A survival guide to Landsat preprocessing

Area of Science:

• Ecological remote sensing
• Geospatial analysis
• Environmental monitoring

Background:

• Landsat data are crucial for ecological research but require complex preprocessing.
• Inconsistent terminology and methods in existing literature hinder accurate data analysis.
• Ecologists face challenges in selecting appropriate preprocessing workflows for Landsat imagery.

Purpose of the Study:

• To provide a clear overview of Landsat missions and sensors.
• To clarify preprocessing terms and differentiate common methods.
• To offer standardized workflows and a decision tree for ecological applications.

Main Methods:

• Literature synthesis on Landsat preprocessing techniques.
• Explanation of georeferencing, radiance conversion, and atmospheric/topographic corrections.
• Development of a decision tree for selecting preprocessing levels.

Main Results:

• A concise overview of Landsat missions and sensors is presented.
• Key preprocessing steps (e.g., atmospheric correction) are clearly defined.
• Tailored workflows and a decision tree guide ecologists in data preparation.

Conclusions:

• A parsimonious approach to Landsat preprocessing is recommended.
• Well-tested, accessible, and documented data products and methods are advised.
• The findings support accurate ecological monitoring and are applicable to other remote sensing platforms.