Multispectral satellite imaging improves detection of large individual fossils

Palaeontological field surveys in remote regions are a challenge, because of uncertainty in finding new specimens, high transportation costs, risks for the crew and a long time commitment. The effort can be facilitated by using high-resolution satellite imagery. Here we present a new opportunity to investigate remote fossil localities in detail, mapping the optical signature of individual fossils. We explain a practical workflow for detecting fossils using remote-sensing platforms and cluster algorithms. We tested the method within the Petrified Forest National Park, where fossil logs are sparse in a large area with mixed lithologies. We ran both unsupervised and supervised classifications, obtaining the best estimations for the presence of fossil logs using the likelihood and spectral angle mapper algorithms. We recognized general constraints and described logical and physical pros and cons of each estimated map. We also explained how the outcomes should be critically evaluated with consistent accuracy tests. Instead of searching for fossiliferous outcrops, our method targets single fossil specimens (or highly condensed accumulations), obtaining a significant increase in potential efficiency and effectiveness of field surveys. When repeatedly applied to the same region over time, it could also be useful for monitoring palaeontological heritage localities. Most importantly, the method here described is feasible, easily applicable to both fossil logs and bones, and represents a step towards standard best practices for applying remote sensing in the palaeontological field

Multispectral satellite imaging improves detection of large individual fossils

Palaeontological field surveys in remote regions are a challenge, because of uncertainty in finding new specimens, high transportation costs, risks for the crew and a long time commitment. The effort can be facilitated by using high-resolution satellite imagery. Here we present a new opportunity to investigate remote fossil localities in detail, mapping the optical signature of individual fossils. We explain a practical workflow for detecting fossils using remote-sensing platforms and cluster algorithms. We tested the method within the Petrified Forest National Park, where fossil logs are sparse in a large area with mixed lithologies. We ran both unsupervised and supervised classifications, obtaining the best estimations for the presence of fossil logs using the likelihood and spectral angle mapper algorithms. We recognized general constraints and described logical and physical pros and cons of each estimated map. We also explained how the outcomes should be critically evaluated with consistent accuracy tests. Instead of searching for fossiliferous outcrops, our method targets single fossil specimens (or highly condensed accumulations), obtaining a significant increase in potential efficiency and effectiveness of field surveys. When repeatedly applied to the same region over time, it could also be useful for monitoring palaeontological heritage localities. Most importantly, the method here described is feasible, easily applicable to both fossil logs and bones, and represents a step towards standard best practices for applying remote sensing in the palaeontological field

Concepts for on-board satellite image registration. Volume 2: IAS prototype performance evaluation standard definition

Problems encountered in testing onboard signal processing hardware designed to achieve radiometric and geometric correction of satellite imaging data are considered. These include obtaining representative image and ancillary data for simulation and the transfer and storage of a large quantity of image data at very high speed. The high resolution, high speed preprocessing of LANDSAT-D imagery is considered

Using Satellite Images of Environmental Changes to Predict Infectious Disease Outbreaks

A strong global satellite imaging system is essential for predicting outbreaks

Quantum Sensor Miniaturization

The classical bound on image resolution defined by the Rayleigh limit can be beaten by exploiting the properties of quantum mechanical entanglement. If entangled photons are used as signal states, the best possible resolution is instead given by the Heisenberg limit, an improvement proportional to the number of entangled photons in the signal. In this paper we present a novel application of entanglement by showing that the resolution obtained by an imaging system utilizing separable photons can be achieved by an imaging system making use of entangled photons, but with the advantage of a smaller aperture, thus resulting in a smaller and lighter system. This can be especially valuable in satellite imaging where weight and size play a vital role.Comment: 3 pages, 1 figure. Accepted for publication in Photonics Technology Letter

Current, emerging and future technologies for sensing the environment

This paper reviews current technologies that are used for environmental monitoring, and presents emerging technologies that will dramatically improve our ability to obtain spatially distributed, real-time data about key indicators of environmental quality at specific locations. Futuristic approaches to environmental monitoring that employ fundamental breakthroughs in materials science to revolutionise the way we monitor our environment will also be considered. In particular, approaches employing biomimetic and 'adaptive'/'stimuli-responsive' materials will be highlighted, as these could play an important role in the realization of small, low power, low cost, autonomous sensing and communications platforms that could form the building blocks of the much vaunted environmental 'sensor web'