Private Sector
Climate Engine helps companies navigate the wealth of Earth observation data to deliver high-value, actionable insights at global and local scales.
Leverage Google Cloud + Earth observation data.
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Climate Engine provide services and support to help companies derive benefits from bringing Earth observation analytics into their decision making systems.
Companies face a dual challenge.
They are increasingly asked to improve their sustainability and reduce their carbon footprints. At the same time, they are experiencing increasing risks to their supply chains, assets, and portfolios due to climate change.
To meet both these challenges, Earth observation data can be a powerful tool. Petabytes of data are being generated every day that can be converted into actionable business intelligence. To take advantage of this promise, relevant data needs to be converted into actionable insights.
Climate Engine helps companies navigate the overwhelming wealth of data to extract key insights and deliver them into decision making contexts through its Enterprise deployment of Google Earth Engine.
Climate Engine helps companies identify value and deliver outputs into decision making systems.
The following is the process by which Climate Engine engages with companies to deliver valuable insights at scale:
01
Use Case Identification
The first step is to identify use cases within a company where Earth observation data and analytics can help reduce risks, provide insights, or improve its sustainability. 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 Climate Engine Enterprise Google Cloud solution 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 decision making systems. The Climate Engine Enterprise deployment of Google Earth Engine is installed on the client’s Google Cloud instance. Steps include:
- API DEVELOPMENT
- API CONFIGURATION
- AUTHENTICATION CONFIGURATION
- GOOGLE CLOUD FOUNDATIONS
- CLIMATE ENGINE ACCELERATORS
- INTEGRATION WITH GOOGLE LOOKER
- ONBOARD TO SOLUTION SUPPORT
Why Earth Observation Data?
The development and growth of the human systems we rely on (infrastructure, health, agricultural, and economic) is predicated on the belief that the Earth’s systems upon which they are built will function the same way in the future as they have in the past. While the specifics of what the future looks like are dependent on how swiftly we act to reduce our collective impacts, what we know for certain is that the present and the future will not look like the past.
This carries major risks to supply chains, infrastructure, and assets as well as new expectations and demands from regulators, shareholders, stakeholders, and customers.
Fortunately, Earth observation data can be a key tool to help reduce corporate risks and environmental footprints while opening up possibilities for new markets, products, and opportunities.