1. Introduction to Remote Sensing#
In this chapter of Introduction to Geospatial Data Analysis, we explore the fundamentals of remote sensing—a powerful technique for observing and measuring the Earth’s surface from a distance, typically via satellites or aircraft. The chapter provides an overview of key concepts in remote sensing, with a focus on four primary types of resolution: radiometric, spatial, spectral, and temporal.
Understanding these resolutions is essential for geospatial data analysis. Radiometric resolution refers to a sensor’s ability to detect subtle differences in energy, while spatial resolution defines the smallest object that can be discerned. Spectral resolution relates to distinguishing between different wavelengths of light, and temporal resolution indicates the frequency of data collection over the same area.
We will also discuss swaths, which describe the width of the area observed by a sensor during a single pass, crucial for understanding the coverage of remote sensing instruments. Additionally, the chapter introduces techniques for interpreting remote sensing images, a key skill for effectively analyzing and utilizing the data.
The goal of this chapter is to lay the groundwork for understanding how remote sensing data is collected and analyzed, providing essential knowledge for geospatial data analysis. Remote sensing offers vast data coverage, high-resolution details, temporal change monitoring, and access to otherwise inaccessible regions. Mastering these concepts will enable readers to apply remote sensing technology across various fields, including environmental monitoring, urban planning, and disaster management.