Goodbye to EO-1

Hyperspectral data of fields in South America classified using Principle Components Analysis. Data acquired by Hyperion. Image courtesy of NASA.

In contrast to our previous blog, this week’s is a celebration of the Earth Observing-1 (EO-1) satellite whose death will soon be upon us.

EO-1 was launched on the 21st November 2000 from Vandenberg Air Force Base, California. It has a polar sun-synchronous orbit at a height of 705 km, following the same orbital track as Landsat-7, but lagging one minute behind. It was put into this orbit to allow for a comparison with Landsat 7 images in addition to the evaluation of EO-1’s instruments.

It was the first in NASA’s New Millennium Program Earth Observing series, which had the aim of developing and testing advanced technology and land imaging instruments, particularly related to spatial, spectral and temporal characteristics not previously available.

EO-1 carries three main instruments:

  • Hyperion is an imaging spectrometer which collects data in 220 visible and infrared bands at 30 m spatial resolution with a 7.5 km x 100 km swath. Hyperion has offered a range of benefits to applications such as mining, geology, forestry, agriculture, and environmental management.
  • Advanced Land Imaging (ALI) is a multispectral imager capturing 9 bands at 30 m resolution, plus a panchromatic band at 10 m, with a swath width of 37 km. It has the same seven spectral bands as Landsat 7, although it collects data via a different method. ALI uses a pushbroom technique where the sensor acts like a broom head and collects data along a strip as if a broom was being pushed along the ground. Whereas Landsat operates a whiskbroom approach which involves several linear detectors (i.e., broom heads) perpendicular (at a right angle) to the direction of data collection. These detectors are stationary in the sensor and a mirror underneath sweeps the pixels from left to right reflecting the energy from the Earth into the detectors to collect the data.
  • Atmospheric Corrector (LAC) instrument allows the correction of imagery for atmospheric variability, primarily water vapour, by measuring the actual rate of atmospheric absorption, rather than using estimates.

The original EO-1 mission was only due to be in orbit only one year, but with a sixteen year lifetime it has surpassed all expectations. The extension of the one year mission was driven by the Earth observation user community who were very keen to continue with the data collection, and an agreement was reached with NASA to continue.

Psuedo-true colour hyperspectral data of fields in South America. Data acquired by Hyperion. Image courtesy of NASA.

All the data collect by both Hyperion and ALI is freely available through the USGS Centre for Earth Resources Observation and Science (EROS). At Pixalytics we’ve used Hyperion data for understanding the capabilities of hyperspectral data. The two images shown in the blog are a subset of a scene acquired over fields in South America, with image to the right is a pseudo-true colour composite stretched to show the in-field variability.

Whereas the image at the top is the hyperspectral data classified using a statistical procedure, called Principle Components Analysis (PCA), which extracts patterns from within the dataset. The first three derived uncorrelated variables, termed principle components, are shown as a colour composite.

Sadly, satellites cannot go on forever, and EO-1 is in its final few weeks of life. It stopped accepting data acquisition requests on the 6th January 2017, and will stop providing data by the end of February.

It has been a great satellite, and will be sadly missed.

Blog of Many Colours

Image featuring the sister cities of Sault Sainte Marie, Ontario, and Sault Sainte Marie, Michigan. ESA’s Proba satellite acquired this image on 11 August 2006 with its Compact High Resolution Imaging Spectrometer (CHRIS), designed to acquire hyperspectral images with a spatial resolution of 18 metres across an area of 14 kilometres. Data courtesy of SSTL through ESA.

Image featuring the sister cities of Sault Sainte Marie, Ontario, and Sault Sainte Marie, Michigan. ESA’s Proba satellite acquired this image on 11 August 2006 with its Compact High Resolution Imaging Spectrometer (CHRIS), designed to acquire hyperspectral images with a spatial resolution of 18 metres across an area of 14 kilometres. Data courtesy of SSTL through ESA.

The aspect of art at school that really stuck with me was learning about the main colours of the rainbow and how they fit together – like with like, such as yellow, green, blue, and like with unlike such as shades of green with a fleck of red to put spark into a picture. Based on these ideas, when I was a teenager I used to construct geometric mandalas coloured in with gouache. As I began studying remote sensing, it seemed natural that hyperspectral imaging would hold a special fascination.

The term Hyperspectral Imaging was coined by Goetz in 1985 and is defined as ‘the acquisition of images in hundreds of contiguous, registered, spectral bands such that for each pixel a radiance spectrum can be derived.’ Put simply, whereas a picture is made using three colour components for television (red, green and blue), for hyperspectral imaging the spectrum is split into many, sometimes hundreds, of different grades of colour for each part of the image. The term made its way into scientific language by way of the intelligence communities – the military became interested in it as it offered them the ability to tell plastic decoys from real metal tanks, as well as an object’s precise colour.

When the first field spectral measurements were conducted in the early 1970s, technology was not advanced enough for it to be put into operation. However, developments in electronics, computing and software throughout the 1980s and into the 1990s, brought the hyperspectral imaging to the EO community.

A series of parallel hardware development began in the 1980’s, such as at NASA JPL with the Airborne Imaging Spectrometer (AIS) in 1983, followed by AVIRIS (Airborne Visible/IR Imaging Spectrometer). The AVIRIS sensor was first flown in 1987 on a NASA aircraft at 20km altitude and to this day, it is still a key provider of high-quality HS data for the scientific community.

The hardware advances were matched by improvements in software capabilities, with the development of the iconic image cube method of handling this type of data, by PhD students Joe Boardman and Kathryn Kierein-Young, from the University of Colorado. Spectral libraries have been amassed for over 2,400 natural and artificial materials, to enable them to be identified. The most famous is the ASTER spectral library which includes inputs from Johns Hopkins University (JHU) Spectral Library, the Jet Propulsion Laboratory (JPL) Spectral Library, and the United States Geological Survey (USGS – Reston) Spectral Library.

Hyperspectral imaging was primarily developed for the mapping of soils and rock types; and the spectra of these are rich in character. Taking regions from the contiguous spectrum makes it possible to identify surface materials by reflectance or emission and also allows precise atmospheric correction which can only be approximated if you are using discrete, wide colour bands. The shape of the reflectance or emittance spectrum yields information about grain size, abundance and composition as well as the biochemistry of vegetation, such as the concentration of chlorophyll and other pigments and life forms in water bodies.

Earth observation hyperspectral imaging really began with NASA’s Earth Observing-1 Mission (EO-1) launched in 2000, with the Hyperion imager on board that has 200 wavelengths. Since then, various other missions have been launched such as the Compact High Resolution Imaging Spectrometer (CHRIS) on the Proba-1 satellite also in 2001, with 63 spectral bands; or the Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp series of Meteorological satellites whose first version was launched in 2006.

The coming years for hyperspectral imaging looks exciting with a whole series of planned missions including the Italian PRISMA (PRecursore IperSpettrale della Missione Applicativa), German EnMAP (Environmental Mapping and Analysis Program), NASA’s HyspIRI (Hyperspectral Infrared Imager), and JAXA’s (Japan Aerospace Exploration Agency) Hyperspectral Imager Suite (HIUSI).

So for me, and anyone with the same fascination, the future really will be filled with many colours!


Blog written by Dr Louisa Reynolds