Enterprise Services
Climate Engine provides services to help organizations navigate the wealth of satellite data to deliver high-value, actionable insights at global and local scales.
Leverage the power of spaceborne data.
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We provide services and support to organization to help them derive benefits from bringing Earth observation data products and analytics into operational systems.
Space-borne data products and earth system analytics have transformative potential.
For organizations to take advantage of the promise of space-borne data, challenges need to be overcome. These include managing the scope and scale of the data, the need to convert raw data into actionable information, and bringing the best available science into operational contexts.
Climate Engine was formed to help organizations navigate the overwhelming wealth of data to extract key insights and deliver them to the operations of organizations through APIs.
Climate Engine helps identify value, apply appropriate scientific models, and deliver outputs into operations.
The following is the process by which Climate Engine engages with organizations to deliver valuable insights at scale:
01
Use Case Identification
The first step is to identify use cases within an organization where remote sensing data and analytics can materially improve their mandates outcomes. This includes:
- OBJECTIVE IDENTIFICATION
- STAKEHOLDER RESEARCH
- PROOF OF CONCEPT SCOPING
- PROJECT PLANNING
- USER REQUIREMENTS
02
Data Identification
With the use cases in mind, the most relevant data sources need to be identified. This includes reviewing both public and private sources to identify the best fit in terms of budget, desired outcomes, science applicability, spectral bands, timescales, and geospatial scales. Imagery can also include drones and other types of sensors. Steps include:
- IDENTIFYING RELEVANT SPATIAL SUMMARIES
- IDENTIFYING RELEVANT TEMPORAL SCALES
- DETERMINING BUDGET CONSTRAINTS
- OPTIONS ANALYSIS
- ANALYSIS OF DATA RIGHTS AND USAGE
- EXECUTING PROCUREMENTS
03
Data Wrangling
Once raw data sources are identified, data is wrangled into the Climate Engine system for processing. This includes:
- DATA INGESTION
- DATA NORMALIZATION
- DATA REPROJECTION
- DATA CATALOGUE
- DATA SEARCH & DISCOVERY
- DATA STORAGE
04
Scientific Model Application
Once in Climate Engine, scientific models are applied to the data sources in order to derive the required insights. This includes:
- OPTIONS ANALYSIS
- SCIENTIFIC VALIDATION
- MODEL CODING
- MODEL OPTIMIZATION
- EXECUTING PROCUREMENTS
05
API Configuration / Enterprise Solution
With the data system in production, APIs are configured as end-points for integration into operational systems. For larger organizations or governments, a Climate Engine instance can be deployed as an Enterprise Solution within their own Google Cloud Platform. This includes:
- API DEVELOPMENT
- API CONFIGURATION
- AUTHENTICATION CONFIGURATION
- GOOGLE CLOUD FOUNDATIONS
- CLIMATE ENGINE ACCELERATORS
- INTEGRATION WITH GOOGLE LOOKER
- ONBOARD TO SOLUTION SUPPORT
Why Earth Systems Data?
The development and growth of the human built systems we rely on (infrastructure, health, agricultural and economic) have been predicated on the belief that the Earth’s various systems will function the same way in the future as they have in the past. While the specifics of what the future looks like are largely dependent on how swiftly we act to reduce our greenhouse gas emissions, habitat degradation, and pollution, what we do know for certain is that the future will not look like the past.
This fact carries major risks to our infrastructure, health, agricultural, and economic systems.
Fortunately, Earth observation data and applied analytics can be a key tool to help reduce our impact and adapt to these changes. By bringing this data into operations, organizations can reduce their exposure risk and capture opportunities.