Glossary
Permanence ensures that positive environmental outcomes, such as carbon sequestration, last over time and are not undone by future activities or land use changes.
Land assets uploaded to Landler. Includes both owned and not-owned land.
A field or polygon of land uploaded or identified by the user, defined by plot boundaries.
A group of plots logically bundled together either automatically or by the user to be monitored on the platform.
The container for * Physical assets owned or needed by the user (physical asset registry) * Digital nature assets owned by the user (digital asset registry)
A specific action, method, or technique applied to a Plot. This is a predefined list (e.g., No-till farming, Cover crops, Reforestation, Irrigation, Fertilizer application, etc.) Link to list of Practices
The RDI tracks the status of natural capital claims, indicating whether they are in a state of performance or temporarily non-performing, helping assess the health of investments.
Uses radio waves to detect objects, measure distances, and analyze surface features. Used in synthetic aperture radar (SAR) for all-weather, day-and-night remote sensing.
A machine learning algorithm used for classifying satellite imagery into land cover types by aggregating multiple decision trees.
Regenerative practices aim to restore the land's health over time, focusing on long-term sustainability by improving soil quality, water retention, and biodiversity.
The acquisition of information about an object or phenomenon without direct physical contact, typically using satellite or aerial sensors. Used in environmental monitoring, agriculture, and disaster response.
A generated document, accessible on the platform or as a download, created for stakeholders like investors, regulators, or internal teams. A report aggregates data from other platform entities such as Measurements, Assets, Valuation and, optionally, adds context either through LLM or TLG team support. Report formats: Webpage, downloadable PDF, Excel, JSON file generated by API endpoint Link to list of Reports
SAI is an initiative promoting sustainable agricultural practices, aiming to improve the economic, social, and environmental aspects of food production.
SBTI drives ambitious climate action by helping companies set targets to reduce emissions in line with climate science to limit global warming to well below 2°C.
SBTN is an initiative that helps companies set science-based targets for nature, including biodiversity, water, and land, aiming to reduce their negative environmental impact.
SEEA-EEA is an accounting framework that integrates environmental and economic data, helping nations measure the value of ecosystems and natural resources in their economy.
The SFRD mandates financial institutions to disclose the sustainability risks and impacts of their investments, encouraging greater transparency in the finance sector.
Measures global soil moisture at ~9km resolution with a 3-day revisit period, improving drought and flood prediction models.
Scope 3 emissions represent a significant part of a company’s total emissions, focusing on the full life cycle of products and services, including those of suppliers and customers.
A radar imaging satellite providing SAR data (spatial resolution of 5m–20m) with a 6-day revisit cycle. Used for flood monitoring, land deformation studies, and sea ice tracking.
Provides high-resolution (10m–60m) multispectral imagery with a 5-day revisit period. Used for land use classification, forest monitoring, and agricultural applications.
A geographic point (latitude/longitude) used as a reference for low-resolution or area-based measurements where a specific plot boundary is not required.
The amount of water contained in soil, monitored via satellites and in-situ sensors. Key for drought prediction, agricultural productivity, and climate modeling.
The level of detail a remote sensing image provides, determined by the pixel size of the imagery. High-resolution images capture finer details, useful for urban mapping and precision agriculture.
The ability of a sensor to distinguish between different wavelengths of light, affecting its capability to detect specific materials or vegetation types. Hyperspectral sensors have the highest spectral resolution.