There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The State of Food and Agriculture

Human Development Report 2006

In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market.

/pdf/applications-of-3d-city-models-state-of-the-art-review-3yewcl5e4i.pdf

Applications of 3D City Models: State of the Art Review

Spaceborne differential synthetic aperture radar interferometry (DInSAR) has already proven its potential for mapping ground deformation phenomena, e.g. volcano dynamics. However, atmospheric disturbances as well as phase decorrelation have prevented hitherto this technique from achieving full operational capability. These drawbacks are overcome by carrying out measurements on a subset of image pixels corresponding to pointwise stable reflectors (Permanent Scatterers, PS) and exploiting long temporal series of interferometric data. Results obtained by processing 55 images acquired by the European Space Agency (ESA) ERS SAR sensors over Southern California show that the PS approach pushes measurement accuracy very close to its theoretical limit (about 1 mm), allowing the description of millimetric deformation phenomena occurring in a complex fault system. A comparison with corresponding displacement time series relative to permanent GPS stations of the Southern California Integrated GPS network (SCIGN) is carried out. Moreover, the pixel-by-pixel character of the PS analysis allows the exploitation of individual phase stable radar targets in low-coherence areas. This makes spaceborne interferometric measurements possible in vegetated areas, as long as a sufficient spatial density of individual isolated man-made structures or exposed rocks is available. The evolution of the Ancona landslide (central Italy) was analysed by processing 61 ERS images acquired in the time span between June 1992 and December 2000. The results have been compared with deformation values detected during optical levelling campaigns ordered by the Municipality of Ancona. The characteristics of PS, GPS and optical levelling surveying are to some extent complementary: a synergistic use of the three techniques could strongly enhance quality and reliability of ground deformation monitoring. D 2002 Elsevier Science B.V. All rights reserved.

Monitoring Landslides and Tectonic Motions with the Permanent Scatterers Technique

A synthetic aperture radar (SAR) raw signal simulator for urban scenes is presented along with models it employs to compute the backscattered field and to account for the imaging radar sensor characteristics Urban areas are represented as a set of dielectric buildings placed over a random rough nonflat dielectric terrain The adopted models allow evaluation of the raw signal on a sound physical and mathematical background: the scattering model employs the Kirchhoff approach appropriately extended to include multiple-reflection effects, and the radar model operates in the two-dimensional Fourier transformed domain Details to assess how and why the simulator is also efficient with respect to the computational time are provided In addition, relevant examples are discussed to show the simulator potentialities and assess the validity of the main results It is shown that the simulator is able to quantitatively assess performances of SAR sensors over urban structures The proposed simulator turns out to be also useful to train numerical schemes devoted to feature extraction, and to test any specific SAR processing technique Comments for further developments of the simulation tool are presented

SAR raw signal simulation for urban structures

We present a new methodology for rapid flood mapping exploiting Sentinel-1 synthetic aperture radar data. In particular, we propose the usage of ground range detected (GRD) images, i.e., preprocessed products made available by the European Space Agency, which can be quickly treated for information extraction through simple and poorly demanding algorithms. The proposed framework is based on two processing levels providing event maps with increasing resolution. The first level exploits classic co-occurrence texture measures combined with amplitude information in a fuzzy classification system avoiding the critical step of thresholding. The second level consists of a change-detection approach applied to the full resolution GRD product. The discussion is supported by several experiments demonstrating the potentiality of the proposed methodology, which is particularly oriented toward the end-user community.

Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for design of oil slick detection and interpretation systems. In this paper, the ocean simulation issues are presented, and the main problems relating to the oil presence on the sea surface are treated. Attention is focused on the electromagnetic side of the problem, taking account of the sensor signatures, the dielectric, physical-chemical, and geometric nature of the oil slick, and the environmental conditions. The presented SAR simulator is based on an ocean model and an oil slick model. The former makes use of multiscale description of the ocean surface: the distributed surface model for the SAR-ocean interaction is considered by taking into account the nonlinear hydrodynamic effect for the water particle movement. The latter model implements a modification of the ocean spectrum, based on the Marangoni theory and accounting for the nonlinear wave interaction mechanism. However, the proposed SAR raw signal simulator is modular and flexible, thus allowing other possible physical models for modeling the oil slick effect over the ocean spectrum. Meaningful SAR simulation experiments are presented and discussed, elucidating the role of difference on pollutants, oil thickness, wind speed and direction, incident wavelength and angle and other radar parameters. Validation of the simulator is also presented by comparison with experimental data. A striking conclusion of the paper is that higher order moments (from the second on) of oil slick SAR image statistics are quite different compared to those pertinent to an equivalent wind speed decrease on the imaged area. This suggests a convenient way to define new appropriate oil slick signatures.

/pdf/sar-raw-signal-simulation-of-oil-slicks-in-ocean-3nqfezbzca.pdf

SAR raw signal simulation of oil slicks in ocean environments

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for designing new sensors, testing processing algorithms, planning missions, and devising inversion algorithms. In this paper, a spotlight SAR raw signal simulator for distributed targets is presented. The proposed procedure is based on a Fourier domain analysis: a proper analytical reformulation of the spotlight SAR raw signal expression is presented. It is shown that this reformulation allows us to design a very efficient simulation scheme that employs fast Fourier transform codes. Accordingly, the computational load is dramatically reduced with respect to a time-domain simulation and this, for the first time, makes spotlight simulation of extended scenes feasible.

/pdf/efficient-spotlight-sar-raw-signal-simulation-of-extended-2qzifvfz0t.pdf

Efficient spotlight SAR raw signal simulation of extended scenes

In this paper, we present a complete framework to support the monitoring of natural and man-made disasters by means of synthetic aperture radar (SAR) images. The fractal geometry is the most appropriate mathematical instrument in describing the irregularity of a natural observed scene, by means of few effective and reliable parameters. Therefore, fractal concepts can be used to model and identify geometrical changes that occurred in areas hit by disasters. We present an overall framework employing fractal-based models, algorithms, and tools to support the identification of natural area changes due to natural or man-made disasters. Such a framework includes an algorithm used to extract fractal parameters from a 2-D signal, a fractal interpolation tool, and a SAR raw-signal simulator. The combined use of these tools provides an innovative instrument for disaster monitoring applications. In this paper, we implement the fractal framework to obtain a relation between the fractal parameters of a SAR image and those of the relative imaged area. In addition, a case study is discussed, showing the potentiality of our framework for flooding detection

/pdf/a-novel-approach-for-disaster-monitoring-fractal-models-and-31v2inrutv.pdf

Giuseppe Ruello

Papers

SAR raw signal simulation for urban structures

Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images

SAR raw signal simulation of oil slicks in ocean environments

Efficient spotlight SAR raw signal simulation of extended scenes

A Novel Approach for Disaster Monitoring: Fractal Models and Tools