Application of drone for landslide mapping,dimension estimation and its 3D reconstruction

Dimension estimation of landslides is a major challenge while preparing the landslide inventory map, for which very high-resolution satellite data/aerial photography is required, which is very expensive. An alternative is the application of drones for such mapping. This study presents the utility of drone/unmanned aerial vehicle (UAV) for mapping and 3D reconstruction of two landslides near IIT Mandi, Himachal Pradesh. In this study, we used DJI Phantom 3 Advanced drone to collect high-resolution images of landslides. Features in the images were automatically detected, described, and matched among photographs using scale invariant feature transform (SIFT) technique. The 3D position and orientation of the cameras and the XYZ location of each feature in the photographs was estimated using bundle block adjustment. This resulted in sparse 3D point cloud, which was densified using Clustering View for Multi-View Stereo (CMVS) algorithm. Finally, surface reconstruction was done using Poisson Surface Reconstruction method, which was visualised in open source software CloudCompare. The 3D model, generated from drone images, was validated using field measurements of some objects, and 3D surface created from total station. Various quantities i.e. width (length), height and perimeter were measured in the 3D drone model and verified with total station data. The differences among all the measured quantities for both the landslides are less than 5% keeping the measurements of total station as reference. The 3D reconstructed from the sets of photographs is very accurate giving the measurements up to cm level and even small objects could be easily identified. In addition, digital elevation model (DEM) of sub meter resolution could be easily generated and used for various applications. Hence drone-based imagery in combination with 3D scene reconstruction algorithms provide flexible and effective tools to map and monitor landslide apart from accurately assessing the dimensions of the landslides.     

Two‐dimensional flow patterns near contour grass hedges

Grass hedges are narrow strips of stiff‐stemmed vegetation used to control erosion and sediment delivery. When planted on the contour, the hydraulic resistance of the vegetation slows runoff, creates ponding, and promotes sediment deposition. When tillage is performed between grass hedges, soil may be thrown against the vegetation, where it settles to form a berm within the hedge. Tillage‐induced berms divert part of runoff, causing it to flow alongside the hedge without crossing it. Such flow partitioning created by grass hedges was measured on experimental plots located on silt loam loess soil near Holly Springs, Mississippi, USA, where hedges planted at the bottom of 5%, 22.1‐m‐long slopes evolved berms averaging 0.13 m in height. They diverted about 80% of the runoff for events smaller than 5 mm and about 50% for large events. A two‐dimensional model was developed to determine overland flow patterns over complex terrains, accounting for oriented roughness created by tillage corrugations, crop rows, and larger features such as berms and vegetative barriers. The model was used to reproduce the flow partition observed in the field experiments and to determine how berm height and slope steepness and length affected runoff redistribution. Numerical simulations indicated that for most runoff events, ponded runoff depths were not high enough to overtop the berm but rather crossed the berms through cracks and gaps, represented in the model as small triangular weirs. The model also was applied to a 6.0‐ha watershed in Western Iowa, USA, where nine grass hedges were planted across 12–16% slopes. Computed dynamic flow properties showed that berms increased the amount of runoff flowing laterally upslope of the hedges and that a large portion of the runoff crossed the vegetative strips at a few locations and with high flow depths, increasing the risk of development of ephemeral gullies. Copyright © 2011 John Wiley & Sons, Ltd.     

Galaxy formation in the reionization epoch as hinted by Wide Field Camera 3 observations of the Hubble Ultra Deep Field

We present a large sample of candidate galaxies at z ≈ 7-10,selected in the Hubble Ultra Deep Field using the new observations of the Wide Field Camera 3that was recently installed on the Hubble Space Telescope.Our sample is composed of 20 z850-dropouts(four new discoveries),15 Y105-dropouts(nine new discoveries)and 20 J125-dropouts(all new discoveries).The surface densities of the z850-dropouts are close to what was predicted by earlier studies,however,those of the Y105-and J125-dropouts are quite unexpected.While no Y105-or J125-dropouts have been found at AB < 28.0 mag,their surface densities seem to increase sharply at fainter levels.While some of these candidates seem to be close to foreground galaxies and thus could possibly be gravitationally lensed,the overall surface densities after excluding such cases are still much higher than what would be expected if the luminosity function does not evolve from z～7 to 10.Motivated by such steep increases,we tentatively propose a set of Schechter function parameters to describe the luminosity functions at z ≈ 8 and 10.As compared to their counterpart at z ≈ 7,here L*decreases by a factor demanded by the existing observations,they are allowed and seem to agree with the data better than other alternatives.If these luminosity functions are still valid beyond our current detection limit,this would imply a sudden emergence of a large number of low-luminosity galaxies when looking back in time to z ≈ 10,which,while seemingly exotic,would naturally fit in the picture of the cosmic hydrogen reionization.These early galaxies could easily account for the ionizing photon budget required by the reionization,and they would imply that the global star formation rate density might start from a very high value at z ≈ 10,rapidly reach the minimum at z ≈ 7,and start to rise again towards z ≈ 6.In this scenario,the majority of the stellar mass that the universe assembled through the reionization epoch seems still undetected by current observations at z ≈ 6.     

Environmental patchiness,litter decomposition and associated faunal patterns in a Spartina alterniflora marsh

Spartina alterniflora leaf litter bundles were placed in a North Carolina salt marsh to study the effects of environmental heterogeneity on decomposition and animal colonization. Sediment type (mud vs. sand), tidal inundation zone (near bay, mid-marsh and upper marsh) and Spartina growth form (tall vs. short) were studied. Tidal zone had the greatest effect on decomposition rate. The main effects of sediment type and growth form were not significant. All treatments affected animal distribution patterns in the leaf bundles. Nearly all common taxa were more common on mud than sand. Most taxa showed a strong association with one tidal zone. Half of the taxa were associated with one of the Spartina growth forms. Many interactions among the treatments were also significant.This study demonstrates the significance of environmental heterogeneity in a Spartina marsh both for litter decomposition and animal distributions.     

Subsistence in coastal fisheries policy: What's in a word?

Consideration of subsistence fishing activities seems particularly relevant to coastal fisheries policy, yet formal recognition of subsistence fishing is often absent from associated policy frameworks. A critical problem is the very meaning of the term “subsistence.” A review of the literature on subsistence, dominated until recently by North American research, reveals a schism between interpretations emphasizing material aspects of subsistence and interpretations highlighting cultural aspects. The North American literature on the subject is heavily influenced by a focus on Arctic indigenous populations emphasizing cultural survival. Ultimately, subsistence can be a matter of survival in the belly, the soul, or both. International case studies suggest that different interpretations of subsistence are appropriate in different circumstances, and that appropriate policy can be fashioned only after the local context of subsistence is understood.     

Domain choice in an experimental nested modeling prediction system for South America

Summary The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Ni?o) and January–March 1985 (La Ni?a). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies.     

A model for the relation between spreading rate and oblique spreading

Atwater and Macdonald have suggested that oblique spreading occurs at mid-ocean ridges which spread slowly (half rate less than 3 cm/yr), while the spreading is perpendicular at faster-spreading ridges. This paper explores this relation using the ratio of the power dissipated at ridges to that on transform faults to find the angle of oblique spreading (θ). The dependence of the energy dissipation rate on spreading rate is included in simple models of a ridge and transform. These arguments suggest that θ is related to the half spreading rate approximately by sin θ ～ V^?1.     

The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction

For lack of sufficient observations, the definition of atmospheric moisture fields (including water vapor and clouds) remains a difficult problem whose solution is essential for improved weather forecasts. Moisture fields are under-observed in time and space, primarily because the distribution of water in the atmosphere is highly variable. Because water is important in weather and climate processes, a significant effort has been expended to develop new or improved remote sensing systems to mitigate this problem. One such system uses ground-based Global Positoning System (GPS) receivers to make accurate all-weather estimates of atmospheric refractivity at very low cost. This largely unanticipated application of GPS had led to a new and potentially significant upper-air observing system for meteorological agencies and researchers around the world (Wolfe & Gutman, 2000). The first and most mature use of GPS for this purpose is in the estimation of integrated (total column) precipitable water vapor above a fixed site (Duan et al., 1996, with improvements by Niell, 1996, and Fang et al., 1998). The techniques currently used by the National Oceanic and Atmospheric Administration's Forecast Systems Laboratory (NOAA/FSL) to collect, process, and distribute GPS water vapor observations are mature and almost ready for transition to operational use. NOAA/FSL has shown that GPS integrated water vapor data can be used effectively in objective (i. e., numerical weather prediction) and subjective weather forecasting. To understand the strengths and limitations of GPS for weather forecasting, it is essential to understant what types of information are currently available to forecasters and modelers, and how models use the data to describe the current and probable future state of the atmosphere. It is also important to understand the current trends in modern weather prediction to ensure that GPS observing system play a significant role in the future. ? 2001 John Wiley & Sons, Inc.     

An assessment of the time-dependence structure of streams in New Jersey,USA

The lag-one serial correlation coefficient is one of the important hydrological metric used as a quantitative measure of carry-over capacity of water stored within a catchment. In this study, the annual lag-one serial correlation coefficient has been computed for 27 unregulated streams spread across the two main climatic regions of New Jersey, USA. The computed mean annual lag-one serial correlation coefficient was found to be 0.17, which is typical of the national value. It appears that streams that drain northern catchments have higher carry-over capacity in comparison to their southern counterparts. Further, the Goud–Dincer Gamma method of reservoir storage capacity was used to compare the average reservoir storage needed to meet the over-year storage requirement for a hypothetical reservoir located within the two main climatic regions. The results revealed that on average, a reservoir needed to meet over-year storage requirements in climate region 1 (northern New Jersey) needs to be a little more than one half times as large as those in climate region 2 (southern New Jersey) for the same level of regulation. Though groundwater recharge to streams in the southern catchments are generally higher than their northern counterparts, it appears relatively less ground water (release from storage) in any given year in the south is carried from the previous year(s).