Cecil

Cecil has partnered with Kanop to provide its global forest screening and monitoring datasets on Cecil's nature data platform. This post introduces Kanop's datasets, explains how to access them through Cecil, and outlines how they support use cases across the private and public sectors.

At New York Climate Week, Cecil worked with The Landbanking Group + Earthmover to host two events on nature data. - During our Nature Data Breakfast, Alex Logan, Tom Walker and Jamie Batho discussed the critical role accessible nature data will play in accelerating innovations such as Landler. - At our data + dumplings meetup, Alex Logan and Ryan Abernathey presented solutions need to unlock accessible nature + climate data, whilst Tom Nicholas explained how [C]Worthy are working with data to support ocean carbon removal. The sentiment across both events was clear - accessible data sits at the foundation of a nature positive economy. We need to keep working on solutions that make this data accessible for the innovators, landowners and corporates driving progress. Where to find us next? - Data + Dumplings meetup - London, 23rd October. - Celebrating Nature Tech - Cali, 25th October - Data + Dumplings meetup - NYC, 13th November. Links to RSVP for these events in the comments below.

Yesterday, Planet announced the world’s first global scale forest carbon monitoring system at 3-meter resolution. Tree-level data, for every forest on Earth, every quarter. Cecil has partnered with Planet because we believe these datasets are valuable to a wide variety of teams across the corporate, finance, and nonprofit sectors. We're excited to make these datasets accessible and enable teams to analyse, baseline, and monitor forest biomass at scale.

Cecil has partnered with Planet to provide its Forest Carbon Diligence and Forest Carbon Monitoring datasets on the Cecil nature data platform. This post introduces the two datasets, explains how to access them through Cecil, and briefly outlines how these datasets support use cases across the private and public sectors.

Over the last six months, we’ve explored the technical, scientific, and commercial challenges of accessing nature data. In our latest newsletter, we summarise these barriers and explain our approach to solving them. We also share our documentation which includes details on our API, the datasets we currently support, and the science behind our solution. Links to the newsletter and documentation in the comments below 👇

Nature data products bridge various disciplines across environmental science, spatial data analysis, and software engineering. This complexity creates a unique need for useful documentation to support effective understanding and use of nature datasets. In this newsletter, we unpack the challenges teams are facing accessing this documentation and suggest key principles to help overcome them. Link in comments below.

Advanced technologies like remote sensing satellites have drastically increased the amount of nature data generated. In 2023, over 100 TB of satellite imagery was collected daily, with 20,000 more satellites expected by 2030. New tools like hyperspectral sensors, camera traps, and bioacoustics devices are also driving this data growth. In this newsletter, we explore the challenges that large volumes of data are creating for teams with raster-based nature data workflows and how spatial indexes have emerged as a potential solution. Link in the comments below.

Spatial data has evolved through numerous formats. netCDF, released in 1990, has had ongoing updates as recent as 2023. The introduction of new formats and standards, like fiboa by Taylor Geospatial Engine and Cloud-Native Geospatial Foundation, reflects ongoing efforts to improve the ecosystem and meet changing data needs. In Newsletter 4, we explore key spatial data concepts and dive into various formats, standards, and libraries. Link in the comments.

Finding the right nature data for analysis workflows can take months. Data is scattered across countless repositories and most open data platforms are tailored for nature-specific needs. This forces nature data users to rely on spreadsheets to manually track datasets and their limitations. In the third issue of our Nature Data Newsletter, we explain why finding nature data is so difficult. Link in the comments.

Selecting nature datasets. We spoke to over 30 nature data users about the challenges they face finding nature data. Whether searching for, shortlisting, or evaluating datasets - they felt unsupported by existing tools, making the process frustrating and time consuming. However, we also found something encouraging; many teams have developed consistent and repeatable criteria to effectively select datasets for their analysis. We summarised this criteria in our second newsletter to help guide your next search for nature data. Link to the full newsletter in the comments.