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Offered By: IBMSkillsNetwork

Analyze Forest Cover Loss by Wildfires with Geospatial APIs

Analyze data to assess wildfire impacts, visualize forest loss, and understand environmental changes. Use geospatial APIs to determine the change in Above Ground Biomass (AGB). Leverage a rich repository of geospatial and temporal data, along with an advanced analytics engine capable of executing complex queries to uncover relationships between different environmental factors. You will use Python to visualize wildfire-affected areas and leverage the power of technology to better understand the environmental impacts.

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Guided Project

Data Science

4.5
(2 Reviews)

At a Glance

Analyze data to assess wildfire impacts, visualize forest loss, and understand environmental changes. Use geospatial APIs to determine the change in Above Ground Biomass (AGB). Leverage a rich repository of geospatial and temporal data, along with an advanced analytics engine capable of executing complex queries to uncover relationships between different environmental factors. You will use Python to visualize wildfire-affected areas and leverage the power of technology to better understand the environmental impacts.

In this guided project, you will explore environmental intelligence, using geospatial APIs to analyze forest loss caused by wildfires. By following a step-by-step use case, you'll learn how to take advantage of advanced geospatial and temporal data to understand and visualize the impacts of wildfires on forests. These APIs give you the ability to engage with a large repository of geospatial data, coupled with a powerful analytics engine to execute complex queries and uncover relationships between environmental factors.

When you complete this project, you'll understand how to use Python to visualize changes in the Above Ground Biomass (AGB) in wildfire-affected areas and assess the extent of forest loss. You'll gain valuable skills in environmental impact analysis, disaster recovery, and the intersection of technology and environmental science. This hands-on experience will give you insight into sustainable forestry management and ecosystem protection techniques, which are crucial for mitigating the impacts of climate change.

This project features IBM Environmental Intelligence APIs, empowering individuals and organizations to address pressing environmental challenges with data-driven insights. By understanding and analyzing forest loss due to wildfires, you contribute to sustainable land stewardship and environmental resilience. Build the skills you need to be part of the movement towards responsible land management and a more sustainable future.

Note: To complete this project, you must register to receive free access to the IBM Environmental Intelligence API keys. The process is simple and steps are provided in the project.


What you'll learn

After completing this project, you will:
  • Understand the fundamentals of geospatial APIs and their role in environmental intelligence.
  • Learn how to use Python to interact with geospatial APIs and visualize data.
  • Develop skills in identifying and analyzing areas affected by forest loss from wildfires.
  • Gain practical experience in environmental impact assessment and disaster recovery using data-driven insights.

What you'll need

To successfully complete this guided project, you will need:
  • Basic knowledge of Python programming.
  • Access to the IBM Skills Network Labs environment, which comes pre-installed with necessary tools such as Docker.
  • A current version of a web browser such as Chrome, Edge, Firefox, Internet Explorer, or Safari for the best experience.

Get started on this journey to enhance your technical skills while contributing to the analysis of critical environmental challenges. By the end of this project, you will be well-equipped to address complex environmental issues using cutting-edge geospatial technology.

Estimated Effort

30 Minutes

Level

Beginner

Skills You Will Learn

API, Data Visualization, Environmental Intelligence, Geospatial, Python

Language

English

Course Code

GPXX0RY6EN

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