assessment

Severe weather events put enormous pressure on insurances that manage the risks of farmers, governments or companies. Highly scalable spatio-temporal data is an essential input for modern insurers to model different scenarios for their customers.

Start: Dienstleistungen

References

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Partners

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Start: Kunden
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Reik Leiterer
PhD

CEO
Co-Founder

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Hendrik Wulf
PhD

CPO
Co-Founder

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Gillian Milani
PhD

CTO
Co-Founder

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Bernhard Sassik
MSc

Developer
Shareholder

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Clémence Herny
PhD

Data Scientist

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Clotilde Marmy
MSc

Data Scientist

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Gwenaelle Salamin
MSc

Data Scientist

Start: Unser Team
Start: Über uns

About

Every day, multiple satellites collect petabytes of data from our earth's surface. A lot of those images are freely available, but due to the sheer endless amount of possible applications in science and business services, they are stored in a raw state that satisfies only the most basic needs for as many use-cases as possible. The theme of generic solutions for everybody is symptomatic for the remote sensing community and exactly the reason why ExoLabs exists - We develop solutions that are tailored to your needs!

With us, the complex tasks of pre-processing large amounts of satellite data in different spatial, temporal and spectral dimensions can be dispatched and the prevailing concept of general solutions forgotten. We start building where your idea begins. 

ExoLabs is a Swiss company located in Zurich, founded in 2017 as a spin-off of the University of Zurich. Remote sensing is our common interest and scientific background.

Schwandenholzstrasse 272

8046 Zürich, Switzerland

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