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Coursera

Start Remote Sensing

Coursera via Coursera

Overview

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Start Remote Sensing is a beginner-level course that introduces you to the core concepts needed to analyze vegetation using satellite imagery, with a strong focus on understanding data before drawing conclusions. In this course, you explore how Earth-observing satellites collect measurements not photographs and why those measurements must be interpreted carefully. You will compare commonly used satellite missions such as Landsat and Sentinel, learning how differences in spatial resolution, revisit frequency, and spectral bands influence what can be analyzed and how confidently results can be compared. You will then calculate and interpret the Normalized Difference Vegetation Index (NDVI) using red and near-infrared bands, focusing on what the index responds to and what its values reveal about vegetation condition. The course also emphasizes data readiness, showing how atmospheric effects distort raw satellite imagery and why preprocessing steps such as atmospheric correction and surface reflectance are essential before NDVI analysis. By the end of the course, you will be able to produce and interpret a vegetation index that supports a forest-health brief while developing reasoning skills for further study or applied work in remote sensing and environmental monitoring.

Syllabus

  • Landsat vs. Sentinel
    • In this module, you will explore how Earth-observation satellites collect data and compare Landsat and Sentinel sensors to understand when and why each is used for vegetation monitoring and forest analysis.
  • Calculating NDVI from Satellite Bands
    • In this module, you will apply spectral concepts to calculate NDVI, a widely used vegetation index, and interpret what NDVI values reveal about plant health.
  • Preparing Satellite Imagery for Analysis
    • In this module, you will learn why atmospheric effects distort raw satellite imagery and apply basic atmospheric correction to prepare surface reflectance data suitable for vegetation analysis and NDVI calculation in a forest health context.

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