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DSTC-01695 Online (e-LMS) Advanced Postgrad

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

by - DSTC

Master Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery in 4 weeks through hands-on, project-based online training with DSTC.

★★★★★ Be the first to review • 3 Days · 4.5 hrs • e-Certificate Included
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From ₹2,500 + GST

Programme Parameters

Educational Level:
Advanced Postgrad
Duration & Workload:
3 Days (4.5 Hrs)
Delivery Mode:
Online (e-LMS)
Prerequisites:
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.

About This Course

Use satellite data and AI to optimize agriculture. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.

🎯 Program Aim

Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery is a hands-on course that teaches how to use satellite data and AI to optimize agriculture.

📋 Course Objectives

1. Apply Artificial Intelligence methods to authentic research and industry problems.
2. Assemble a documented case study that evidences your applied capability.

👥 Who Should Enroll?

• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence

🚀 Key Learning Outcomes

• Tangible, reproducible Artificial Intelligence work to show supervisors or employers.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.

💎 What You'll Gain

🎥

Live & Recorded Sessions

Lifetime access to class recordings
🎓

e-Certificate on Completion

Cryptographically verified credential
💬

Post-Programme Support

Direct access to mentors & council
💻

Hands-On Experience

Notebooks, real-world code & datasets

Curriculum Outline

Module 1 Sensors

Satellite Data Sources and Their Trade-offs

• Sentinel-2, Landsat and commercial constellations: revisit, resolution, cost
• Spectral bands, radiometric calibration and surface reflectance products
• Cloud masking and the gaps it leaves in a monsoon-season time series

Module 2 Indices

Vegetation Indices in Practice

• NDVI construction, saturation at high biomass and soil background effects
• EVI, NDRE, NDWI and choosing an index for the question at hand
• Comparability across sensors and why raw index values are not interchangeable

Module 3 Time Series

Building and Smoothing the Signal

• Compositing, gap filling and Savitzky-Golay or harmonic smoothing
• Phenology metrics: start of season, peak and senescence
• Field boundary delineation and pure-pixel extraction

Module 4 Analysis

Classification and Anomaly Detection

• Crop type classification from phenological profiles
• Within-field variability and management zone delineation
• Anomaly detection against a field or regional baseline

Module 5 Delivery

Scale, Tooling and Validation

• Google Earth Engine and cloud-native geospatial workflows
• Validating against ground truth and yield records
• Delivering outputs to agronomists and insurers in a usable form

Technical Specifications

ParameterRequirement
Covered Tool / PlatformPython
Covered Tool / PlatformArcGIS
Covered Tool / PlatformCropSyst
Covered Tool / PlatformDSSAT
Covered Tool / PlatformQGIS
Covered Tool / PlatformDrone Technology

Frequently Asked Questions

This is an Recorded Lectures (Self-Paced) course delivered via our e-LMS platform. You will have access to pre-recorded video lectures, reading materials, assignments, quizzes, and hands-on projects that you can complete at your own pace.

Yes! Upon successful completion of all modules, assignments, and assessments, you will receive an e-Certification along with an e-Marksheet from DSTC (DSTC) that you can showcase on your CV and LinkedIn profile.

Learners should have a foundational understanding of Agricultural Science concepts. Familiarity with basic tools and programming is recommended.

You will have access to all course materials for the duration of 3 Days (60-90 minutes each day). The self-paced format allows you to learn according to your own schedule through our online learning management system.

Yes, dedicated mentor support is available throughout the course. You can reach out for doubt-clearing sessions, project guidance, and career advice related to Agricultural Science. Our mentors are industry experts and experienced professionals. Enroll in Agri-Tech Analytics: NDVI Time-Series Analysis from Satellite Imagery today and take the next step in your professional journey. With expert-curated content, practical projects, and industry-recognized certification, this course is your gateway to mastering Agricultural Science skills that matter.

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