Tag Archives: Landsat

Developments in remotely sensed data for geology

Over several decades remote sensing – the interpretation and analysis of image data – has become a central part of many geologists’ ‘toolkit’. It continues a ‘tradition’ founded in the interpretation of panchromatic (black and white), stereoscopic aerial photographs that began after World War 2. But after 1972 and the launch of the first Landsat platform, it has been served by more synoptic views from space using a variety of systems that produce data in many wavelengths of EM radiation, thereby providing opportunities to study spectral properties of the Earth’s surface. This imagery also possesses the analytical flexibility afforded by being recorded in digital form. Since the 1986 launch of the first SPOT platform digital stereoscopic potential from space entered the options for geological interpretation. The Landsat Thematic Mapper (TM) launched in 1982 expanded the spectral range of data. Previously that had been restricted to the visible and near infrared (VNIR) affected mainly by living vegetation and the iron oxy-hydroxides that are the main colorants of rock and soil and TM added a shortwave infrared (SWIR) band. Natural reflectance spectra in that region are affected by Al-OH, Mg-OH and C-O bonds in various hydroxylated silicates and carbonate minerals. The data from TM and its successor the Enhanced Thematic Mapper (ETM) resulted in an explosion of effort into lithological mapping and structural analysis. The last depended on a step-change in resolution to 15 m in the panchromatic band of the ETM system since 1993, together with 10 m stereoscopic resolution from the SPOT family, that enable confident mapping at around 1:100 000 to 1:50 000 scales.

The ETM, its successor on Landsat-8 in 2013 – the Operational Land Imager (OLI) – and the somewhat similar ESA Sentinel-2 system (2015) suffer from one major frustration. Their single broad SWIR band is unable to discriminate –OH and C-O spectral features and hence the lithologically useful range of hydroxylated silicates and carbonate mineral spectra. Also missing from the spectral ‘toolkit’ was any data relating to the major rock-forming silicates. Both drawbacks were remedied to some extent by the launch in 1999 of the Japan/US Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). As well as the VNIR in three bands, including a stereo-image pair, this covered the mineralogically useful SWIR with 6 narrow  wavelength range bands imaging and 5 bands in the thermally emitted infrared (TIR) where common silicates show substantial spectral differences. ASTER produced primarily geoscientific data that have been found to be of enormous use in geological and mineralogical mapping at the 1:100 000 scale.

Nowadays all the data types mentioned so far, except SPOT, are available for download free of cost from the Earth Explorer site operated by the US Geological Survey (use the Data Sets tab at the EE home page): a superb resource that would suit most geological applications. Yet none of these data have spatial resolution better than 10 m. The commercial Earth observation sector has mainly focussed on increasingly finer spatial resolution, mainly panchromatic and the VNIR range of wavelengths that yield information on vegetation and surface topographic and cultural detail, for which there are many profitable markets. Apart from the follow-on to SPOT – the Pléiades system with resolution as fine as 0.5 m – data from a whole constellation of once independent hi-res systems (WorldView, Quickbird, GeoEye, IKONOS and OrbView) are now administered by one vendor Digital Globe. The finest resolution currently available publically is that of WorldView-3 (0.3 m), beyond which is the classified purview of the US intelligence community. The figure illustrates just how much more detailed geological information there is in the finest resolution data than in the same kind of image reduced to 15 m resolution, the best offered by ASTER. That detail needs to be tempered by a few facts: by comparison with the high-res image ASTER shows a regional context, i.e. large-scale geological structures; it covers more spectral bands and is therefore more revealing lithologically; the highest resolution data (WorldView-3 archived) are priced at US$14 to 19 per km2  for each of 6 different band-bundles with a minimum order of 25 km2. Note: for some areas Google Earth has coverage at high-resolution captured at several dates, though some remain at 15 m resolution (based on Landsat-7 ETM).

30cm v 15m

An area in Utah, USA, with almost 100% exposure and very low vegetation cover shown by simulated natural colour images at ~0.3 m with a scale of ~1:1225 (top) and ~15 m at ~1:61275. Credit: Google Earth

The geologist’s dream data would, I suppose, consist of many bands that divide the VNIR, SWIR and TIR into narrow wavebands so that rock and soil spectra can be accurately reproduced, thereby allowing considerable discrimination between different rock types and their main constituent minerals. Oh yes, and it would have decent resolution – better than 15 m. There is indeed such a hyperspectral instrument called CRISM and data from it can be downloaded freely but, before there is a stampede to get access, note that the acronym stands for Compact Reconnaissance Imaging Spectrometer for Mars! For the Earth most hyperspectral data are captured from airborne missions, except for one orbital mission that occasionally functioned over a tiny fraction of the Earth from 2001 to 2017 – NASA’s EO-1 Hyperion system that produced 7.5 km swaths at 30 m resolution with 220 spectral bands covering the VNIR and SWIR regions. Apart from one aimed at oceanic and atmospheric issues, that will say little about rocks, NASA and ESA have no plans in this niche. One commercial developer, Satellogic of Argentina, has hyperspectral plans but only where an income stream is guaranteed, which seems to be just for crops and vegetation spanning the VNIR range. Other outfits have wish lists but few concrete plans in the geoscientific spectral range.

With pending budget cuts to NASA’s Earth science programme (9%), NOAA (22%) and the USGS (14%) demanded by the Trump administration, progress with US contributions to Earth observation can’t be anticipated with much hope. Commercial interests have to pay the shareholders and their dominant focus is on government intelligence agencies, the media, private weather forecasters and agribusiness. So do not expect another or better CRISM in Earth orbit. But it is possible to get by quite nicely at the reconnaissance, small-scale level of mapping, lithological discrimination and some mineral identification with the moderate resolution 14 spectral bands captured by ASTER. If you have the cash, then WorldView-3 offers similar panchromatic, VNIR and SWIR data options at 0.3, 1.2 and 3.7 m resolution, respectively, that should enable very intricate geological mapping.

You may learn more about geological remote sensing here.

‘Big data’ on water resources

 

Two petabytes (2×1015) is a colossal number which happens to approximate how much data has been collected in geocoded form by the Landsat Thematic Mapper and its successors since it was first launched in 1984. In tangible form these would occupy about half a million DVDs, weighing in at about 8 metric tonnes; ‘daunting’ comes nowhere near describing the effort needed to visually interpret this unique set of multi-date imagery. Using the Google Earth Engine, the free cloud-computing platform for big sets of image data which hosts all Landsat data and much else (but not yet the equally daunting ASTER data – roughly a million 136 Mb scenes) the 32 years-worth has been analysed for its content of hydrological information by the European Commission’s Joint Research Centre in Italy, with assistance from Google Switzerland. Using the various spectral characteristics of water in the visible and infrared region, the team has been able to assess the position on the continents of surface water bodies larger than 900 m2, both permanent and ephemeral, and how the various categories have changed in the last 32 years (Pekel, J.-F. et al. 2016. High-resolution mapping of global surface water and its long-term changes. Nature, v. 540, p. 418-422; doi:10.1038/nature20584). The results are conveniently and freely available in their entirety at the Global Surface Water Explorer, an unparalleled and easy-to-use opportunity for water resource managers, wetland ecologists and geographers in general.

Among the revelations are sites and areas that have been subject to gains and losses in water availability, the extents of new and vanished permanent and seasonal water bodies and the conversion of one to the other. A global summary gives a net disappearance of 90 thousand km2 of permanent water bodies, about the area of Lake Superior, but exceeded by new permanent bodies totalling 184 thousand km2. There has been a net increase in permanent water on all continents except Oceania with a loss one percent (note that Antarctica and land north of the Arctic Circle were not analysed). More than 70 % of the losses are in the semi-arid Middle East and Central Asia (Iran, Iraq, Uzbekistan, Kazakhstan and Afghanistan), due mainly to overuse of irrigation, dam construction and long-term drought. Much of the increase in water occurrence stems from reservoir construction, but climate change may have played a part through increased precipitation and melting of high-altitude snow and ice, as in Tibet.

The Aral Sea in Uzbekistan and Kazakhstan has suffered dramatic loss of standing and seasonal water cover due to overuse of water for irrigation from the two main rivers, the Amu (Oxus) and Syr, that flow into it. Note the key to the colours that represent different categories of changes in surface water. (Credit: Global Surface Water Explorer)

The Aral Sea in Uzbekistan and Kazakhstan has suffered dramatic loss of standing and seasonal water cover due to overuse of water for irrigation from the two main rivers, the Amu (Oxus) and Syr, that flow into it. Note the key to the colours that represent different categories of changes in surface water. (Credit: Global Surface Water Explorer)

Many of the lakes in the northern Tibetan Plateau have grown in size during the last 32 years, mainly due to increased precipitation and snow melt. (Credit: Global Surface Water Explorer)

Many of the lakes in the northern Tibetan Plateau have grown in size during the last 32 years, mainly due to increased precipitation and snow melt. (Credit: Global Surface Water Explorer)

There are limitation to the accuracy of the various categories of change, one being the persistence of cloud cover in humid climates, another being the sometimes haphazard scheduling of Landsat Data capture (in some case that has depended on US Government interest in different areas of the world).

More detail on using remote sensing in exploration for and evaluation of water resources can be found here.