New Year Offer End Date: 30th April 2024
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Program

Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery

Precision in Every Pixel: Elevating Agriculture with Satellite Imagery and AI

Skills you will gain:

About Program:

Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery is a hands-on workshop that teaches how to use satellite data and AI to optimize agriculture. Participants will learn to analyze NDVI time-series data for crop health monitoring, yield prediction, and precision farming.

Aim: The workshop aims to teach participants how to use satellite imagery and NDVI time-series analysis, combined with AI, to monitor crop health, predict yields, and implement sustainable farming practices for improved productivity.

Program Objectives:

What you will learn?


📡 Day 1 — Introduction to NDVI and Satellite Imagery

  • Focus: Introduction to NDVI and satellite imagery for crop monitoring
  • Key Topics:
    • Understanding NDVI and its role in crop health monitoring
    • Introduction to remote sensing and satellite platforms (Sentinel, Landsat)
    • Exploring the importance of time-series analysis in agriculture
  • Hands-on (Google Colab):
    • Task: Access and process satellite imagery, perform basic NDVI calculation using Google Earth Engine and Python


🌾 Day 2 — Time-Series Analysis and Crop Monitoring

  • Focus: Time-series analysis for monitoring crop health and growth patterns
  • Key Topics:
    • Overview of time-series data and its significance in agriculture
    • Analyzing NDVI time-series data to monitor seasonal changes and crop health
  • Hands-on (Google Colab):
    • Task: Process and analyze multi-temporal NDVI data, identify crop stress, growth patterns, and yield forecasts using Python and Google Earth Engine


🌱 Day 3 — AI in Agri-Tech and Predictive Modeling

  • Focus: Introduction to AI and machine learning for precision agriculture
  • Key Topics:
    • AI techniques for crop yield prediction, disease detection, and resource management
    • Applying machine learning models to NDVI data for actionable insights in agriculture
  • Hands-on (Google Colab):
    • Task: Build predictive models for crop yield and disease detection using Python, explore case studies on AI applications in agriculture

Mentor Profile

Fee Plan

INR 1999 /- OR USD 50

Get an e-Certificate of Participation!

2024Certfiacte

Intended For :

  • Agriculture Professionals: Those involved in precision agriculture, crop monitoring, and farm management.
  • Data Scientists & Engineers: Individuals with an interest in applying machine learning, AI, and remote sensing to agriculture.
  • Researchers & Academicians: Those working in the fields of agricultural science, environmental science, and Agri-Tech innovation.
  • Students: Graduate and postgraduate students specializing in agriculture, environmental science, data science, or related fields.
  • Industry Professionals: From sectors including Agri-Tech, sustainable farming, and remote sensing technology.

Career Supporting Skills

Program Outcomes

  • Analyze NDVI Data to assess crop health and growth.
  • Apply AI to predict yields and detect diseases.
  • Use Remote Sensing Tools like Google Earth Engine and Python for data analysis.
  • Implement Sustainable Practices to optimize resources and enhance productivity.
  • Translate Insights into Action for precision agriculture and smarter farming solutions.