Learn About Remote Sensing on Sentinel-Bird

The Analysis: NDVI, NDBI & Change Detection

Mon, 01 Jan 0001 00:00:00 +0000

Normalized Difference Indices

So what can we do with all these bands? One example can be seen in Normalized Difference Vegetation Index (NDVI). This method, which was published in 1974, is calculated by subtracting red from the near-infrared, and dividing it by the sum of near-infrared and red. The near-infrared is strongly reflected by healthy vegetation, while the red band is absorbed for photosynthesis.

With Sentinel-2 specifically this looks like: NDVI = (Band 8 - Band 4) / (Band 8 + Band 4). The result is a raster where photosynthesizing organisms are highlighted!

The Noise: Clouds, Shadows, & AI

Mon, 01 Jan 0001 00:00:00 +0000

The Weather Problem

Sentinel-2 is an optical satellite. It relies on sunlight reflecting off the Earth’s surface to capture an image. This means it has a massive, unavoidable blind spot: clouds.

If a thick cloud bank is sitting over Gaza on the day of a 5-day revisit, the satellite simply captures a picture of the top of the clouds. Furthermore, even if the sky is mostly clear, clouds cast long, dark shadows that completely obscure the ground data beneath them.

The Pixels: Spatial Resolution & Rasters

Mon, 01 Jan 0001 00:00:00 +0000

What Exactly is a Raster?

We get one raster file for each band within the Sentinel-2 data. The raster file contains cells ordered and arranged in a big grid. At the 10 meter resolution, a 10 by 10 meter square accounts for a single cell’s worth of information. At the 60 meter resolution, a 60 by 60 meter square area gives us a single cell’s worth of information.

The information within each cell is simply a measurement of amplitude. So if we open a 10 meter band 3 raster file from the Sentinel-2A sat and look at the value of the top left cell, it is telling us the MSI measured amplitude of the 559.8 (green) wavelength of light at a 10 by 10 meter spot on the Earth. Literally, it tells us how green that spot is.

The Source: Sentinel-2 & Copernicus

Mon, 01 Jan 0001 00:00:00 +0000

In this article, we are going to focus exclusively on Sentinel data. First though, we will describe some of the basics. There are many types of imaging satellites: some like Sentinel-1 capture radar, others like Sentinel-2, capture light. As you may be aware, the light spectrum is significantly larger than what our human eyes can see, and the Sentinel-2 satellites can see far more than we can.

Sentinel-2 satellites carry the Multi-Spectral Instrument (MSI) that images Earth in 13 spectral bands across different wavelengths. Here are the specific wavelengths for both Sentinel-2A and Sentinel-2B satellites.

The Spectrum: Beyond Visible Light

Mon, 01 Jan 0001 00:00:00 +0000

Understanding Reflection and Spectral Signatures

We can do a lot of wild stuff with all this data. We can even do math between rasters of different bands. First though, we need to talk a little about reflection.

Surfaces reflect light differently; intuitively, we both know that. If you look at a mirror, you’ll notice that it reflects much more than whatever surface you are standing on at the time. But have you ever noticed that sometimes you look a little ‘off’ when you look in a mirror you are less familiar with? Two mirrors reflect differently because they have literal physical differences, their surfaces reflect different wavelengths based on their molecular structure and composition. So what about that color difference you see?