Response of NDVI dynamics to precipitation in the Beijing–Tianjin sandstorm source region

This article analysed the spatio-temporal changes in vegetation cover in the Beijing–Tianjin sandstorm source region in China and related these changes to vegetation types based on the Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data set from 1982 to 2006. The annual maximum NDVI and peak time were identified. The different periods (1–12 months) of accumulated precipitation before the peak time were then calculated at the grid scale for each year. On this basis, the NDVI–rainfall relationship and the temporal responses in this area were studied by calculating the correlation coefficient between the annual maximum NDVI and different periods (1–12 months) of accumulated precipitation before the occurrence of the annual maximum NDVI for each pixel. The results show an upward trend in regional vegetation, a significant recovery efficiency for grassland, and the evident degradation of cropland. Peak plant growth is significantly related to precipitation and is strongly positively correlated with precipitation in the previous period (1 month) regardless of vegetation type. The regions showing the strongest correlations between peak plant growth and 1 month cumulative rainfall are the western desert grassland, grassland to forest in the transitional hill regions, the mountains of Yanshan, and the Greater Hinggan Mountains.     

Evaluation of the VI–T s method for estimating the land surface moisture index and air temperature using ASTER and MODIS data in the North China Plain

Two conditions are required when a remotely sensed vegetation index–land surface temperature (VI–T _s) diagram is used to estimate the land surface moisture index (LSMI) and air temperature (T _a). First, a suitable sampling window size is required to define an ideal VI–T _s diagram. Second, T _a must be homogeneous across the sampling window. In this study, the Shannon diversity index (SDI) and the semivariogram method were used to evaluate the VI–T _s diagram for estimating LSMI and T _a from Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and MODerate-resolution Imaging Spectroradiometer (MODIS) datasets. The results show that T _a is homogeneous across a sampling window with a width of several tens of kilometres (46.0–83.6 km) based on the semivariogram method and spatial autocorrelation analysis of the T _a from 83 meteorological stations in the North China Plain (NCP) in 2003. When the SDIs of VI and T _s are respectively larger than 77% and 63% of their maximums within predetermined sampling windows, LSMI estimations by ASTER and T _a estimations by ASTER and MODIS are reliable.     

Predictions of the Al-rich region of the Al–Co–Ni–Y system based upon first-principles and experimental data

A thermodynamic database has been produced for the Al–Co–Ni–Y quaternary system, with an emphasis on the Al-rich region of the Al–Ni–Y ternary system. The database was created using the CALPHAD method, combining existing binary systems with relevant experimental and first-principles information for selected Al–Ni–Y and Co-containing compounds. The thermodynamic database was used to produce equilibrium and non-equilibrium Scheil simulations to determine the phases present in Al–Co–Ni–Y alloys. The values for the Scheil simulation show good agreement, when compared with experimentally determined phase fractions of intermetallic particles dispersed in an Al matrix for three Al-rich quaternary alloys.     

Performance improvement for source mobility in named data networking based on global–local FIB updates

The mobile devices have become the norm, rather than an exception for people’s daily life, and these devices possess strong ability (e.g., increasingly large storage) to serve as content sources in future information-centric networks, e.g., named data networking (NDN). The efficient discovery of contents provided by mobile devices is a challenging task. Most of existing studies adopted ID-Locator split architecture to handle the problems raised by source mobility in NDN, e.g., the content source is suddenly disconnected from the network when providing on-going services. However, these solutions require very high control overhead to maintain up-to-date location information of sources in an ID-Locator mapping system. Software defined networking (SDN) is a promising tool to make cross-layer decisions based on its logically centralized controller, and thus can facilitate the implementation of forwarding strategies in NDN according to application requirements. To this end, this paper proposes a new packet forwarding algorithm under SDN paradigm that is able to update the forwarding information base (FIB) of NDN node considering both the mobility pattern of mobile sources and network states. In particular, the algorithm leverages the SDN controller to perform the tradeoff between global FIB updates on all NDN nodes and local FIB updates on NDN nodes that are previously connected by mobile sources to lower the control overhead. A discrete-event simulator based on NS3 simulation framework is developed to validate the effectiveness and feasibility of the proposed algorithm. In addition, the performance of the algorithm is compared with that of existing solutions based on ID-Locator split architecture. The results show that the proposed packet forwarding algorithm has a lower request-to-response latency and higher successful content request ratio with reduced control overhead under different working conditions.     

Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation

Most of the reported prognostic techniques use a small number of condition indicators and/or use a thresholding strategies in order to predict the remaining useful life (RUL). In this paper, we propose a reliability-based prognostic methodology that uses condition monitoring (CM) data which can deal with any number of condition indicators, without selecting the most significant ones, as many methods propose. Moreover, it does not depend on any thresholding strategies provided by the maintenance experts to separate normal and abnormal values of condition indicators. The proposed prognostic methodology uses both the age and CM data as inputs to estimate the RUL. The key idea behind this methodology is that, it uses Kaplan–Meier as a time-driven estimation technique, and logical analysis of data as an event-driven diagnostic technique to reflect the effect of the operating conditions on the age of the monitored equipment. The performance of the estimated RUL is measured in terms of the difference between the predicted and the actual RUL of the monitored equipment. A comparison between the proposed methodology and one of the common RUL prediction technique; Cox proportional hazard model, is given in this paper. A common dataset in the field of prognostics is employed to evaluate the proposed methodology.     

A modified super-efficiency measure based on simultaneous input–output projection in data envelopment analysis

Super-efficiency data envelopment analysis (SE-DEA) models have been developed and applied in many situations. However, under the condition of variable returns to scale (VRS), infeasibility of the SE-DEA model may occur and restrict its application. A modified SE-DEA measure based on simultaneous input–output projection is proposed as a way to systematically characterize the super-efficiency in both inputs and outputs. The modified measure overcomes the infeasibility problem while providing ease of computation and interpretation. The practicability of the proposed measure in real applications and its comparison to other super-efficiency measures are illustrated empirically using an example.     

ITEA—interactive trajectories and events analysis: exploring sequences of spatio-temporal events in movement data

Widespread use of GPS and similar technologies makes it possible to collect extensive amounts of trajectory data. These data sets are essential for reasonable decision making in various application domains. Additional information, such as events taking place along a trajectory, makes data analysis challenging, due to data size and complexity. We present an integrated solution for interactive visual analysis and exploration of events along trajectories data. Our approach supports analysis of event sequences at three different levels of abstraction, namely spatial, temporal, and events themselves. Customized views as well as standard views are combined to form a coordinated multiple views system. In addition to trajectories and events, we include on-the-fly derived data in the analysis. We evaluate our integrated solution using the IEEE VAST 2015 Challenge data set. A successful detection and characterization of malicious activity indicate the usefulness and efficiency of the presented approach.     

An integrated soft and hard classification approach for evaluating urban expansion from multisource remote sensing data: a case study of the Beijing–Tianjin–Tangshan metropolitan region,China

Integrating soft and hard classification to monitor urban expansion can effectively provide comprehensive urban growth information to urban planners. In this study, both the impervious surface coverage (as a soft classification result) and land cover (as a hard classification result) in the Beijing–Tianjin–Tangshan metropolitan region (BTTMR), China, were extracted from multisource remote sensing data from 1990 to 2015. Then, we evaluated urban expansion based on centre migration, standard deviation ellipse, and spatial autocorrelation metrics. Furthermore, the differences between the soft and hard classification results were analysed at the landscape scale. The results showed that (1) the impervious surface area increased considerably over the past 25 years. Notably, the areas of urban built-up land and industrial production land increased rapidly, while those of ecological land and agricultural production land seriously decreased. (2) The distribution of impervious surfaces was closely related to the regional economic development plan of ‘One Axis, Two Wing, and Multi-Node’ in the BTTMR. (3) The contributions of different land use types to impervious surface growth ranked from high to low as follows: urban built-up land, rural residential land, industrial production land, agricultural production land, and ecological land. (4) The landscape metrics varied considerably based on the hard and soft classification results and were sensitive to different factors.     

Time-series analysis of NDVI from AVHRR data over the Hindu Kush–Himalayan region for the period 1982–2006

The Hindu Kush–Himalayan (HKH) region with its surrounding mountains in central Asia is a region that has been warming at an alarming rate and is sensitive to climate change due to its heterogeneous terrain and high altitude. In a region where research is limited due to the paucity of field-based biophysical observations, analysis of remotely sensed data such as the normalized difference vegetation index (NDVI) can provide invaluable information on spatio-temporal patterns in linkages among land use, climate and vegetative phenological cycles, and trends in vegetative cover. In this study, NDVI data with 8 km spatial resolution for each 15 day composite period from 1982 to 2006 were analysed using a seasonal trend analysis technique, where the first step determines the annual mean and seasonal NDVI patterns across the HKH region. The second step analyses the non-parametric trends in magnitude and timing of the annual mean and seasonal NDVI cycle. The seasonal vegetation cycles were compared for the first and last ten years of the time series and were also analysed across areas undergoing significant change. Results indicated an overall greening trend in NDVI magnitude in most areas, particularly over open shrubland, grassland and cropland. Trends in the annual seasonal timing of NDVI indicated an earlier green-up for most parts of this region. Results also confirmed deforestation trends observed in a few states in northeastern India and Myanmar (Shan state) within the HKH region.     

Mean seasonal cycle and evolution of the sea surface temperature from satellite and in situ data in the English Channel for the period 1986–2006

A night-time series of sea surface temperature (SST) of the advanced very high-resolution radiometer (AVHRR) sensors provided by the AVHRR/Pathfinder was analysed over the period 1986–2006 in the English Channel. The studied area is characterized by a strong influence of the bathymetry on the mixing of the water column, mostly through the action of the tide and waves, leading to regional patterns in the SST fields. Another specific aspect of the area is the relatively large number of in situ measurements available from coastal stations. The remotely sensed SST data with fine spatial resolution and high-frequency measurements made at coastal stations have been analysed using a common model. The long-term evolution of SST has been defined in this study through a linear trend while the seasonal evolution has been described through two harmonic functions. The daily satellite SST fields have been estimated over the period 1986–2006 by applying the kriging method to the anomalies calculated from the model. These interpolated temperatures were compared with in situ data, including many coastal stations unreachable at the sensor resolution. To use those coastal stations for comparison and to complement the satellite-derived data set, we defined transfer functions established from fine analysis of the in situ gradients along cross shore transects. The study showed the existence of a long-term warming and that this trend was not homogeneous in the area studied. The central part of the English Channel and the Western part of Brittany show an increase in temperature of about 0.6°C and the Northern part of the Irish and Baltic Sea, included in the studied area, show a maximum increase in the temperature of 1.6°C over the period 1986–2006.     

Sensitivity analysis and optimization of vehicle–bridge systems based on combined PEM–PIM strategy

This paper presents a new optimization method for coupled vehicle–bridge systems subjected to uneven road surface excitation. The vehicle system is simplified as a multiple rigid-body model and the single-span bridge is modeled as a simply supported Bernoulli–Euler beam. The pseudo-excitation method transforms the random surface roughness into the superposition of a series of deterministic pseudo-harmonic excitations, which enables convenient and accurate computation of first and second order sensitivity information. The precise integration method is used to compute the vertical random vibrations for both the vehicle and the bridge. The sensitivities are used to find the optimal solution, with vehicle ride comfort taken as the objective function. Optimization efficiency and computational accuracy are demonstrated numerically.     

Theoretical study of surface interaction stresses considering one-dimensional material distributions in the in-plane direction based on the Lennard–Jones potential

In this work, the interaction stresses (i.e., pressures and shear stresses) between a half-space comprising a uniform material and a half-space comprising one-dimensional material distributions in the in-plane direction were theoretically derived. The interaction stress was derived from the Lennard–Jones potential as a vector for the (0, 0, 1) surface using two different material distribution patterns. The first pattern was a periodic distribution of materials (Pattern 1) and the second was a distribution of two materials with a single interface (Pattern 2). The interaction stresses for Pattern 1 were derived based on a Fourier series, while those for Pattern 2 were derived as elementary functions. The pressures possessed non-fluctuation terms and fluctuation terms, while the shear stresses possessed fluctuation terms only. The basic characteristics of these interaction stresses for parallel planes were quantitatively clarified by presenting the distributions and vector diagrams of the interaction stresses.

     

Vegetation cover changes and their relationship to climate variation in the source region of the Yellow River,China, 1990–2000

The change history of vegetation cover and its relations to growing season precipitation (GSP) and average growing season temperature (AGST) in the source region of the Yellow River (SRYR) during 1990–2000 was retrieved based on the 1 km Advanced Very High‐Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data and meteorological records. The results show an overall warming and drying trend of the climate and a common degradation tendency of the ecosystem, with a greening trend in higher rugged regions. The pixel‐by‐pixel correlations between NDVI and climate factors indicate that a decrease in GSP mainly affects ecosystems with low precipitation and worse vegetation condition, and superimposes on the effects of increasing AGST which further deteriorate the climate background of these ecosystems. However, the positive correlations between AGST and NDVI in some higher/rugged regions suggest that the raising temperature can ameliorate vegetation growth conditions in these areas. Comparison and combination of the results of three change detection algorithms, i.e. post‐classification comparison (PCC), principal components analysis (PCA) and a newly developed multi‐temporal image difference (MTID) method, show that the integration of different methods can give a more comprehensive understanding of vegetation changes than any single method.     

Spatial–temporal changes in vegetation coverage in the global coastal zone based on GIMMS NDVI3g data

ABSTRACT

In this paper, we used the Global Inventory Modelling and Mapping Studies (GIMMS) third-generation Normalized Difference Vegetation Index (NDVI) (GIMMS NDVI3g) dataset. Based on GIMMS NDVI3g data over the global coastal zone from 1982 to 2014, the spatial–temporal characteristics of vegetation coverage were analysed by plotting the spatial pattern and monthly calendar of NDVI; furthermore, historical trends and future evolutions of vegetation coverage change at the pixel scale were studied by performing the Mann-Kendall trend test and calculating the trend slope (β) and Hurst index (H) of NDVI. The main findings are as follows: 1) Vegetation density exhibits dramatic differences in the global coastal zone. Specifically, desert belts mostly have perennial non-vegetation or low vegetation coverage, and tundra belts principally have moderate or high vegetation coverage; additionally, forest belts mainly have dense vegetation coverage. 2) In the global coastal zone, intra-annual variations in vegetation coverage show a ‘∩’-shaped curve with an obvious peak from June to September (maximum in July or August), while inter-annual variations show a fluctuating but generally slowly increasing trend over the entire study period; accordingly, variations in different subregions show significant differences. 3) At monthly, seasonal and annual scales, the overall vegetation coverage increases in the global coastal zone, while there are relatively few areas with decreasing vegetation coverage; furthermore, change trends of vegetation coverage in most areas will demonstrate relatively strong positive persistence in the future. 4) The increasing trend in high-latitude coastal tundra is extremely significant in the growing season because vegetation in the tundra belts is highly sensitive to climate change. 5) Areas with a decreasing trend of vegetation coverage exhibit spatial patterns of aggregation in the ‘circum urban agglomeration’ and ‘nearby desert belt’ regions, that is, the decreasing trend of vegetation coverage is relatively high in coastal urban agglomeration areas and desert belt peripheries. This paper is expected to provide knowledge to support vegetation conservation, ecosystem management, integrated coastal zone management and climate change adaptation in coastal areas.     

Analysis of collocated AIRS and MODIS data: a global investigation of correlations between clouds and atmosphere in 2004–2012

We used collocated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) to investigate correlations between cloud parameters and atmospheric stability. We focus on low clouds and specifically investigate the cloud parameters cloud cover and cloud optical thickness from MODIS. The selected atmospheric parameters from AIRS are maximum relative humidity (MRH), lower tropospheric stability (LTS), and water vapour gradient (QTS). The correlations were tested for temporal and regional variation on a global scale and over a time frame of 10 years. Cloud cover and MRH show weak correlations and strong variations on both the temporal and spatial scales. However, cloud cover and lower tropospheric stability show a high correlation in areas with low maritime clouds. The correlation is relatively stable, but slightly increased for the years 2009–2012. Correlations between cloud cover and QTS show a similar behaviour, but slightly stronger variations on the spatial and temporal scales, with better correlations in the East Pacific and from 2004 to 2012. The correlations with cloud optical thickness are weaker in all three cases. A more detailed analysis of the Southeast Pacific shows the influence of El Niño Southern Oscillation (ENSO) on most parameters, but a relatively stable behaviour for the connection of cloud fraction and LTS. Based on the analysis, we suggest that relative humidity is an insufficient approach to link atmospheric properties and low cloud cover. However, we find good correlations with respect to LTS and QTS. LTS in particular indicates low temporal fluctuations, even in the case of influence by ENSO.     

Analysis on the variations of atmospheric CO2 concentrations along the urban–rural gradients of Chinese cities based on the OCO-2 XCO2 data

Anthropogenic CO₂ emissions contribute the most to the growth of atmospheric CO₂ concentrations. These emissions are largely concentrated in urban areas where human activities are intense. Studies have been conducted to explore the urban and rural difference in CO₂ concentrations based on ground-based measurements. The launch of NASA’s Orbiting Carbon Observatory-2 (OCO-2) satellite provides a new opportunity to monitor CO₂ concentrations and their spatial and temporal variations at city scale. The objective of this study is to analyse the spatial and temporal distributions of CO₂ concentrations along the urban–rural gradients of Chinese cities, using the column averaged CO₂ dry air mole fraction (XCO₂) data derived from OCO-2. We used both conceptual and physical urban–rural gradients to analyse variations in CO₂ concentrations over space. The results show that the urban and rural difference in CO₂ concentrations of these cities can be monitored. And, the seasonal variations of CO₂ concentrations in these cities can also be detected using the XCO₂ data. Moreover, the variations in CO₂ concentrations along the urban–rural gradients have four main types with significant enhancements of CO₂ concentrations were observed in urban areas, urban–rural transitional areas, rural areas, and without regular patterns, respectively. The results are generally different from the common assumption that CO₂ concentrations peak in central urban areas and decline in rural areas. In conclusion, the XCO₂ data can be used to analyse the spatial-temporal variations of CO₂ concentrations along the urban–rural gradients of Chinese cities, and the results have important policy implications for mitigating CO₂ emissions.     

Numerical analysis on electroosmotic flows in a microchannel with rectangle-waved surface roughness using the Poisson–Nernst–Planck model

The present study has numerically investigated two-dimensional electroosmotic flows in a microchannel with dielectric walls of rectangle-waved surface roughness to understand the roughness effect. For the study, numerical simulations are performed by employing the Nernst–Planck equation for the ionic species and the Poisson equation for the electric potential, together with the traditional Navier–Stokes equation. Results show that the steady electroosmotic flow and ionic-species transport in a microscale channel are well predicted by the Poisson–Nernst–Planck model and depend significantly on the shape of surface roughness such as the amplitude and periodic length of wall wave. It is found that the fluid flows along the surface of waved wall without involving any flow separation because of the very strong normal component of EDL (electric double layer) electric field. The flow rate decreases exponentially with the amplitude of wall wave, whereas it increases linearly with the periodic length. It is mainly due to the fact that the external electric-potential distribution plays a crucial role in driving the electroosmotic flow through a microscale channel with surface roughness. Finally, the present results using the Poisson–Nernst–Planck model are compared with those using the traditional Poisson–Boltzmann model which may be valid in these scales.     

On the formulation and implementation of geometric and manufacturing constraints in node–based shape optimization

We introduce a novel method to handle geometrical and manufacturing constraints in parameter–free shape optimization. Therefore the design node coordinates are split in two sets where one set is declared as new design variables and the other set is coupled to the new design variables such that the geometrical constraint is fulfilled. Thereby no additional equations are appended to the optimization problem. In contrast the implementation of a demolding constraint is presented by formulating inequality constraints which indeed have to be attached to the optimization problem. In the context of a sensitivity–based shape optimization approach all manufacturing constraints have to be formulated in terms of the finite element node coordinates such that first order gradients with respect to the design node coordinates can be derived.