John van Genderen

Next-generation Digital Earth

A speech of then-Vice President Al Gore in 1998 created a vision for a Digital Earth, and played a role in stimulating the development of a first generation of virtual globes, typified by Google Earth, that achieved many but not all the elements of this vision. The technical achievements of Google Earth, and the functionality of this first generation of virtual globes, are reviewed against the Gore vision. Meanwhile, developments in technology continue, the era of “big data” has arrived, the general public is more and more engaged with technology through citizen science and crowd-sourcing, and advances have been made in our scientific understanding of the Earth system. However, although Google Earth stimulated progress in communicating the results of science, there continue to be substantial barriers in the public’s access to science. All these factors prompt a reexamination of the initial vision of Digital Earth, and a discussion of the major elements that should be part of a next generation.

Digital Earth 2020: towards the vision for the next decade

Abstract This position paper is the outcome of a brainstorming workshop organised by the International Society for Digital Earth (ISDE) in Beijing in March 2011. It argues that the vision of Digital Earth (DE) put forward by Vice-President Al Gore 13 years ago needs to be re-evaluated in the light of the many developments in the fields of information technology, data infrastructures and earth observation that have taken place since. The paper identifies the main policy, scientific and societal drivers for the development of DE and illustrates the multi-faceted nature of a new vision of DE grounding it with a few examples of potential applications. Because no single organisation can on its own develop all the aspects of DE, it is essential to develop a series of collaborations at the global level to turn the vision outlined in this paper into reality.

Remote sensing image fusion: an update in the context of Digital Earth

Remote sensing image fusion has come a long way from research experiments to an operational image processing technology. Having established a framework for image fusion at the end of the 90s, we now provide an overview on the advances in image fusion during the past 15 years. Assembling information about new remote sensing image fusion techniques, recent technical developments and their influence on image fusion, international societies and working groups, and new journals and publications, we provide insight into new trends. It becomes clear that image fusion facilitates remote sensing image exploitation. It aims at achieving better and more reliable information to better understand complex Earth systems. The numerous publications during the last decade show that remote sensing image fusion is a well-established research field. The experiences gained foster other technological developments in terms of sensor configuration and data exploitation. Multi-modal data usage enables the implementation of the concept of Digital Earth. In order to advance in this respect, we recommend that updated guidelines and a set of commonly accepted quality assessment criteria are needed in image fusion.

Structuring contemporary remote sensing image fusion

The exploitation of multi-sensor images at pixel level is a widely implemented research field in Earth observation. In this context, image fusion plays an important role since it effectively combines complementary image content to enhance information contained in the individual datasets. This article presents an overview of the existing fusion techniques and their achievements for Earth scientists. This research started off with the compilation of a database on remote sensing image fusion journal publications. Research results were exploited, grouping the literature into different aspects of relevance. Six categories of information have been built according to the journal, the application, sensors that provided the images used in the case study, applied fusion techniques, areas of achievement, and on-going research highlighting unresolved questions and current science. This resulted in an overview on the categorisation of image fusion techniques, explanation of the various approaches used within a certain category, and description of particularities when dealing with the fusion of optical and radar imagery. Even though many researchers intend to find the best algorithm, there is a greater need to define an appropriate workflow prior to processing the imagery with the knowledge in all related fields, that is, remote sensing image fusion and the desired application to address the different aspects of error propagation.

Fundamentals of satellite remote sensing: an environmental approach

This is a very useful textbook for university teachers giving undergraduate courses in remote sensing, and for those giving courses on environmental issues. It is written by one of the best known E...

Wavelet transform for noise reduction of SAR interferograms

SAR interferometry is a technique for extracting height information from phase difference images referred to as interferograms. Phase measurements from interferograms need to be unwrapped before useful information can be extracted since they are given module 2(pi) . Phase unwrapping is a difficult task to do because phase measurements tend to be corrupted by additive random phase noises caused by low coherence. The current approach to the phase noise reduction is to smooth interferograms by using coherent averaging method, which is simple but leads to a degradation of spatial resolution and edge blur. In this paper, an approach to phase noise reduction is proposed based on the wavelet transform. It is implemented by decomposing the original interferogram into a smoothed approximation and a series of wavelet planes at different resolution levels, followed by a morphological filtering of the wavelet planes that contain noises. The noise-reduced interferogram is reconstructed based on the approximation and the smoothed wavelet planes. The results show that the proposed approach can reduce phase noises with retained spatial resolution of the original interferograms when preserving edges.

Enhanced image analysis through multilevel data fusion techniques

The Western European Union Satellite Center (WEUSC) operationally exploits multisensor data for security oriented applications using data fusion techniques. Fused data can contribute to improved interpretation capabilities and more reliable results since the data with different characteristics are combined. The input images vary in spectral and spatial resolution as well as in time and therefore give a more complete view of the objects observed. This paper outlines a research projected initiated by WEUSC with the aim to demonstrate the benefit of data fusion using data from visible/infrared and synthetic aperture RADAR satellite sensors with regards to improved visual image interpretation. All three processing levels of data fusion are considered, i.e. pixel-based, feature-based and decision-based. Using advanced analytical or numerical data fusion techniques the data are processed for visual and semi-automatic interpretation to extract and analyze features of interest, in particular man-made objects, such as airfields, vehicles and infrastructure. After a short description of the WEUSC framework an introduction to the data fusion demonstrator is given. The paper continues with a description of methodology, implementation, and first results obtained. It concludes with an evaluation of the experiences gained.

Multisensor fusion: optimization and operationalization for mapping applications

Taking advantage of both optical and microwave remote sensing images with their complementary information, image fusion becomes a valuable approach to provide and improve up-to-date space maps in frequently cloud covered areas such as the humid Tropics. Remotely sensed data from north of the Netherlands is processed for test and calibration purposes. Later on it is planned to implement the methodology in Indonesia; the selected research area is situated on Sumatra. This paper gives an overview about the existing techniques and presents first results of fusing ERS- 1 SAR data with SPOT and LANDSAT TM investigating different combinations of fusion techniques and input imagery in terms of orbit, looking angle and spectral/spatial resolution. It is anticipated to provide an optimized fusion approach which takes into account the parameters which influence the accuracy and information extraction possibilities of fused data in relation to mapping and map updating in tropical developing countries.

Tracking and data fusion: a handbook of algorithms, by Yaakov Bar-Shalom, Peter K. Willett and Xin Tian

Tracking and data fusion: a handbook of algorithms, by Yaakov Bar-Shalom, Peter K. Willett and Xin Tian, Storrs, CT, YBS Publishing, 2011, 1235 pp., US

The Digital Belt and Road program in support of regional sustainability

300, ISBN 978-0964-8312-78 This mammoth refer...