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.
En menos de dos décadas, en Bolivia estamos viendo cómo, por un lado, se consolida un modelo agrario dominante de agricultura empresarial a gran escala y, por otro, la agricultura a pequeña escala de campesinos e indígenas, que todavía muchos creemos que es la que provee la mayor parte de los alimentoso que consumimos.
En menos de dos décadas, en Bolivia estamos viendo cómo, por un lado, se consolida un modelo agrario dominante de agricultura empresarial a gran escala y, por otro, la agricultura a pequeña escala de campesinos e indígenas, que todavía muchos creemos que es la que provee la mayor parte de los alimentoso que consumimos.
En menos de dos décadas, en Bolivia estamos viendo cómo, por un lado, se consolida un modelo agrario dominante de agricultura empresarial a gran escala y, por otro, la agricultura a pequeña escala de campesinos e indígenas, que todavía muchos creemos que es la que provee la mayor parte de los alimentoso que consumimos.