What is Environmental Data? Examples, Types, and Databases

Environmental Data Explained

Who Uses Environmental Data and For Which Use Cases?

Scientists are always in the hunt of high-end observational data sets mixed with simulations to understand and predict the behavior of the ecosystem with time. They collect, aggregate, and analyze environmental data to know more about the earth processes, test location, and parameterize and offer information to the common public and specific user groups. It helps them in solid planning related to infrastructure, environment, and energy usage.

The general public uses detailed environmental data to stay up-to-date on the existing condition of the environment. It helps them to take the necessary steps in order to minimize their carbon footprint on mother earth.

Policymakers do a thoughtful analysis of environmental data and use it to implement vital environmental policy changes. They also effectively harness advanced technology to close data gaps that have long hampered good policymaking and helps them find out the issue in time to take preventive action.

Companies across the globe are nowadays setting up specific goals in order to become more sustainable. They use environmental performance data to stay compliant with regulatory requirements and to attract sustainable investment.

What are Typical Environmental Data Attributes?

Collecting the following environmental data metrics is important:

Meteorological Data

• Temperature
• Wind speed
• Pressure
• Rain or snow
• Humidity level

Biodiversity Data

• Species abundance
• The total number of specific species type
• Species size or weight
• Population growth rate
• Mortality rate
• Life span/longevity

Socioeconomic and Occupational Health Data

• Total number of slums in a specific area
• Affected population per the state
• Health status of the communities
• Existing infrastructure facilities in a particular area

Pollution Data

• Air quality
• Groundwater quality
• Particulate matter
• VOCs, Ozone, and nitrogen dioxide levels
• Number of wildlife fires and open area burns

How is Environmental Data Typically Collected?

Environmental data collection typically includes solid planning, technical expertise, and a wide knowledge of environmental rules.

The elements of systematic planning include goals, schedule, project organization, data requirements, data collection methods, data quantity and quality, QA and QC needs, analytical methods – all of which ensure that the relevant and accurate data is gathered for the intended use.

Sources of environmental data include:

Statistical Surveys – You can carry out surveys to garner environmental statistics from a specific part of the population of interest

Administrative Records – Administrative data stored by the governments and other organizations can also be used for the generation of environmental

Remote Sensing and Thematic Mapping – Remote sensors obtain high-quality environmental data about the inaccessible or deadly regions and objects for a certain distance, usually with the help of satellite or air aircraft. This technology is usually used to collect and analyze forests, changes in soil erosion, pollution level, an estimate of the animal population, and the impact of natural disasters.

Monitoring Systems - Use field monitoring stations that capture all qualitative and qualitative environmental data aspects such as soil, air, water, or quality; meteorological or hydrological parameters. The best thing about this technique is that data is typically collected using verified scientific methods and constantly uses modeling to enhance data quality.

Scientific Research - Accurate environmental data is also collected via scientific research. This kind of information is usually available for free or low cost.

How to Assess the Quality of Environmental Data?

Environmental data quality matters a lot when it comes to making important decisions, evaluations, and conclusions related to the environment. That is why it is crucial to use appropriate data quality models and methodologies to achieve the desired outcome.

Here is a step-by-step guide to use while assessing environmental data quality:

Step 1: Understand the Sources and Collection Methods Well
When evaluating environmental data, make sure you are familiar with the sources and data collection methods. Also, the source must be legal, ethical, and 100% original to avoid any potential issues.

Step 2: Ask for References
Ask your data provider to provide you references of their past customers so that you can validate the quality of data. You can also reach out to their previous customers directly.

Step 3: Apply Data Testing (Sample Set)
Ask your data provider for a sample data set and then test it well. Analyze the results carefully and check if this is what you want.

How is Environmental Data Typically Priced?

If you fail to plan appropriately and model your unique environmental needs in advance, you will end up paying your data company more. Some of the more common pricing models we see are:

1. Subscription/Licensing: You need to subscribe to the data provider. After you get access to API, and this model type provides regularly updated datasets.

2. Pay Per Large Batch (one-time payment): You can also make a one-time payment for each larger batch of environmental datasets.

3. Tailored Quotes for Special Needs: If you have unique needs, you can explain this to your environmental data provider. Remember, your pricing will differ depending on your needs.

What to Ask Environmental Data providers?

The following are the key questions to consider asking your next environmental data vendor:

• Where and how was the data collected?
• How do you process and validate your environmental data?
• Can you provide me with a sample for testing?

Where Can I Buy Environmental Data?

You can explore our data marketplace to find a variety of Environmental Data tailored to different use cases. Our verified providers offer a range of solutions, and you can contact them directly to discuss your specific needs.

How is the Quality of Environmental Data Maintained?

The quality of Environmental Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.

How Frequently is Environmental Data Updated?

The update frequency for Environmental Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.

Is Environmental Data Secure?

The security of Environmental Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.

How is Environmental Data Delivered?

Environmental Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Environmental Data.

How Much Does Environmental Data Cost?

The cost of Environmental Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Environmental Data for your needs.

What Are Similar Data Types to Environmental Data?

Environmental Data is similar to other data types, such as Telecom Data, Weather Data, B2B Data, AI Training Data, and Automotive Data. These related categories are often used together for applications like Weather Analytics.