SAR Interferometric phase noise reduction using wavelet transform

The problem of synthetic aperture radar interferometric phase noise reduction is addressed. A new technique based on discrete wavelet transforms is presented. This technique guarantees high resolution phase estimation without using phase image segmentation. Areas containing only noise are hardly processed. Tests with synthetic and real interferograms are reported.

Reconstruction of the join time-delay Doppler-scale reflectivity density in the wide-band regime. A frame theory based approach

The inverse scattering problem concerning the determination of the joint time-delayDoppler-scale reflectivity density characterizing continuous target environments is addressed by recourse to the generalized frame theory. A reconstruction formula,involving the echoes of a frame of outgoing signals and its corresponding reciprocalframe, is developed. A ‘‘realistic’’ situation with respect to the transmission ofa finite number of signals is further considered. In such a case, our reconstruction formula is shown to yield the orthogonal projection of the reflectivity density onto a subspace generated by the transmitted signals.

Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0.13 Mg ha-1 on May 24, 2009 (dry season) to 62.0 Mg ha-1 on March 11, 2007 (rainy season). In these dates, maximum losses in the watershed were 2.2 and 781.5 Mg ha-1 , respectively. Mean annual soil loss in the watershed was 109.5 Mg ha-1 , but the central area, with a loss of nearly 300.0 Mg ha-1 , was characterized as a site of high water-erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Image-Based Coral Reef Classification and Thematic Mapping

This paper presents a novel image classification scheme for benthic coral reef images that can be applied to both single image and composite mosaic datasets. The proposed method can be configured to the characteristics (e.g., the size of the dataset, number of classes, resolution of the samples, color information availability, class types, etc.) of individual datasets. The proposed method uses completed local binary pattern (CLBP), grey level co-occurrence matrix (GLCM), Gabor filter response, and opponent angle and hue channel color histograms as feature descriptors. For classification, either k-nearest neighbor (KNN), neural network (NN), support vector machine (SVM) or probability density weighted mean distance (PDWMD) is used. The combination of features and classifiers that attains the best results is presented together with the guidelines for selection. The accuracy and efficiency of our proposed method are compared with other state-of-the-art techniques using three benthic and three texture datasets. The proposed method achieves the highest overall classification accuracy of any of the tested methods and has moderate execution time. Finally, the proposed classification scheme is applied to a large-scale image mosaic of the Red Sea to create a completely classified thematic map of the reef benthos

Characterization and management of rockslide hazard at Turtle Mountain, Alberta, Canada

In 1903, more than 30 million m3 of rock fell from the east slopes of Turtle Mountain in Alberta, Canada, causing a rock avalanche that killed about 70 people in the town of Frank. The Alberta Government, in response to continuing instabilities at the crest of the mountain, established a sophisticated field laboratory where state-of-the-art monitoring techniques have been installed and tested as part of an early-warning system. In this chapter, we provide an overview of the causes, trigger, and extreme mobility of the landslide. We then present new data relevant to the characterization and detection of the present-day instabilities on Turtle Mountain. Fourteen potential instabilities have been identified through field mapping and remote sensing. Lastly, we provide a detailed review of the different in-situ and remote monitoring systems that have been installed on the mountain. The implications of the new data for the future stability of Turtle Mountain and related landslide runout, and for monitoring strategies and risk management, are discussed.

Multispectral image compression using the wavelet transform

Multispectral images contain information from several spectral wavelengths and currently multispectral images are widely used in remote sensing and they are becoming more common in the field of computer vision and in industrial applications. Typically, one multispectral image in remote sensing may occupy hundreds of megabytes of disk space and several this kind of images may be received from a single measurement. This study considers the compression of multispectral images. The lossy compression is based on the wavelet transform and we compare the suitability of different waveletfilters for the compression. A method for selecting a wavelet filter for the compression and reconstruction of multispectral images is developed. The performance of the multidimensional wavelet transform based compression is compared to other compression methods like PCA, ICA, SPIHT, and DCT/JPEG. The quality of the compression and reconstruction is measured by quantitative measures like signal-to-noise ratio. In addition, we have developed a qualitative measure, which combines the information from the spatial and spectral dimensions of a multispectral image and which also accounts for the visual quality of the bands from the multispectral images.

Classification-Based compression of Multispectral Images

The purpose of this thesis is to present a new approach to the lossy compression of multispectral images. Proposed algorithm is based on combination of quantization and clustering. Clustering was investigated for compression of the spatial dimension and the vector quantization was applied for spectral dimension compression. Presenting algo¬rithms proposes to compress multispectral images in two stages. During the first stage we define the classes' etalons, another words to each uniform areas are located inside the image the number of class is given. And if there are the pixels are not yet assigned to some of the clusters then it doing during the second; pass and assign to the closest eta¬lons. Finally a compressed image is represented with a flat index image pointing to a codebook with etalons. The decompression stage is instant too. The proposed method described in this paper has been tested on different satellite multispectral images from different resources. The numerical results and illustrative examples of the method are represented too.

Interferometría SAR en las islas Shetlend del Sur: modelo numérico de elevaciones de la Isla Decepción

La interferometría con imágenes de radar de apertura sintética (SAR: Synthetic Aperture Radar) desde satélite es una técnica que permite obtener información altimétrica del relieve terrestre, siendo especialmente útil en áreas remotas. Este trabajo muestra una aplicación de esta técnica en las islas Shetland del Sur (Antártida). Para ello se han utilizado imágenes SAR obtenidas por los satélites ERS (European Remote Sensing) de la Agencia Espacial Europea (ESA: European Space Agency) y un proceso interferométrico desarrollado entre el Departament de Geodinàmica i Geofísica de la Universitat de Barcelona y el Institut Cartogràfic de Catalunya.

Lidar measurement of surface melt for a temperate Alpine glacier at the seasonal and hourly scales

This study shows how a new generation of terrestrial laser scanners can be used to investigate glacier surface ablation and other elements of glacial hydrodynamics at exceptionally high spatial and temporal resolution. The study area is an Alpine valley glacier, Haut Glacier d'Arolla, Switzerland. Here we use an ultra-long-range lidar RIEGL VZ-6000 scanner, having a laser specifically designed for measurement of snow- and ice-cover surfaces. We focus on two timescales: seasonal and daily. Our results show that a near-infrared scanning laser system can provide high-precision elevation change and ablation data from long ranges, and over relatively large sections of the glacier surface. We use it to quantify spatial variations in the patterns of surface melt at the seasonal scale, as controlled by both aspect and differential debris cover. At the daily scale, we quantify the effects of ogive-related differences in ice surface debris content on spatial patterns of ablation. Daily scale measurements point to possible hydraulic jacking of the glacier associated with short-term water pressure rises. This latter demonstration shows that this type of lidar may be used to address subglacial hydrologic questions, in addition to motion and ablation measurements.

Spatiotemporal Aspects of Environmental Monitoring in the Complex Coastal Region of Southwest Finland

The management and conservation of coastal waters in the Baltic is challenged by a number of complex environmental problems, including eutrophication and habitat degradation. Demands for a more holistic, integrated and adaptive framework of ecosystem-based management emphasize the importance of appropriate information on the status and changes of the aquatic ecosystems. The thesis focuses on the spatiotemporal aspects of environmental monitoring in the extensive and geomorphologically complex coastal region of SW Finland, where the acquisition of spatially and temporally representative monitoring data is inherently challenging. Furthermore, the region is subject to multiple human interests and uses. A holistic geographical approach is emphasized, as it is ultimately the physical conditions that set the frame for any human activity. Characteristics of the coastal environment were examined using water quality data from the database of the Finnish environmental administration and Landsat TM/ETM+ images. A basic feature of the complex aquatic environment in the Archipelago Sea is its high spatial and temporal variability; this foregrounds the importance of geographical information as a basis of environmental assessments. While evidence of a consistent water turbidity pattern was observed, the coastal hydrodynamic realm is also characterized by high spatial and temporal variability. It is therefore also crucial to consider the spatial and temporal representativeness of field monitoring data. Remote sensing may facilitate evaluation of hydrodynamic conditions in the coastal region and the spatial extrapolation of in situ data despite their restrictions. Additionally, remotely sensed images can be used in the mapping of many of those coastal habitats that need to be considered in environmental management. With regard to surface water monitoring, only a small fraction of the currently available data stored in the Hertta-PIVET register can be used effectively in scientific studies and environmental assessments. Long-term consistent data collection from established sampling stations should be emphasized but research-type seasonal assessments producing abundant data should also be encouraged. Thus a more comprehensive coordination of field work efforts is called for. The integration of remote sensing and various field measurement techniques would be especially useful in the complex coastal waters. The integration and development of monitoring system in Finnish coastal areas also requires further scientific assesement of monitoring practices. A holistic approach to the gathering and management of environmental monitoring data could be a cost-effective way of serving a multitude of information needs, and would fit the holistic, ecosystem-based management regimes that are currently being strongly promoted in Europe.

Engineering Geology for Society and Territory: volume 2: landslide processes

This book is one out of 8 IAEG XII Congress volumes, and deals with Landslide processes, including: field data and monitoring techniques, prediction and forecasting of landslide occurrence, regional landslide inventories and dating studies, modeling of slope instabilities and secondary hazards (e.g. impulse waves and landslide-induced tsunamis, landslide dam failures and breaching), hazard and risk assessment, earthquake and rainfall induced landslides, instabilities of volcanic edifices, remedial works and mitigation measures, development of innovative stabilization techniques and applicability to specific engineering geological conditions, use of geophysical techniques for landslide characterization and investigation of triggering mechanisms. Focuses is given to innovative techniques, well documented case studies in different environments, critical components of engineering geological and geotechnical investigations, hydrological and hydrogeological investigations, remote sensing and geophysical techniques, modeling of triggering, collapse, runout and landslide reactivation, geotechnical design and construction procedures in landslide zones, interaction of landslides with structures and infrastructures and possibility of domino effects. The Engineering Geology for Society and Territory volumes of the IAEG XII Congress held in Torino from September 15-19, 2014, analyze the dynamic role of engineering geology in our changing world and build on the four main themes of the congress: environment, processes, issues, and approaches.

Practices of place-making through locative media artworks

Peer-reviewed

Large slope deformations detection and monitoring along shores of the Potrerillos dam reservoir, Argentina, based on a small-baseline InSAR approach

The Argentina National Road 7 that crosses the Andes Cordillera within the Mendoza province to connect Santiago de Chile and Buenos Aires is particularly affected by natural hazards requiring risk management. Integrated in a research plan that intends to produce landslide susceptibility maps, we aimed in this study to detect large slope movements by applying a satellite radar interferometric analysis using Envisat data, acquired between 2005 and 2010. We were finally able to identify two large slope deformations in sandstone and clay deposits along gentle shores of the Potrerillos dam reservoir, with cumulated displacements higher than 25mm in 5years and towards the reservoir. There is also a body of evidences that these large slope deformations are actually influenced by the seasonal reservoir level variations. This study shows that very detailed information, such as surface displacements and above all water level variation, can be extracted from spaceborne remote sensing techniques; nevertheless, the limitations of InSAR for the present dataset are discussed here. Such analysis can then lead to further field investigations to understand more precisely the destabilising processes acting on these slope deformations.