Choosing the right type of imagery for your project
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
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.