UMD Global Land Analysis and Discovery team

05/27/2026

We’re excited to see NASA spotlight the impact of DIST-ALERT in helping organizations monitor and respond to land and forest change around the world in near real time.

Developed through a collaboration between NASA OPERA and the UMD Global Land Analysis and Discovery team, DIST-ALERT leverages Harmonized Landsat and Sentinel-2 (HLS) data to provide rapid, global vegetation disturbance alerts every few days. The system is already supporting applications ranging from environmental compliance and sustainable supply chains to conservation and habitat protection.

The NASA feature highlights how DIST-ALERT is helping:
🌎 Detect unauthorized land clearing and construction in New England
🌲 Support sustainable forestry and supply chain transparency across the US, Canada and the EU
🐒 Protect critical chimpanzee habitat in East Africa

We’re proud to contribute to tools that turn Earth observation science into actionable information for decision-makers worldwide.

Read the full NASA story here: https://science.nasa.gov/missions/landsat/three-ways-that-a-new-land-monitoring-system-is-transforming-how-we-manage-forests/

DIST-ALERT, a global land change monitoring system, is revolutionizing forest management.

04/30/2026

“Generally speaking, a good year is a good year,” said Matt Hansen, a professor at the University of Maryland and director of the UMD Global Land Analysis and Discovery team, which contributed forest-loss data to the report. “But you need good years forever if you’re going to conserve the tropical rainforest.”

In 2025, the world razed less forest than any other year in the last decade. The bad news: global warming is making wildfires more frequent and intense.

04/29/2026

🌍 The 2025 Global Tree Cover Loss Map update from the UMD Global Land Analysis and Discovery team in collaboration with Global Forest Watch at the World Resources Institute is now available!

This latest release provides valuable insights into global forest change, helping researchers, policymakers, and environmental practitioners better understand patterns of tree cover loss worldwide.

Explore and download the data here:

🌲 Global Tree Cover Loss:
https://glad.earthengine.app/view/global-forest-change

🔥 Global Tree Cover Loss Due to Fire:
https://glad.earthengine.app/view/global-forest-loss-due-to-fire

Access to timely, high-quality forest monitoring data is essential for supporting conservation efforts, climate action, and sustainable land management.

Take a look and explore the latest updates!



UMD- Department of Geographical Sciences-Students & Alumni

04/29/2026

Tropical primary rainforest loss dropped in 2025 after record-breaking loss in 2024. But forest loss remains high, and fires pose a growing threat.

2025 data from UMD Global Land Analysis and Discovery team is now available on Global Forest Watch.

Countries like Brazil, Colombia, Indonesia and Malaysia are showing it’s possible to quickly slow forest loss with stronger policies and enforcement.

However, climate-driven fires are a dangerous new normal, threatening to reverse this progress. Plus, demand for commodities like cattle, soy, palm oil and gold is driving forest loss in Latin America and Southeast Asia.

Read the full analysis here on World Resources Institute's living report on forests, the Global Forest Review 👉 https://bit.ly/4tEjQm7

🌎 Explore the data on Global Forest Watch: https://bit.ly/48suuUq
🌍 Learn more about how the data compares to other national estimates: https://bit.ly/3QFdAMe
🌏 Check out the data on WRI’s new innovative, AI-powered system: https://bit.ly/48sU4Zu

Our thanks to WRI Africa, WRI Brasil, WRI Indonesia, WRI Colombia and WRI Europe for their invaluable contributions to this analysis.

04/23/2026

🌍 New Publication from the UMD Global Land Analysis and Discovery team 🌱

We’re proud to congratulate lead authors Ahmad Khan and Peter Potapov, along with their colleagues from the University of Maryland and World Resources Institute, on the new paper in Remote Sensing of Environment: “Global annual cropland dynamics 2015–2024.”

This study presents the first operational, annual global cropland dataset at 30 m resolution, using Landsat Analysis Ready Data and advanced machine learning to map cropland extent and change from 2015 to 2024.

🔍 Key findings:

- Global cropland area increased by ~6% (2015–2024), continuing a longer-term rise of nearly 14% since 2003;

- Africa and South America led recent growth, with the largest national-scale increase observed in Brazil;

- About one-third of new cropland came from conversion of natural vegetation or irrigation expansion in drylands;

- Despite expansion, cropland per capita is declining, underscoring mounting pressure on global food systems.

By combining consistent satellite observations with scalable modeling, this work provides critical insights into how food production, land use, climate, and socio-economic forces are reshaping the Earth’s surface.

📊 Open data & tools:

Global annual cropland dataset (2015–2024): https://glad.umd.edu/dataset/annual-croplands

Landsat Analysis Ready Data (GLAD-ARD):
https://glad.umd.edu/ard

📄 Read the paper:
https://authors.elsevier.com/sd/article/S0034-4257(26)00208-7

This open-access dataset supports applications in food security monitoring, sustainable land management, and SDG reporting, and reflects the GLAD Lab’s commitment to transparent, operational Earth observation.

👏 Congratulations again to Ahmad, Peter, and the entire team on this impactful contribution!



UMD- Department of Geographical Sciences-Students & Alumni

03/26/2026

New publication: An accurate 10 m annual crop map product of maize and soybean across the United States. Congratulations to the team of UMD GLAD co-authors led by Dr. Haijun Li! 🎉

Read the article (open access): https://essd.copernicus.org/articles/18/2227/2026/
Explore the data: https://glad.earthengine.app/view/us-crop-map
Download the data: https://glad.umd.edu/dataset/mapping-crops-10-m-resolution-united-states

Abstract. High-resolution crop maps over large spatial extents are fundamental to many agricultural applications; however, generating high-quality crop maps consistently across space and time remains a challenge. In this study, we improved a workflow for crop mapping and developed an openly availabl...

11/14/2025

UMD GLAD's Professor Matthew Hansen co-authored a new blog post exploring the connection between land-use change and climate change. Read the full write-up here:
https://www.wri.org/insights/land-use-climate-change-feedback-loop

The article features several UMD GLAD products:

🌲 Global Tree Cover Loss
https://glad.earthengine.app/view/global-forest-change

🔥 Global Tree Cover Loss Due to Fire
https://glad.earthengine.app/view/global-forest-loss-due-to-fire

📡 DIST-Alerts (Near-Real Time Vegetation Disturbance Alerts)
https://glad.earthengine.app/view/dist-alert

UMD- Department of Geographical Sciences-Students & Alumni

Land-use change has long been recognized as a major contributor to global warming. Deforestation and agriculture alone account for nearly 25% of human-caused greenhouse gas (GHG) emissions.

10/08/2025

🚀 Big news from the UMD GLAD Lab!

Our team has published a major study in Nature Communications led by Amy Pickens, unveiling DIST-ALERT, the first system to globally track land surface change in near real time.

Using data from five satellites (Landsat 8/9 and Sentinel-2A/B/C), DIST-ALERT achieves a 1–4 day revisit rate, allowing scientists to detect changes driven by people and nature, such as agricultural expansion, deforestation, fires, drought, and mining, faster and with greater precision than ever before.

As Amy explains in the UMD BSOS feature, “DIST-ALERT monitoring in such a low-latency mode enables data to be more actionable; not just for policymaking, but for actually responding to individual events.”

This system is already being integrated into platforms like Global Forest Watch, expanding alerts from tropical forests to global coverage, which is a major leap for environmental transparency and response.

📄 Read the paper: https://doi.org/10.1038/s41467-025-64014-9

🛰 Explore the DIST-ALERT map: https://glad.earthengine.app/view/dist-alert

📖 Read more in the UMD BSOS feature: https://bsos.umd.edu/featured-content/umd-researchers-create-first-system-track-near-real-time-changes-global-land-cover



UMD- Department of Geographical Sciences-Students & Alumni

An operational satellite-based monitoring system using NASA/USGS and ESA imagery enables rapid tracking of global land change, with the area of conversion due to direct human action and fire equaling the size of California in 2023.

10/01/2025

❓Why would a scientist who tracks forests speak out about political AI? 🤖

Andres Hernandez-Serna of UMD Global Land Analysis and Discovery team GLAD warns: the AI that maps forests is now shaping political messages without labels or accountability.

Learn more: https://go.umd.edu/political-ai-costs

09/16/2025

📢 New CEOS LPV Global Land Cover Map Validation Guidelines Published! 🌍

We are proud to share that several members of the UMD GLAD team played key roles in developing the newly released Global Land Cover Map Validation Guidelines: https://doi.org/10.5067/doc/ceoswgcv/lpv/lc.001

👏 Contributions from our team included:

Alexandra Tyukavina – Lead and Editor
Anna Komarova – Co-editor
Xiao-Peng Song – Chapter Lead
Amy Pickens, Peter Potapov, and Matthew Hansen – Chapter Contributors

The updated guidelines build on the foundational Strahler et al. (2006) document and provide:
✅ A comprehensive overview of two decades of methodological studies
✅ Summary of key terminology and principles of map accuracy assessment
✅ Requirements for reporting sampling design, response design, and accuracy metrics
✅ Methods for land cover class area estimation as a complement to map accuracy assessment
✅ Approaches for accounting for reference data errors
✅ An overview of unbiased estimators for various sampling designs
✅ Guidance on emerging practices such as operational validation updates, near real-time map validation, and local map quality metrics
✅ Examples of validation studies implementing the methods in practice

This resource is designed to support both newcomers to land cover validation (such as graduate students and practitioners) and experienced researchers looking to systematize their knowledge.

We are excited to see GLAD’s continued leadership in advancing global standards for Earth Observation products! 🚀

CEOS Land Product Validation website