Level 1
What type of satellite data I need to use?
Understanding satellite sensor types, their differences, advantages, and limitation is crucial for conducting an EO project.
The most common is to divide sensors into passive, which capture signals emitted or reflected from an object (like the human eye works), and active, which register the backscattering of their own emitted signal (like bats or dolphins). Among the first group optical sensors (also called Imaging Radiometers) are the most popular, and among the second you may encounter Radar, or Synthetic Aperture Radar (SAR), LiDAR (laser), Laser Altimetry, and other technologies.
When choosing data for your project, besides the sensor type, you should consider three resolutions: spectral, spatial, and temporal.
In terms of spectral resolution, among optical sensors we usually differentiate multispectral, which could have tens of broad (from tens to hundreds of nanometres wide) spectral bands, and hyperspectral sensors, which can have hundreds of very narrow (2-10 nanometres) spectral bands. There are different bands (frequencies), on which radar satellites operate as well. SAR has only one frequency, but different compositions of polarisations.
Another way to classify sensors is by the spatial resolution of images (no matter was this image formed by an active or a passive sensor). Borders of the following classes are not fixed and tend to change over time while new sensors are developed:
Kilometers – low resolution
Tens of meters – medium resolution
Up to 10 m – high resolution
Less than 1 m – very high resolution (VHR)
While high-resolution and VHR cameras let us detect very small objects on Earth's surface and create topographic maps, low-resolution sensors give us an overview of vast territories daily (or even every 10 minutes, like geostationary meteorological satellites, do).
This leads us to temporal resolution – the frequency of image update, or revisit time. Obviously, this frequency depends on orbit geometry, sensor field of view, and local conditions (for example, no optical images in the visible part of spectra are taken during the polar night).
Further, you will find materials on specific satellite types.
Optical Remote Sensing and Passive Sensors
Consider taking this introductory level course on optical Earth observation and its main applications by ESA.
When using VHR images, we usually want to receive a high-accuracy derived product, so there are some tricks in processing them. Here are MAGIC’s Drop-In Session (internal link) and supporting materials about 10 things, you need to know about VHR Imagery. An insight on Remote Sensing course by Planetek contains a lot of technical details on satellite image processing (orthorectification, radiometric calibration, and object detection), useful for VHR images, including ERDAS Imagine tutorials.
In case you are looking into using Hyperspectral Imagery here are some useful links for you.
Introduction to Hyperspectral Remote Sensing covers both the theory and practice of hyperspectral data use
Imaging Spectroscopy for Agricultural Applications - even if you are not interested in agriculture, this course is useful for understanding how to study vegetation dynamics.
Hyperspectral Data for Land and Coastal Systems tells about different hyperspectral data sources, and applications not limited to Coastal ecosystems.
Peter Fretwell’s talk (internal link) on Spectral analysis considers different approaches to utilizing image spectral characteristics for various purposes.
Radar Remote sensing and SAR
SAR technology is quite different from optical, so start by familiarising yourself with Radar Remote Sensing terminology and concepts using NASA or Alaska Satellite Facility (ASF) resources. Then, here are some courses to take to get a deeper understanding:
Echoes in space - The most comprehensive course on SAR; explains the physical basis of Radar Remote Sensing, SAR image processing details using SNAP, and SAR data applications. If you need more info on the physical background of Radar Remote Sensing, start with the complementary Basic Principles of Radar Backscatter course.
The courses above contain lots of material and could take a lot of time to go through. If you need a ‘quick’ start into SAR try 4-hour NASA ARSET Introduction to Synthetic Aperture Radar.
After that, you may be interested in Radar data applications. This course studies the SAR main usage directions with the Canadian satellite constellation as an example.
Planetek’s SAR systems in remote sensing course together with the theoretical section, contains a lot of practical-oriented material.
For those who prefer to read: SAR Handbook (check one-pagers!)
LiDAR
LiDAR, one of the active RS methods, has many applications in environmental studies due to its ability to accurately measure distances and create highly detailed 3D maps. This course will walk you through LiDAR fundamentals, and applications and give some practical knowledge about working with LiDAR data formats.
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