Linear discriminant analysis to describe the relationship between rainfall and landslides in Bogotá, Colombia

Bogotá is located in the central Andean region of Colombia, which is frequently affected by landslide processes. These processes are mostly triggered during the rainy season in the city. This fact remarks the importance of determining what rain-derived parameters (e.g. intensity, antecedent rain, daily rain) are better related with the occurrence of landslides. For this purpose, the linear discriminant analysis (LDA), a technique derived from multivariate statistics, was used. The application of this type of analysis led to obtain simple mathematical functions that represent the probability of occurrence of landslides in Bogotá. The functions also allow to identify the most relevant variables derived from records of rainfall linked to the generation of landslides. A proof of concept using the proposed methodology was done using historic rainfall data from a 9-km² area of homogenous climatology and geomorphology in the south part of Bogotá. Landslides needed to be grouped for the LDA. Each one of these grouping categories represents landslides that occurred in similar geomorphologic conditions. Another set of events with no landslides was generated synthetically. Results of the proof of concept show that rainfall parameters such as normalized rainfall intensity I _MAP, normalized daily rainfall R _MAP and rainy-days normal RDN have the best statistical correlation with the landslides observed in the zone of analysis.     

Effect of frictional heating and thermal advection on pre-seismic sliding: a numerical simulation using a rate-, state- and temperature-dependent friction law

Laboratory experiments on simulated faults in rocks clearly show the temperature dependence of dynamic rock friction. Since rocks surrounding faults are permeable, we have developed a numerical method to describe the thermo-mechanical evolution of the pre-seismic sliding phase which takes into account both the rate-, state- and temperature-dependent friction law and the heat advection term in the energy equation. We consider a laminar fluid motion perpendicular to a vertical fault plane and assume that fluids move away from the fault plane. A semi-analytical temperature solution which accounts for the variability of slip velocity and stress on the fault has been found. This solution has been generalized to the case of a time varying fluid velocity and then was used to include the thermal pressurization effect. After discretizing the temperature solution, the evolution of the system is obtained by the solution of a system of first order differential equations which allows us to determine the evolution of slip, slip rate, friction coefficient, effective normal stress, temperature and fluid velocity. The numerical solutions are found using a Runge-Kutta method with an adaptative stepsize control in time. When the thermal pressurization effects can be neglected, the heat advection effect gives rise to a delay, with respect to the purely conductive case, of the earthquake occurrence time. This delay increases with increasing permeability H of the system. When the thermal pressurization effects are taken into account the situation is opposite, i.e. the onset of instability tends to precede that of the purely conductive case. The advance in the time of occurrence of instability increases with increasing coefficient of thermal pressurization. In the small permeability range (H ≤ 10^?18 m²), the seismic moment and nucleation length of the pre-seismic phase are significantly smaller than those predicted by the purely conductive model.     

Europium-activated cathodoluminescence in minerals

Cathodoluminescence observations give information on the presence of europium in several minerals including apatite, fluorite, strontianite, and scheelite. Information on the oxidation state of the crystallization environment and on the partitioning of europium between coexisting mineral pairs may be obtained.The apatite in carbonatites and genetically related igneous rocks almost always contains europium in the divalent state. Occasionally both divalent and trivalent europium are observed.Europium is preferentially incorporated into strontianite when it crystallizes together with apatite in these same rocks. Similar results are found for fiuorite.     

On the heat budget of the Arabian Sea

This study analyzes the heat budget of the Arabian Sea using satellite-derived sea-surface temperature (SST) from 1985 to 1995 along with other data sets. For a better understanding of air–sea interaction, canonical average monthly fields representing the spatial and temporal structure of the various components of the heat balance of the Arabian Sea are constructed from up to 30 years of monthly atmospheric and oceanic data. The SST over the Arabian Sea is not uniform and continually evolves with time. Cooling occurs over most of the basin during November through January and May through July, with the greatest cooling in June and July. Warming occurs over most of the basin during the remainder of the year, with the greatest warming occurring in March and September. Results indicate that the sign of the net heat flux is strongly dependent on the location and month. The effects of net heat flux and penetrative solar radiation strongly influence the change in SST during February and are less important during August and September. Horizontal advection acts to cool the sea surface during the northeast monsoon months. During the southwest monsoon horizontal advection of surface waters warms the SST over approximately the southern half of the basin, while the advection of upwelled water from the Somalia and Oman coasts substantially cools the northern basin. The central Arabian Sea during the southwest monsoon is the only area where the change in SST is balanced by the entrainment and turbulent diffusion at the base of the mixed layer. Agreement between the temporal change in the satellite-derived SST and the change calculated from the conservation of heat equation is surprisingly good given the errors in the measured variables and the bulk formula parameters. Throughout the year, monthly results over half of the basin agree within 3°. Considering that the SST changes between 8° and 12° over the year, this means that our results explain from 62% to 75% of the change in SST over 56% of the Arabian Sea. Two major processes contribute to the discrepancy in the change in SST calculated according to the heat budget equation and the change in SST derived from satellite observations. The first is the effect of the horizontal advection term. The position of the major eddies and currents during the southwest monsoon greatly affects the change in SST due to the large gradient in temperature between the cold upwelled waters along the Somali coast to the warm waters in the interior of the basin. The second major process is the thermocline effect. In areas of shallow mixed-layer depth, high insolation and wind speeds of either less than 3 m/s or greater than 15 m/s, the bulk formulae parameterization of the surface heat fluxes is inappropriate.     

Terrestrial laser scanning to estimate plot-level forest canopy fuel properties

This paper evaluates the potential of a terrestrial laser scanner (TLS) to characterize forest canopy fuel characteristics at plot level. Several canopy properties, namely canopy height, canopy cover, canopy base height and fuel strata gap were estimated. Different approaches were tested to avoid the effect of canopy shadowing on canopy height estimation caused by deployment of the TLS below the canopy. Estimation of canopy height using a grid approach provided a coefficient of determination of R² = 0.81 and an RMSE of 2.47 m. A similar RMSE was obtained using the 99th percentile of the height distribution of the highest points, representing the 1% of the data, although the coefficient of determination was lower (R² = 0.70). Canopy cover (CC) was estimated as a function of the occupied cells of a grid superimposed upon the TLS point clouds. It was found that CC estimates were dependent on the cell size selected, with 3 cm being the optimum resolution for this study. The effect of the zenith view angle on CC estimates was also analyzed. A simple method was developed to estimate canopy base height from the vegetation vertical profiles derived from an occupied/non-occupied voxels approach. Canopy base height was estimated with an RMSE of 3.09 m and an R² = 0.86. Terrestrial laser scanning also provides a unique opportunity to estimate the fuel strata gap (FSG), which has not been previously derived from remotely sensed data. The FSG was also derived from the vegetation vertical profile with an RMSE of 1.53 m and an R² = 0.87.     

Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR

Background

Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them.

Results

Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m^?2. Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R² ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha^?1 for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha^?1 for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R² ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha^?1 [between 0.69–0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha^?1] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R² was between 0.58–0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha^?1 for the echo-based model, whereas for the CHM R² was between 0.37–0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha^?1.

Conclusions

Metrics derived from the CHM show a higher dependence on point density than metrics derived from the echo-based data model. Despite the median of the differences between metrics derived at different point densities differing significantly from zero, the mean change was close to zero and smaller than the standard deviation except for very low point densities (1 point m^?2). The application of calibrated models to estimate AGB on metrics derived from thinned datasets resulted in less than 5% error when metrics were derived from the echo-based model. For CHM-based metrics, the same level of error was obtained for point densities higher than 5 points m^?2. The fact that reducing point density does not introduce significant errors in AGB estimates is important for biomass monitoring and for an effective implementation of climate change mitigation policies such as REDD + due to its implications for the costs of data acquisition. Both data models showed similar capability to estimate AGB when point density was greater than or equal to 5 point m^?2.

     

Extreme rainfalls in SE South America

Heavy rainfall trends in a region of south-eastern South America during 1959–2002 were discussed using daily data of 52 meteorological stations of Argentina, Brazil and Uruguay. Changes in intensity and frequency were both studied with different statistical tests and approaches to check the significance of trends of single and regional aggregated rainfall series. There were predominant positive trends in the annual maximum rainfalls, as well as a remarkable increment in the frequency of heavy rainfalls over thresholds ranging from 50 to 150 mm. However, significant positive trends were not shown in the series of annual maximums and shown only in 15% to 30% of the series of frequencies over thresholds. This lack of significance is due to the high variability of heavy rainfalls in space and time, which makes difficult their capture by single rain gauges. Thus, when the assessment of the heavy rainfall indicators of intensity and frequency were conducted at the regional and sub-regional level, it showed significant trends, both in intensity and frequency over thresholds, with a clearer signal in central and eastern Argentina between 30° and 40° S.     

A very rare triple-peaked type-I X-ray burst in the low-mass X-ray binary 4U 1636−53

We have discovered a triple-peaked X-ray burst from the low-mass X-ray binary (LMXB) 4U 1636−53 with the Rossi X-ray Timing Explorer ( RXTE ). This is the first triple-peaked burst reported from any LMXB using RXTE , and it is only the second burst of this kind observed from any source. (The previous one was also from 4U 1636−53, and was observed with EXOSAT .) From fits to time-resolved spectra, we find that this is not a radius-expansion burst, and the same triple-peaked pattern seen in the X-ray light curve is also present in the bolometric light curve of the burst. Similar to what was previously observed in double-peaked bursts from this source, the radius of the emitting area increases steadily during the burst, with short periods in between during which the radius remains more or less constant. The temperature first increases steeply, and then decreases across the burst also showing three peaks. The first and last peak in the temperature profile occur, respectively, significantly before and after the first and last peaks in the X-ray and bolometric light curves. We found no significant oscillations during this burst. This triple-peaked burst, as well as the one observed with EXOSAT and the double-peak bursts in this source, all took place when 4U 1636−53 occupied a relatively narrow region in the colour–colour diagram, corresponding to a relatively high (inferred) mass-accretion rate. No model presently available is able to explain the multiple-peaked bursts.     

Stepwise selection of functional covariates in forecasting peak levels of olive pollen

High levels of airborne olive pollen represent a problem for a large proportion of the population because of the many allergies it causes. Many attempts have been made to forecast the concentration of airborne olive pollen, using methods such as time series, linear regression, neural networks, a combination of fuzzy systems and neural networks, and functional models. This paper presents a functional logistic regression model used to study the relationship between olive pollen concentration and different climatic factors, and on this basis to predict the probability of high (and possibly extreme) levels of airborne pollen, selecting the best subset of functional climatic variables by means of a stepwise method based on the conditional likelihood ratio test.