Colour Hue and Texture Evaluation for 3D Symbolization of Indoor Environments Using RGB-D Data

In this work an evaluation procedure of the use of colour hue and texture for 3D symbolization of indoor environments using RGB-D data is presented. The main characteristics of the proposed method involve RGB-D cameras to collect colour and depth data and the evaluation of the visual variables colour hue and texture combined with visual aspects such as lighting and camera configuration for the symbolization of 3D indoor environments. High quality coloured point clouds of indoor environments are obtained with the Kinect sensor and then registered and processed in order to create 3D models. These sets of point clouds can be detected, recognized and classified under one of the three following main categories: ceiling, wall or floor. After classification is done, the resulting point clouds are properly treated as 3D triangular meshes in the MeshLab software. These meshes are then filtered to form complete surfaces which are then refined before being considered for visual variable application. We evaluated the proposed method on several indoor environments to show that it efficiently combines the colour and depth data obtained from RGB-D cameras with different parameters defined for the visual variables colour hue and texture for 3D symbolization of indoor environments.     

Definition of geochemical patterns on the soil of Paul de Arzila using correspondence analysis

The aim of this study is to define geochemical and geological patterns, not only inside of Paul de Arzila natural reserve but in the surrounding area. The Correspondence Analysis was used as a discriminate technique to separate previously identified groups, in this case three types of soils (cambisols + luvisols + fluvisols). The purpose was to identify the main chemical association representative for the local types of soils. The results allow us to separate the chemical elements that are related to natural sources from the anthropogenic sources.     

Evaluating subsurface structures and stratigraphic units using 2D electrical and magnetic data at the area north Greater Cairo,Egypt

2D dipole–dipole resistivity data and ground magnetic survey are used in combination with available data from boreholes and surface geology to detect subsurface structures and stratigraphic units and to study the ability of the site area (located at north Grater Cairo) for a building construction.     

Predicting monthly precipitation along coastal Ecuador: ENSO and transfer function models

Theoretical and Applied Climatology - It is well known that El Niño-Southern Oscillation (ENSO) modifies precipitation patterns in several parts of the world. One of the most impacted areas is...     

Climatology and trend analysis of extreme precipitation in subregions of Northeast Brazil

The present paper aims of computing climatology and trend analysis of occurrence and intensity of extreme events of precipitation in subregions of Northeast Brazil (NEB). We used daily rainfall data of 148 rain gauges collected from the hydrometeorological network managed by the National Water Agency during 1972 to 2002 and used quantiles technique in order to select rainfall events. Defining heavy rainfall events as those when at least one rain gauge recorded rainfall above the 95th percentile, normal rainfall was between the 45th and 55th percentiles, and weak rainfall events were under the 5th percentile. The Mann-Kendall nonparametric test was used to calculate the linear trend of the quantity and intensity of rainfall events. The NEB was divided in five subregions using the cluster analysis based on Euclidean distance and Ward’s method: Northern coast, Northern semiarid, Northwest, Southern semiarid, and Southern coast. The results suggest that the subregions are less influenced by El Niño and La Niña, and dry areas have higher variability, with the greatest number of intense events.     

Spatiotemporal variability of methane over the Amazon from satellite observations

The spatiotemporal variability of the greenhouse gas methane(CH_4) in the atmosphere over the Amazon is studied using data from the space-borne measurements of the Atmospheric Infrared Sounder on board NASA's AQUA satellite for the period 2003–12. The results show a pronounced variability of this gas over the Amazon Basin lowlands region, where wetland areas occur. CH_4 has a well-defined seasonal behavior, with a progressive increase of its concentration during the dry season, followed by a decrease during the wet season. Concerning this variability, the present study indicates the important role of ENSO in modulating the variability of CH_4 emissions over the northern Amazon, where this association seems to be mostly linked to changes in flooded areas in response to ENSO-related precipitation changes. In this region, a CH_4 decrease(increase) is due to the El Nino-related(La Ni ?na-related) dryness(wetness). On the other hand, an increase(decrease) in the biomass burning over the southeastern Amazon during very dry(wet) years explains the increase(decrease) in CH_4 emissions in this region. The present analysis identifies the two main areas of the Amazon, its northern and southeastern sectors, with remarkable interannual variations of CH_4. This result might be useful for future monitoring of the variations in the concentration of CH_4, the second-most important greenhouse gas, in this area.     

Groundwater,Acid and Carbon Dioxide Dynamics Along a Coastal Wetland,Lake and Estuary Continuum

Coastal wetlands are hotspots for biodiversity and biological productivity, yet the hydrology and carbon cycling within these systems remains poorly understood due to their complex nature. By using a novel spatiotemporal approach, this study quantified groundwater discharge and the related inputs of acidity and CO₂ along a continuum of a modified coastal acid sulphate soil (CASS) wetland, a coastal lake and an estuary under highly contrasting hydrological conditions. To increase the resolution of spatiotemporal data and advance upon previous methodologies, we relied on automated observations from four simultaneous time-series stations to develop multiple radon mass balance models to estimate groundwater discharge and related groundwater inputs of acidity and dissolved inorganic carbon (DIC), along with surface water to atmosphere CO₂ fluxes. Spatial surveys indicated distinct acid hotspots with minimum surface water pH of 2.91 (dry conditions) and 2.67 (flood conditions) near a non-remediated (drained) CASS area. Under flood conditions, groundwater discharge accounted for ～14.5 % of surface water entering the lake. During the same period, acid discharge from the acid sulphate soil section of the continuum produced ～4.8 kg H₂SO₄?ha^?1 day^?1, a rate much higher than previous studies in similar systems. During baseflow conditions, the low pH water was rapidly buffered within the estuarine lake, with the pH increasing from 4.22 to 6.07 over a distance of ～250 m. The CO₂ evasion rates within the CASS were extremely high, averaging 2163?±?125 mmol m^?2 day^?1 in the dry period and 4061?±?259 mmol m^?2 day^?1 under flood conditions. Groundwater input of DIC could only account for 0.4 % of this evasion in the dry conditions and ～5 % during the flood conditions. We demonstrated that by utilising a spatiotemporal (multiple time-series stations) approach, the study was able to isolate distinct zones of differing hydrology and biogeochemistry, whilst providing more reasonable groundwater acid input estimates and air–water CO₂ flux estimates than some traditional sampling designs. This study highlights the notion that modified CASS wetlands can release large amounts of CO₂ to the atmosphere because of high groundwater acid inputs and extremely low surface water pH.