COVID-19 may have forced the 50th anniversary of Earth Day to be commemorated online last year, yet millions of people participated in calls to action. As we begin to look beyond the pandemic, however, it's vital to remember that we cannot go back to business-as-usual as far as our planet is concerned.
COVID-19 may have forced the 50th anniversary of Earth Day to be commemorated online last year, yet millions of people participated in calls to action. As we begin to look beyond the pandemic, however, it's vital to remember that we cannot go back to business-as-usual as far as our planet is concerned.
COVID-19 may have forced the 50th anniversary of Earth Day to be commemorated online last year, yet millions of people participated in calls to action. As we begin to look beyond the pandemic, however, it's vital to remember that we cannot go back to business-as-usual as far as our planet is concerned.
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 course has been developed in response to the concerns about increasing large-scale land acquisitions and the need to increase investment in agriculture. The objective is to provide guidance to government authorities engaged in investment promotion, approval, and monitoring activities at all stages of the investment cycle.
This course has been developed in response to the concerns about increasing large-scale land acquisitions and the need to increase investment in agriculture. The objective is to provide guidance to government authorities engaged in investment promotion, approval, and monitoring activities at all stages of the investment cycle.
This course has been developed in response to the concerns about increasing large-scale land acquisitions and the need to increase investment in agriculture. The objective is to provide guidance to government authorities engaged in investment promotion, approval, and monitoring activities at all stages of the investment cycle.