United Nations Sustainable Development Goal #15
UN Sustainable Development Goal #15
UN SDG #15
Life on Land

Tech Solutions Related To UN SDG 15: Life on Land

UN Sustainable Development Goal 15: Life on Land, aims to protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, halt and reverse land degradation, and halt biodiversity loss. Learn more about Life on Land in the US in our interactive report. Contact us for insights related to the 11,212 US organizations addressing UN SDG 15.

Discover tech solutions related to endangered species, land use, extinction and other key areas of biodiversity conservation below.

36 results
Technology
By UpstreamTech

Upstream Tech is a technology company that builds decision-making tools for environmental conservation to improve natural resource management. We harness technological advancements in remote sensing, computer science, and machine learning to create customizable planning and monitoring platforms for conservation organizations focused on agriculture, wetlands, water management, and beyond.

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Technology
By BioVinci

BioVinci -bringing modern data visualization, analytics, and machine learning to the new era of life sciences. Click. Drag. And drop. BioVinci makes it easier for scientists to analyze their data, and customize plots for publication.

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Service
By Ellipsis Earth

Ellipsis Earth can remotely identify, map and track plastic waste by harnessing the power of machine learning and aerial imagery. We partner with governments, corporations, academia and non-profits to produce engaging and thought-provoking media content for environmental education, based on our tech data, creating an ecosystem for environmental change.

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Technology
By Trace Genomics

Trace Genomics has developed the first analytics engine that learns as it maps the living soil. We are building the largest, most actionable body of soil intelligence, making thousands of agronomists and growers experts on what’s underground. Working collaboratively across the agriculture ecosystem, Trace Genomics helps growers optimize costs, manage risk and protect their soil as a capital asset.

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Technology
By Wild Me

Wild Me builds open software and artificial intelligence for the conservation research community. Our solution, Wildbook, blends structured wildlife research with artificial intelligence, citizen science, and computer vision to speed population analysis and develop new insights to help fight extinction.

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Technology
By Perennial

Perennial uses the world’s most advanced remote measurement technology for soil carbon sequestration and emissions. We fuse machine learning, ground observations, and remote sensing to map historical, present, and future soil carbon and land-based emissions at continent-level scales.

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Technology
By Fion

Detect fires when they start. Stop them before they spread. Fion’s machine learning model packages highly accurate fire prediction & detection, spread prediction and destruction estimation into custom dashboards for fire departments, forestry services, financial institutions and insurance companies.

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Technology
By Taranis

Taranis is a leading precision agriculture intelligence platform that uses sophisticated computer vision, data science and deep learning algorithms to effectively monitor fields. Taranis offers a full-stack solution for high precision aerial surveillance imagery to prevent crop yield loss due to crop diseases, insects, and weeds.

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Technology
By CropSafe

CropSafe is building the connected farm operating system utilizing satellite imagery and machine learning, allowing you to control everything happening on your farm in one place. CropSafe empowers you with more insights than previously possible, allowing growers like you, all across the world, to produce more efficiently - with less.

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Technology
By precursor SPC

Precursor gathers earth observation data from a network of proprietary multi-sensor ground stations and specialized satellite systems. The high-fidelity data is processed through Machine Learning (ML) algorithms to deliver real-time insights into the changing risks and potential impacts of unpredictable, recurring extreme geospatial events.

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