Patches of forest cleared and tended by Indigenous communities but lost to time still show more food bounty for humans and animals than surrounding forests.
Patches of forest cleared and tended by Indigenous communities but lost to time still show more food bounty for humans and animals than surrounding forests.
Patches of forest cleared and tended by Indigenous communities but lost to time still show more food bounty for humans and animals than surrounding forests.
Advancing women’s land rights is a priority for the international development agenda. Yet, there is no consensus on which rights should be monitored and reported. Three indicators of women’s property rights are widely used in the literature. Each captures a different aspect of women’s land rights, but a recent paper explores the extent to which these different rights are held by the same person, using data from six African countries.
Advancing women’s land rights is a priority for the international development agenda. Yet, there is no consensus on which rights should be monitored and reported. Three indicators of women’s property rights are widely used in the literature. Each captures a different aspect of women’s land rights, but a recent paper explores the extent to which these different rights are held by the same person, using data from six African countries.
Advancing women’s land rights is a priority for the international development agenda. Yet, there is no consensus on which rights should be monitored and reported. Three indicators of women’s property rights are widely used in the literature. Each captures a different aspect of women’s land rights, but a recent paper explores the extent to which these different rights are held by the same person, using data from six African countries.
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.
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.
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.
This publication on Pro Poor Land Management is based on the Handbook on Best Practices, Security of Tenure and Access to Land. It briefly describes recent innovations at the global level in the field of pro poor land management. It shows how governments, including local government and other stakeholders, are coming to grips with implementing the land related principles enshrined in the Habitat Agenda at a practical level in the cities and towns.
This publication on Pro Poor Land Management is based on the Handbook on Best Practices, Security of Tenure and Access to Land. It briefly describes recent innovations at the global level in the field of pro poor land management. It shows how governments, including local government and other stakeholders, are coming to grips with implementing the land related principles enshrined in the Habitat Agenda at a practical level in the cities and towns.
This publication on Pro Poor Land Management is based on the Handbook on Best Practices, Security of Tenure and Access to Land. It briefly describes recent innovations at the global level in the field of pro poor land management. It shows how governments, including local government and other stakeholders, are coming to grips with implementing the land related principles enshrined in the Habitat Agenda at a practical level in the cities and towns.
