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Choosing the right type of imagery for your project

Jon Coursey

Satellite Imagery is used for a wide range of projects, but often times it is tough to figure out just which type of data is needed. In the world of remote sensing, there are many different satellite sensors, all with different resolutions and multispectral capabilities. In this blog, we will explore some basics of remote sensing, what all is available, and common applications of the data.

Remote Sensing 101

As great as a natural color image can look, it is not collected in the same way as, say, the camera on your iPhone. The process of collecting imagery is most commonly referred to as remote sensing, which basically means objects on earth are detected and classified without direct contact. This blog will focus on passive sensing, as this is what is used for natural color and multispectral images (except radar). Passive sensors gather information via radiation that is either emitted or reflected by whatever object the satellite is trying to capture. This data will be captured with whatever spectral bands a sensor can acquire (generally red, green, blue, and near infrared), then sent down to a ground station for processing. From here, the natural color or multispectral image you might have ordered would be put together.

A wide variety of sensors and band combinations are available, and the best options will depend on what you are trying to view, and the size of your project area. Below are a few situations one might face when deciding how to go about selecting the most suitable captures.

What kind of imagery do I need for a base map?

This is generally our most common request. Engineering, architecture, etc. firms will go for images to view ground conditions before building on their project areas. Essentially, they just need an accurate and high resolution picture. In these cases, natural color is the best option.

How much resolution do I need?

This will come down to how large your project area might be, and what is important that you can view with quality. Say your project requires you to obtain an image of California. For this, you wouldn’t want as high of a resolution as if you needed an image of, say, an airport. This would be an extreme amount of detail for such a large area, and would result in enormous file sizes. Additionally, higher resolution sensors typically capture smaller area sizes, so many would be required to fill such an area. And if full coverage even existed, it would be from images accumulated over the course of many months or years. Lower resolution options will give a better overview of an area of this size, and generally use less images to complete the coverage.

One great option is to obtain high resolution imagery of a project site, and lower resolution for the general area. In the images below you will see captures from both the RapidEye & GeoEye sensors. RapidEye captures at 5 meter (being the lower resolution), and GeoEye captures at 0.5 meter resolution. Both show coverage of islands of Hawaii. As you can see, RapidEye still has great detail for a larger city area, but GeoEye has the ability to see specific features within such a city. 

         Figure 1: GeoEye image (0.5 meter resolution)                   Figure 2: RapidEye image (5 meter resolution)

 

When would I need the multispectral bands?

The most common uses for these are measuring crop health and doing vegetative analysis. Most sensors available at MapMart will be equipped with four bands, which are red, green, blue and near-infrared (or RGB & NIR). An image made from these four bands within the ENVI software environment is below. For crop health, one would measure relative reflectance along the wavelengths of these bands. When crops are not healthy, one will notice a decreased reflectance, mainly in the near-infrared reflectance plateau, but also with the blue and green regions of the spectrum.

Multispectral bands can also be used to detect different characteristics on the earth’s surface. Soil, plants, asphalt, etc. all have different spectral signatures, which would be apparent through these multispectral bands. Depending on how many bands you have available, and where they are along the light spectrum, you can start to see more differences within each surface. For example, an asphalt rooftop may appear as only one color with the standard RGB & NIR bands available. If you were working with shortwave infrared (or SWIR) as well, you would start to see different colors within your image. This is because the differences in the components of asphalt are now being detected.

While many applications of this type of data exist, we have covered the most common ones we are contacted for at MapMart. Fortunately, with such a large archive of satellite imagery already existing, with the opportunity to have more collected, a solution can be found for the most unique type of geospatial project. If you need data or help figuring out what type to use for a project, contact us at MapMart.com.

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