LANDac Annual Conference 2025
Plurality of Knowledge: The future of land governance in shifting global contexts
Utrecht, the Netherlands | 2-4 July 2025
Call for Sessions opens 18 December 2024
Utrecht, the Netherlands | 2-4 July 2025
Call for Sessions opens 18 December 2024
The sixteenth session of the Conference of the Parties (COP16) of the United Nations Convention to Combat Desertification (UNCCD) will take place in Riyadh, Saudi Arabia, from 2 to 13 December 2024.
Synthetic Aperture Radar (SAR) has the capability to observe the Earth's surface both day and night and through most weather conditions, making it an ideal sensor to support a wide range of science and applications.
From tree planting in the Maldives and Kenya to the unveiling of large-scale city murals in the United States and activities in zoos across Ireland, Singapore and India, millions of people are coming together to mark this year’s Day.
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Earth Observations for Humanitarian Applications. Refugees, internally displaced people (IDPs), and other displaced populations are made more vulnerable to climate change impacts due to their socio-political marginalization. This three-part, intermediate training presents concrete strategies for mapping localized climate conditions with risks faced by refugee and IDP communities around the world.
The training will focus on flood risk assessments and specific challenges for assessing flood risk in refugee and IDP camps; gauging long-term heat stress in refugee camps and the challenges with decision making surrounding heat risk; and monitoring drought effects on agricultural landscapes in refugee settings using Earth observations (EO) to explore the correlations between anomalies in crop productivity and weather-based factors
The IATI Members' Assembly and Community Exchange 2024 are taking place in Bogotá, Colombia.
This seminar will be an opportunity to deepen and consolidate the various issues raised in the initial contributions proposed for the collective work. Participants will have the opportunity to explore in depth the fundamental issues related to citizen participation in land governance, with a focus on the specific challenges faced in Africa. In-depth discussions will analyze the root causes of land problems, identify gaps in existing public policies, and formulate concrete proposals for effective reforms. Furthermore, the seminar will provide a platform for a comprehensive analysis of the role of alumni as an essential component of NELGA's sustainability in the sub-region and ends up with a setting up and launching of the NELGA AC alumni network
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Introduction to Lightning Observations and Applications. This three-part, introductory training focuses on global and regional lightning data products that can be applied to disaster risk preparedness.
As the intensity and frequency of extreme weather events are likely to increase due to climate change impacts, lightning activity will likely increase as well, causing more power outages, increased risks of wildfire ignition, and increased numbers of injuries and fatalities. Therefore, information about lightning activity is critical for better preparedness against these disasters.
Theme: Smart Cities in Africa for the 21st Century
NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online webinar series: Large Scale Applications of Machine Learning using Remote Sensing for Building Agriculture Solutions. Remote sensing data is becoming crucial to solve some of the most important environmental problems, especially pertaining to agricultural applications and food security. Participants will become familiar with data format and quality considerations, tools, and techniques to process remote sensing imagery at large scale from publicly available satellite sources, using cloud tools such as AWS S3, Databricks, and Parquet. Additionally, participants will learn how to analyze and train machine learning models for classification using this large source of data to solve environmental problems with a focus on agriculture.