Commercially operated by GeoEye.
Launched in September 2008, GeoEye-1 has one of the highest spatial resolutions among commercial satellite sensors. From the same company that operates IKONOS (GeoEye) comes GeoEye-1, a spaceborne multispectral sensor with a panchromatic band (.41 meters) and 4 multispectral bands (blue, green, red, and near infrared, at 1.65 meters). The sensor has the ability to rotate any direction and can acquire images up to 60 degrees off nadir.
GeoEye-1 data is very useful for studying surface conditions on a fine scale. Its short return interval (3 days) is also advantageous for observing changing conditions and increases the chance of getting cloud and smoke free scenes. There are two potential drawbacks of using GeoEye-1 data. First, the cost of acquiring the imagery is very high. Unlike sensors such as Landsat and MODIS which are continually acquiring and archiving data, GeoEye-1 imagery is gathered on-demand. Purchasing archived images, however, will cut your costs in half. Second, the high spatial resolution of the data makes it challenging to work with for very large (e.g., bigger than 50,000 ac) landscapes.
The panchromatic band has a spatial resolution of .41 meters at nadir. The 4 color bands have a spatial resolution of 1.65 meters at nadir. Images acquired at off-nadir angles will have spatial resolutions greater than what is listed above. GeoEye-1 data is gathered in 11-bit radiometric precision (pixels can have values from 0 to 2,047) but can also be scaled down to 8-bits (0-256).
Swath width of GeoEye-1 is 15.2 km at nadir. Scene sizes are customizable, and you pay for only the imagery within your study area. For large areas, multiple passes may be required. Thus, several smaller images will need to be combined to get a seamless image for the larger area.
GeoEye-1 is in a sun synchronous orbit and flies at an altitude of 681 km above the Earth. With the ability to position the camera at off-nadir angles, GeoEye-1 can re-image a place on Earth approximately every 3 days. If extreme off-nadir angles are not acceptable, then revisit times increase.
All information regarding GeoEye-1 products is available on the GeoEye website. http://www.geoeye.com/CorpSite/
From GeoEye you can get georeferenced images (Geo), orthorectified (terrain corrected, Geo Professional) images, or stereo images (GeoStereo). Scene sizes can be customized to fit your area of interest. Image costs for Geo products are $12.50 per km2 for archived images, and $25 per km2 for new acquisitions. Geo Professional products cost $30 per km2. Images can be retrieved through an FTP site or mailed.
Products can also be purchased through many of GeoEye’s channel partners. Some of the companies sell higher processed products and some of the companies might sell images at reduced costs. A list of resellers can be found here. http://www.geoeye.com/CorpSite/products-and-services/channel-partners/Default.aspx.
Because GeoEye-1 is commercially operated, there are some licensing restrictions regarding image usage and sharing. Please consult with GeoEye to get the level of licensing that is appropriate for your research or project.
GeoEye-1 imagery is primarily distributed in a Geotiff format making it user friendly for geographic information systems such as ArcGIS and common image processing software.
* Shruthi et al. (2011) This paper investigates the use of object-oriented image analysis (OOA) to extract gully erosion features from satellite imagery, using a combination of topographic, spectral, shape (geometric) and contextual information obtained from IKONOS and GEOEYE-1 data. A rule-set was developed and tested for a semi-arid to sub-humid region in Morocco.
GeoEye-1 images usually come in a user friendly Geotiff format, which is preferred because of its easy integration with GIS platforms like ArcGIS and image processing programs such as Erdas Imagine and ENVI. The size of the files will depend on the extent of the scene, but because of its fine resolution, GeoEye-1 data can be very large (1 GB or more).
* Shruthi R, Kerle N, Jetten V. 2011. Object-based gully feature extraction using high spatial resolution imagery. Geomorphology 134 (3-4): 260-268.
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