Christine Pohl

Multisensor image fusion in remote sensing: Concepts, methods and applications

With the availability of multisensor, multitemporal, multiresolution and multifrequency image data from operational Earth observation satellites the fusion of digital image data has become a valuable tool in remote sensing image evaluation. Digital image fusion is a relatively new research field at the leading edge of available technology. It forms a rapidly developing area of research in remote sensing. This review paper describes and explains mainly pixel based image fusion of Earth observation satellite data as a contribution to multisensor integration oriented data processing.

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.

Multi‐sensor Image Maps from SPOT, ERS and JERS

Abstract Image mapping using data from visible and infrared sensors has, as a major drawback, the frequent cloud cover experienced in many countries. This is one of the main reasons why topographic maps at 1:100,000 scale and larger are often outdated. The results of a study which investigated the possibilities of fusing up‐to‐date spaceborne microwave data with existing images from optical sensors for topographic map updating at a scale of 1:100, 000 are presented in this paper. A key issue researched was the influence of geometric distortions and corrections of remote sensing data on the results of pixel based digital image fusion. After having terrain‐geocoded and radiometrically enhanced imagery from the Landsat, SPOT, ERS‐1 and JERS‐1 satellites, the data were fused applying a variety of colour transformation techniques as well as statistical or arithmetic methods. Initially, the image fusion was implemented using images covering a test site in the north of The Netherlands in order to calibrate speci...

A review of remote sensing applications for oil palm studies

Abstract Oil palm becomes an increasingly important source of vegetable oil for its production exceeds soybean, sunflower, and rapeseed. The growth of the oil palm industry causes degradation to the environment, especially when the expansion of plantations goes uncontrolled. Remote sensing is a useful tool to monitor the development of oil palm plantations. In order to promote the use of remote sensing in the oil palm industry to support their drive for sustainability, this paper provides an understanding toward the use of remote sensing and its applications to oil palm plantation monitoring. In addition, the existing knowledge gaps are identified and recommendations for further research are given.

Ehlers pan-sharpening performance enhancement using HCS transform for n -band data sets

ABSTRACT The Ehlers fusion method, which combines a standard intensity-hue-saturation (IHS) transform with fast Fourier transform filtering, is a high spectral characteristics preservation algorithm for multitemporal and multisensor data sets. However, for data sets of more than three bands, the fusion process is complicated, because only every three bands are fused repeatedly for multiple times until all bands are fused. The hyper-spherical colour sharpening (HCS) fusion method can fuse a data set with an arbitrary number of bands. The HCS approach uses a transform between an n-dimensional Cartesian space and an n-dimensional hyper-spherical space to get one single intensity component and n − 1 angles. Moreover, from a structural point of view, the hyper-spherical colour space is very similar to the IHS colour space. Hence, we propose to combine the Ehlers fusion with an HCS transform to fuse n-band data sets with high spectral information preservation, even hyper-spectral images. A WorldView-2 data set including a panchromatic and eight multispectral bands is used for demonstrating the effectiveness and quality of the new Ehlers –HCS fusion. The WorldView-2 image covers different landscapes such as agriculture, forest, water and urban areas. The fused images are visually and quantitatively analysed for spectral preservation and spatial improvement. Pros and cons of the applied fusion methods are related to the analysed different landscapes. Overall, the Ehlers –HCS method shows the efficacy for n-band fusion.

Increasing the potential of Razaksat images for map-updating in the Tropics

The high resolution remote sensing satellite Razaksat is a unique satellite system since it operates in a near-equatorial orbit with a low inclination angle of 9. In a first study scientists have found the images suitable for feature extraction in an urban context to update the road network at a scale of 1:25,000. In a preceding project for land cover mapping the research team used the five available bands of Razaksat imagery. This paper describes a continuation of the former study in which techniques are used to fuse the high resolution panchromatic band with the lower resolution multispectral bands. The study investigates the impact of pansharpening on the spatial and spectral content of the data. It compares various image fusion techniques and their impact on land use classification results. The image fusion techniques investigated are Brovey Transform, High Pass Filtering, Principal Component Analysis, Wavelet Approach and Ehlers Fusion. The images are classified using a maximum likelihood classifier. The results show that the use of an appropriate image fusion technique with adequately tuned parameters can improve quality of the resulting thematic maps.

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.

Application of standing waves as audible information in hypertension therapy

Globally, there are 9.4 million cardiovascular deaths accounted for by hypertension complications. Prediction studies reveal that this number will increase to 1.15 billion in 2025 due to lack of awareness and insufficient treatment. Treatments in lowering blood pressure are less successful. Another factor is the presence of hypertension medication resistance among patients. This suggests that a solution to treat hypertension has to be found in non-pharmalogical approaches. In this study, standing waves are implemented in an audio therapy to lower blood pressure values among the tested patients. 34 subjects from both genders of different age groups joined this study. The results are promising. In total, 65% of the participating patients experienced lower systolic blood pressure values, while 53% experienced lower diastolic values. An important finding is that parallel medication interferes with the therapy and yields no improvement. This study implies that standing waves therapy is an encouraging approach for treating hypertension in a long term. Future studies will be conducted with improved experimental conditions and larger subject groups for better results.