Effect of climatic oscillations on flood occurrence on Papaloapan River,México,during the 1550–2000 period

This study presents a chronology of historical and measured flood events in the Papaloapan River basin of Mexico during 450 years. Twenty-eight historical floods were recorded during the period 1550–1948 on this river and one flood event (1969) in the instrumental era (1949–2000), of which 14 were extraordinary floods and only 15 were catastrophic ones. There were several flood-rich decades during 1860–1870, 1880–1890, 1920–1930 and 1940–1950. Wavelet analysis found a significant flooding periodicity of 58 years. The wavelet coherence analysis found that flooding had an in-phase relationship with the Atlantic Multidecadal Oscillation and also with the Pacific Decadal Oscillation. Logistic regression corroborated that there exists a positive relationship between floods events and these two natural climatic oscillations. The logistic regression model predicted correctly 92% of flood events.     

Assessing the performance of WRF model in predicting high-impact weather conditions over Central and Western Africa: an ensemble-based approach

Natural Hazards - For numerical weather prediction over a particular region, it is important to know the best combination of physical parameterizations available in the considered modelling frame...     

Influence of the sediment delivery ratio index on the analysis of silting and break risk in the Plasencia reservoir (Central System,Spain)

The random forest method was used to generate susceptibility maps for debris flows, rock slides, and active layer detachment slides in the Donjek River area within the Yukon Alaska Highway Corridor, based on an inventory of landslides compiled by the Geological Survey of Canada in collaboration with the Yukon Geological Survey. The aim of this study is to develop data-driven landslide susceptibility models which can provide information on risk assessment to existing and planned infrastructure. The factors contributing to slope failure used in the models include slope angle, slope aspect, plan and profile curvatures, bedrock geology, surficial geology, proximity to faults, permafrost distribution, vegetation distribution, wetness index, and proximity to drainage system. A total of 83 debris flow deposits, 181 active layer detachment slides, and 104 rock slides were compiled in the landslide inventory. The samples representing the landslide free zones were randomly selected. The ratio of landslide/landslide free zones was set to 1:1 and 1:2 to examine the results of different sample ratios on the classification. Two-thirds of the samples for each landslide type were used in the classification, and the remaining 1/3 were used to evaluate the results. In addition to the classification maps, probability maps were also created, which served as the susceptibility maps for debris flows, rock slides, and active layer detachment slides. Success and prediction rate curves created to evaluate the performance of the resulting models indicate a high performance of the random forest in landslide susceptibility modelling.     

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

The digital ‘connected’ earth: open technology for providing location-based services on degraded communication environments

In the current world, it is easy to listen that everybody and everything is connected. Over this connected world, the concept of location-based services has grown in order to provide digital services in everyplace and at every time. Nevertheless, this is not 100% true because the connection is not guaranteed for many people and in many places. These are the Degraded Communications Environments (DCE), environments where the availability of high-speed communications is not guaranteed in at least the 75% of the time. This paper works over the experience of a previous work in developing light protocols that do not need broadband for communication. This work provides an extension of these protocols for the inclusion of mobile devices as elements of the communication process and a set of libraries to allow the development of applications in DCE. The work done has involved the development of two frameworks: an Android framework that makes the incorporation of Android devices easier and a server-based framework that provides the server side for the development of the referred applications. A use case that uses these two frameworks has been developed. Finally, all technology developed is available throw a public Git repository.     

Revisit the calibration errors on experimental slant total electron content (TEC) determined with GPS

The calibration errors on experimental slant total electron content (TEC) determined with global positioning system (GPS) observations is revisited. Instead of the analysis of the calibration errors on the carrier phase leveled to code ionospheric observable, we focus on the accuracy analysis of the undifferenced ambiguity-fixed carrier phase ionospheric observable determined from a global distribution of permanent receivers. The results achieved are: (1) using data from an entire month within the last solar cycle maximum, the undifferenced ambiguity-fixed carrier phase ionospheric observable is found to be over one order of magnitude more accurate than the carrier phase leveled to code ionospheric observable and the raw code ionospheric observable. The observation error of the undifferenced ambiguity-fixed carrier phase ionospheric observable ranges from 0.05 to 0.11 total electron content unit (TECU) while that of the carrier phase leveled to code and the raw code ionospheric observable is from 0.65 to 1.65 and 3.14 to 7.48 TECU, respectively. (2) The time-varying receiver differential code bias (DCB), which presents clear day boundary discontinuity and intra-day variability pattern, contributes the most part of the observation error. This contribution is assessed by the short-term stability of the between-receiver DCB, which ranges from 0.06 to 0.17 TECU in a single day. (3) The remaining part of the observation errors presents a sidereal time cycle pattern, indicating the effects of the multipath. Further, the magnitude of the remaining part implies that the code multipath effects are much reduced. (4) The intra-day variation of the between-receiver DCB of the collocated stations suggests that estimating DCBs as a daily constant can have a mis-modeling error of at least several tenths of 1 TECU.     

Image-aided platform orientation determination with a GNSS/low-cost IMU system using robust-adaptive Kalman filter

The availability of miniaturized sensors with enhanced capabilities, new methods for image processing, and easy access to small and low-weight airborne platforms for data acquisition, including unmanned vehicles, opens new possibilities for geodetic navigation applications and developing new developments in sensor fusion. In this context, the development of efficient methods, based on low-cost sensors, to extract precise georeferenced information from digital cameras is of utmost interest. We present a method to improve the performance of the integration of GNSS/low-cost IMU by exploiting the orientation changes retrieved from digital images. In this work, a robust-adaptive Kalman filter is also introduced to further improve the performance of the method deployed. The adaptive factor and the robust factor accomplished are determined by innovation information and the threshold value of orientation changes between consecutive images. Results from airborne tests used to assess the performance of the method are presented. The results show that using a non-metric camera, the Euler angle estimation accuracy of the GNSS/low-cost IMU integration can be improved to be close to 0.5 degree and an additional improvement, which can reach 59%, can be achieved after using the robust-adaptive Kalman filter.     

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as “The Internet of Things” solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.     

‘Filament’ marker beds in the Karababa-A Member (Turonian) of the Arabian platform,SE Turkey: Palaeo-environmental significance,stratigraphy and correlation potential

A ‘filament’ event bed/level corresponds to the occurrence of thin elongate calcitic, shells, or plates of pelagic, bivalve or crinoidal, origin, within pelagic, laminated and organic-matter rich limestones. These organic-rich limestones had been generally deposited under hypoxic/anoxic conditions in an outer-ramp environment. These thin elongate, bivalve shells, or crinoidal plates, are found broken in small pieces, disintegrated, or simply preserved parallel to bedding as almost complete specimens. Such ‘filament’ beds were spotted in SE Turkey in deposits, namely the Karababa-A Member, around the Cenomanian-Turonian boundary (C/TB) and above. On a global scale, these filament event beds illustrate sea-level rise related to eustacy and/or climatic change. The abundance of filaments close to the C/TB is a biological marker of high organic productivity resulting from a climatic change to warmer conditions. The prevailing higher sea-level conditions were then favourable to the accumulation and preservation of organic-rich facies, characteristic of the Oceanic Anoxic Event 2 (OAE2). Using both biostratigraphic and carbon isotopic data, those deposits were dated from the latest Cenomanian-Turonian age. ‘Filament’ event beds were recorded in the same order, except for some small differences. A good number of these bio-events are global. Consequently, on a global scale, they are susceptible to constrain the C/TB, especially the base of the Turonian stage, with a significant degree of confidence.     

Use of Recycled Polyethylene Terephthalate Strips in Soil Improvement

Geotechnical and Geological Engineering - Many studies have investigated polyethylene terephthalate (PET) and polypropylene fibers in soil improvement. However, there is a lack of research using...