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Description
Canesis Data offers exploration professionals an economical means to access an extensive and continuously expanding collection of seismic and well data sourced from all over the world. It has compiled one of the most comprehensive assortments of non-proprietary legacy data found anywhere. The data comes from both public domain and industry sources, is refined, and made available for public purchase. Numerous datasets undergo scanning and vectorization, while others are original digital data, as specified. With a history of success, Canesis Data leverages its vast expertise to tackle the various challenges that arise in restoring legacy data, which can often be in poor condition or delicate. The company not only processes publicly available data independently but also engages in collaborative efforts in scenarios like open licensing rounds. This valuable data is available for sale to suitably qualified companies during licensing periods and is processed to meet the same high standards as proprietary services, ensuring reliability and quality for all clients. Additionally, Canesis Data continually seeks to innovate and improve its offerings, making it a trusted partner in the exploration industry.
Description
Google Earth Engine serves as a cloud-centric platform designed for the scientific examination and visualization of geospatial data, granting users access to an extensive public archive containing over 90 petabytes of analysis-ready satellite imagery alongside more than 1,000 carefully curated geospatial datasets. This rich collection boasts over five decades of historical imagery that is refreshed daily, with pixel resolutions reaching as fine as one meter, showcasing datasets from sources such as Landsat, MODIS, Sentinel, and the National Agriculture Imagery Program (NAIP). Through its web-based JavaScript Code Editor and Python API, Earth Engine empowers users to perform analyses on Earth observation data while employing machine learning techniques, thereby enabling the creation of sophisticated geospatial workflows. The platform's seamless integration with Google Cloud facilitates large-scale parallel processing, allowing for thorough analyses and efficient visualization of Earth data. Furthermore, Earth Engine's compatibility with BigQuery enhances its capabilities, making it a versatile tool for users in various fields. This unique combination of features positions Google Earth Engine as an essential resource for researchers and professionals working with geospatial information.
API Access
Has API
API Access
Has API
Integrations
GeoPandas
Google Cloud Analytics Hub
Google Cloud BigQuery
Google Cloud Platform
JavaScript
Python
WeatherNext
Integrations
GeoPandas
Google Cloud Analytics Hub
Google Cloud BigQuery
Google Cloud Platform
JavaScript
Python
WeatherNext
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$500 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Canesis Data
Country
United Kingdom
Website
canesis.net
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/earth-engine
Product Features
Product Features
GIS
3D Imagery
Census Data Integration
Color Coding
Geocoding
Image Exporting
Image Management
Internet Mapping
Interoperability
Labeling
Map Creation
Map Sharing
Near-Matching
Reverse Geocoding
Spatial Analysis