Advances in positioning and wireless communicating technologies make it possible to collect large volumes of trajectory data of moving vehicles in a fast and convenient fashion. These data can be applied to traffic studies. Behind this application, a methodological issue that still requires particular attention is the way these data should be spatially visualized. Trajectory data physically consists of a large number of positioning points. With the dramatic increase of data volume, it becomes a challenge to display and explore these data. Existing commercial software often employs vector-based indexing structures to facilitate the display of a large volume of points, but their performance downgrades quickly when the number of points is very large, for example, tens of millions. In this paper, a pyramid-based approach is proposed. A pyramid method initially is invented to facilitate the display of raster images through the tradeoff between storage space and display time. A pyramid is a set of images at different levels with different resolutions. In this paper, we convert vector-based point data into raster data, and build a grid-based indexing structure in a 2D plane. Then, an image pyramid is built. Moreover, at the same level of a pyramid, image is segmented into mosaics with respect to the requirements of data storage and management. Algorithms or procedures on grid-based indexing structure, image pyramid, image segmentation, and visualization operations are given in this paper. A case study with taxi trajectory data in Shanghai is conducted. Results demonstrate that the proposed method outperforms the existing commercial software.

In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.

The response of the agro-ecological system to the environment includes the response of individual crop’s physiologic process and the adaption of the crop community to the environment. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. In this research, two typical agro-ecological models, the Decision Support System for Agro-technology Transfer (DSSAT) model and the Agro-ecological Zone (AEZ) model, are employed, and a framework for effective cross-scale data-model fusion is proposed and illustrated. The national observed data from 36 different agricultural observation stations and historical weather stations (1962-1999) are employed to estimate average crop productivity. Comparison of the two models’ estimations are consistent, which would indicate the possibility ofcross-scale crop model fusion.

Candidate division JS1-and Chloroflexi-related bacteria are ubiquitous in various deep marine sediments worldwide, yet almost nothing is known about their abundance and diversity in cold seep sediments. Here, we investigated the abundance and diversity of JS1- and Chloroflexi-related bacteria in a cold seep marine sediment core collected from the northern South China Sea (SCS) with the employment of quantitative polymerase chain reaction (qPCR) and 16S rRNA gene phylogenetic analyses. The qPCR results showed that 16S rRNA gene copies per gram of sediments for the total bacteria and JS1- and Chloroflexi-related bacteria were at magnitudes of 10⁸ and 10⁶, respectively. The relative abundance of JS1- and Chloroflexi-related 16S rRNA genes to that of total bacteria was 0.07%–8.78% throughout the core. Phylogenetic analyses showed that the JS-1 related clone sequences were dominant throughout the core. Our study provided insights into abundance and diversity of JS1- and Chloroflexi-related bacteria in the northern SCS cold seep sediments.

Nitrite-dependent anaerobic methane-oxidizing (n-damo) bacteria and anaerobic ammonia oxidizing (anammox) bacteria are two groups of microorganisms involved in global carbon and nitrogen cycling. In order to test whether the n-damo and anammox bacteria co-occur in natural saline environments, the DNA and cDNA samples obtained from the surficial sediments of two saline lakes (with salinity of 32 and 84 g/L, respectively) on the Tibetan Plateau were PCR-amplified with the use of anammox- and n-damo-specific primer sets, followed by clone library construction and phylogenetic analysis. DNA and cDNA-based clones affiliated with n-damo and anammox bacteria were successfully retrieved from the two samples, indicating that these two groups of bacteria can co-occur in natural saline environments with salinity as high as 84 g/L. Our finding has great implications for our understanding of the global carbon and nitrogen cycle in nature.

To understand the influence of human disturbance on the sediment processes along Kalpakkam coast, India, beach and seabed sediments at 200 m, 500 m, and 1 km into the sea were collected monthly for one year and analyzed. Coarser material close to the tidal inlets (river) and manmade structures (sea wall) indicate the effect of these features in altering the grain size distribution from the general trend. The bivariant plots confirm the dominance of deposition under beach environment. The CM diagram (C-one percentile grain diameter, M – median) divulges that the deposition takes place by suspension and rolling of sediments with C<1 mm. Linear discriminate function analysis for sediments at Kalpakkam indicates a shallow marine environment for all the samples collected. On the multigroup multivariant discriminant functions V₁ –V₂ diagram, the bulk of the samples from Kalpakkam to Mahabalipuram fall in the field of beach deposition. These results show that reworked sediments, submerged during the Holocene marine transgression are being deposited on present-day beaches by waves, currents and rivers in the study area. Though a high wave energy environment is prevailing in the study area, dominant northward sediment transport along the Kalpakkam-Mahabalipuram coast is not altered due to human interventions. Beach building activity in front of the sea wall ensures the safety of Indira Gandhi Centre for Atomic Research (IGCAR) from wave actions without causing any significant changes to the coastal environment.

A three dimensional numerical model based on the hydrodynamic module of finite-volume coastal ocean (FVCOM) was established for the Yellow River estuary. The model has been calibrated by observed data and proved to be suitable to reflect the hydrodynamic force in the research area. We employed the model to simulate the tidal shear front off the Yellow River estuary and analyzed the formation, spread and duration of two different types of shear front. To examine the effect of bathymetry evolution on the position of tidal shear front, subaqueous bathymetry of the Yellow River estuary was changed according to the changing patterns obtained from the past few years. Tidal shear front was modeled on both the original and the changed bathymetry. The results show that the position of shear front moved from a shallow to a deep area due to the deposition of bathymetry. The influence of bathymetry evolution on hydrodynamic characteristics including the distribution of salinity and the movement of particles was studied. We found the dispersion areas of low salinity became larger after changing bathymetry and the particles on the surface, middle and bottom layer are able to move further both north and west of Laizhou Bay on the changed bathymetry.

Landslide is one of the major natural disasters which cause extensive loss of life and property. During the last three decades, different researchers have developed different methodologies to prepare landslide susceptibility mapping and hazard assessment in the world. The main goal of this paper is to apply a fuzzy logic approach to landslide susceptibility mapping in the Garuwa sub-basin area, East Nepal. Eight different causative factors are considered: slope angle, slope aspect, slope shape, relative relief, distance from drainage, land use, geology, and distance from active faults. Likelihood ratios are obtained for each class of causative factors by comparison with past landslide occurrences. Then, the likelihood ratios are normalized between zero and one to obtain fuzzy membership values. Next, different fuzzy operators are applied to generate landslide susceptibility maps. Comparison with the landslide inventory map reveals that the fuzzy gamma (γ) operator with a γ-value of 0.70 yields the best prediction accuracy which is then used to produce the final landslide susceptibility zonation map.

Solid particles, particularly urban surface dust in urban environments contain large quantities of pollutants. It is considered that urban surface dust is a major pollution source of urban stormwater runoff. The stormwater runoff washes away urban surface dust and dissolves pollutants adsorbed onto the dust and finally discharges into receiving water bodies. The quality of receiving water bodies can be deteriorated by the dust and pollutants in it. Polluted waters can be purified by wetlands with various physical, chemical, and biologic processes. These processes have been employed to treat pollutants in urban stormwater runoff for many years because purification of treatment wetlands is a natural process and a low-cost method. In this paper, we reviewed the processes involved during pollutants transport in urban environments. Particularly, when the urban stormwater runoff enters into wetlands, their removal mechanisms involving various physical, chemical and biologic processes should been understood. Wetlands can remove heavy metals by absorbing and binding them and make them form a part of sediment. However, heavy metals can be released into water when the conditions changed. This information is important for the use of wetlands for removing of pollutants and reusing stormwater.

Forest land is the essential and important natural resource that provides strong support for human survival and development. Research on forest land changes at the county level about its characteristics, rules, and spatial patterns is, therefore, important for regional resource protection and the sustainable development of the social economy. In this study we selected the GIS and Geoda software package to explore the spatial disparities of forest land changes at the Beijing-Tianjin-Hebei area county level, based on the global and local spatial autocorrelation analyses of exploratory spatial data. The results show that: 1) during 1985–2000, the global spatial autocorrelation of forest land change is significant in the study area. The global Moran’s I value is 0.3122 for the entire time period and indicates significant positive spatial correlation (p<0.05). Moran’s I value of forest land change decreases from 0.3084 at the time stage I to 0.3024 at the time stage II; 2) the spatial clustering characteristics of forest land changes appear on the whole in Beijing-Tianjin-Hebei area. Moran’s I value decreases from the time stage I to time stage II, which means that trend of spatial clustering of forest land change is weakened in the Beijing-Tianjin-Hebei area; 3) the grid map of the local Moran’s I for each county reflects local spatial homogeneity of forest land change, which means that spatial clustering about regions of high value and low value is especially significant. The regions with “High-High” correlation are mainly located in the north hilly area. However, the regions with “Low-Low” correlation were distributed in the middle of the study area. Therefore, protection strategies and concrete measures should be put in place for each regional cluster in the study area.

The invasion of hydrilla in many waterways has caused significant problems resulting in high maintenance costs for eradicating this invasive aquatic weed. Present identification methods employed for detecting hydrilla invasions such as aerial photography and videos are difficult, costly, and time consuming. Remote sensing has been used for assessing wetlands and other aquatic vegetation, but very little information is available for detecting hydrilla invasions in coastal estuaries and other water bodies. The objective of this study is to construct a library of spectral signatures for identifying and classifying hydrilla invasions. Spectral signatures of hydrilla were collected from an experimental tank and field locations in a coastal estuary in the upper Chesapeake Bay. These measurements collected from the experimental tank, resulted in spectral signatures with an average peak surface reflectance in the near-infrared (NIR) region of 16% at a wavelength of 818 nm. However, the spectral measurements, collected in the estuary, resulted in a very different spectral signature with two surface reflectance peaks of 6% at wavelengths of 725 nm and 818 nm. The difference in spectral signatures between sites are a result of the components in the water column in the estuary because of increased turbidity (e.g., nutrients, dissolved matter and suspended matter), and canopy being lower (submerged) in the water column. Spectral signatures of hydrilla observed in the tank and the field had similar characteristics with low reflectance in visible region of the spectrum from 400 to 700 nm, but high in the NIR region from 700 to 900 nm.