A framework for preparation of an early warning system was developed for Maryland, using a GIS database and a collective overlay of maps that highlight highway slopes susceptible to soil slides or slope failures in advance through spatial and statistical analysis. Data for existing soil slope failures was collected from geotechnical reports and field visits. A total of 48 slope failures were recorded and analyzed. Six factors, including event precipitation, geological formation, land cover, slope history, slope angle, and elevation were considered to affect highway soil slope stability. The observed trends indicate that precipitation and poor surface or subsurface drainage conditions are principal factors causing slope failures. 96% of the failed slopes have an open drainage section. A majority of the failed slopes lie in regions with relatively high event precipitation (P>200 mm). 90% of the existing failures are surficial erosion type failures, and only 1 out of the 42 slope failures is deep rotational type failure. More than half of the analyzed slope failures have occurred in regions having low density land cover. 46% of failures are on slopes with slope angles between 20° and 30°. Influx of more data relating to failed slopes should give rise to more trends, and thus the developed slope management system will aid the state highway engineers in prudential budget allocation and prioritizing different remediation projects based on the literature reviewed on the principles, concepts, techniques, and methodology for slope instability evaluation (Leshchinsky et al., 2015).
Various spectral data preprocessing approaches have been used to improve endmember extraction for urban landscape decomposition, yet little is known of their comparative adequacy for impervious surface mapping. This study tested four commonly used spectral data treatment strategies for endmember derivation, including original spectra, image fusion via principal component analysis, spectral normalization, and the minimum noise fraction (MNF) transformation. Land cover endmembers derived using each strategy were used to build a linear spectral mixture analysis (LSMA) model in order to unmix treated image pixels into fraction maps, and an urban imperviousness map was generated by combining the fraction maps representing imperviousness endmembers. A cross-map comparative analysis was then performed to rank the four data treatment types based on such common evaluation indices as the coefficient of determination (R2) and root mean square error (RMSE). A Landsat 7 ETM+ multispectral image covering the metropolitan region of Shanghai, China was used as the primary dataset, and the model results were evaluated using high-resolution color-infrared aerial photographs of roughly the same time period. The test results indicated that, with the highest R2 (0.812) and the lowest RMSE (0.097) among all four preprocessing treatments, the endmembers in the form of MNF-transformed spectra produced the best model output for characterizing urban impervious surfaces. The outcome of this study may provide useful guidance for future impervious surface mapping using medium-resolution remote sensing data.
The scatterometer (SCAT) on-board China’s HY-2A satellite has the capability to provide high resolution wind vector information over the global ocean surface. These wind vector data produced by the HY-2A scatterometer (HY-2A SCAT) are available to the data assimilation system with real-time information of high accuracy. In this paper, two experiments are designed to investigate the impact of HY-2A SCAT data in the three-dimensional variational assimilation system for the Weather Research and Forecast model (WRF 3DVAR). The powerful Typhoon Bolaven, which struck South Korea in August 2012, is selected for this case study. The results clearly demonstrate that HY-2A SCAT data can effectively complement the scarce observations over the ocean surface and improve the prediction of the wind and pressure fields of a typhoon. The case study of Typhoon Bolaven exhibits the significant and positive impact of HY-2A SCAT data on the numerical prediction of the tropical cyclone track.
In this research, we normalized the characteristics of ocean eddies by using satellite observation of the Sea Level Anomaly (SLA) data to determine the most typical shape of ocean eddies. This normalization is based on modified analytic functions with nonlinear optimal fitting. The most typical eddy is the Taylor vortex (~50%), which exhibits a Gaussian-shaped exp(-r2) SLA and a vorticity distribution of (1-r2)exp(-r2) as a function of the normalized radii r. The larger the amplitude of the eddy, the more likely the eddy is to be Gaussian-shaped. Furthermore, approximately 40% of ocean eddies are combinations of two Gaussian eddies with different parameters, but the composition of these types of eddies is more like a quadratic eddy than a Gaussian one. Only a small portion of oceanic eddies are pure quadratic eddies (<10%) with the same vorticity distribution as a Rankine vortex. We concluded that the Taylor vortex is a good approximation of the typical shape of ocean eddies.
The transport timescales were investigated in response to water level variation under different constant flow rates in Dahuofang Reservoir. The concept of water age was applied to quantify the transport timescales. A three-dimensional hydrodynamic model was developed based on the Environmental Fluid Dynamics Code (EFDC). The model was calibrated for water surface elevation and temperature profiles from April 1, 2008 to October 31, 2008. Comparisons of observed and modeled data showed that the model reproduced the water level fluctuation and thermal stratification during warm season and vertical mixing during cold season fairly well. The calibrated model was then applied to investigate the response of water age to water level changes in Dahuofang Reservoir. Model results showed that water age increases from confluence toward dam zone. In the vertical direction, the water age is relatively uniform at upstream and stratifies further downstream, with a larger value at bottom layer than at surface layer. Comparisons demonstrated that water level variation has a significant impact on transport timescales in the reservoir. The impact of water level drawdown on water age is stronger at bottom layer than at surface layer. Under high flow conditions, the water age decreases 0–20 days at surface layer and 15–25 days at bottom layer. Under mean flow conditions, the water age decreases 20–30 days at surface layer and 30–50 days at bottom layer. Furthermore, the impact is minor in the upstream and increases further downstream. The vertical stratification of water age weakens as the water level decreases. This study provides a numerical tool to quantify the transport timescale in Dahuofang Reservoir and supports adaptive management of regional water resources by local authorities.
A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-supervised k-means (SKM) clustering method with deleting the worst cluster (SKMd) band-clustering algorithms. Moreover, four feature combination schemes were designed for hyperspectral image classification by using spectral and textural features. It has been proven that the proposed method using VGLCM outperforms the gray-level co-occurrence matrices (GLCM) method, and the experimental results indicate that the combination of spectral information with volumetric textural features leads to an improved classification performance in hyperspectral imagery.
Incubation experiments have shown that ultraviolet radiation (UVR) has significant influences on marine primary production (MPP). However, existing satellite remote sensing models of MPP only consider the effects of visible light radiation, ignoring the UVR. Additionally, the ocean color satellite data currently used for MPP estimation contain no UV bands. To better understand the mechanism of MPP model development with reference to satellite remote sensing, including UVR’s effects, we first reviewed recent studies of UVR’s effects on phytoplankton and MPP, which highlights the need for improved satellite remote sensing of MPP. Then, based on current MPP models using visible radiation, we discussed the quantitative methods used to implement three key model variables related to UVR: the UVR intensity at the sea surface, the attenuation of UVR in the euphotic layer, and the maximum or optimal photosynthetic rate, considering the effects of UVR. The implementation of these UVR-related variables could be useful in further assessing UVR’s effects on the remote sensing of MPP, and in re-evaluating our existing knowledge of MPP estimation at large spatial scales and long-time scales related to global change.
Organochlorine pesticides (OCPs) found in rivers from the Sichuan Basin to Aba Prefecture profile were analyzed to assess possible health risks to adults and children who use the river as a source of drinking water. OCP concentrations in surface water ranged between 22.29–274.28 ng·L−1. Compared with other published data around the world, OCP levels in this study were moderate. Among all OCPs, hexachlorobenzene (HCB) and hexachlorocyclohexanes (HCHs) were the predominant compounds. Higher concentrations of OCPs were attributed close to the agricultural fields of the Sichuan Basin, current OCPs inputs, and long-range atmospheric transport from abroad. Various spatial patterns of OCPs in the profile might be affected by the usage and physicochemical properties of the pesticides, in addition to the adjacent geographical environment. The health risk assessment indicated that most OCPs had little impact on human health according to the acceptable risk level for carcinogens (10−6) recommended by the US EPA. However, carcinogenic effects caused by heptachlor, Aldrin, HCB, and α-HCH might occur in drinking water. The risk of negative impacts caused by OCPs is much higher for children than for adults.
A 180-day incubation experiment was conducted to investigate the effect of different organic materials on the chemical properties of coastal soil with high salinity and relatively low pH. Four organic materials (three kinds of plant residues: straw, composted straw, and fresh reed; and one kind of poultry manure: chicken manure) were applied at a ratio of 15 g·kg?1 to samples of costal saline soil from the Yellow River Delta of China. The results showed that the soil pH and exchangeable sodium percentage (ESP) decreased, whereas soil cation exchangeable capacity (CEC) and macronutrient concentrations increased, regardless of the type of organic material used. All treatments showed a remarkable increase in soil soluble organic carbon (SOC) during the 180-day incubation. The peak values of SOC in descending order were chicken manure, reed, composted straw, straw, and control soil. At the end of incubation, the highest level of SOC occurred in the straw-amended soil, followed by composted straw, reed, and chicken manure-amended soils. Soil respiration rate and available nitrogen were significantly influenced by the type of material used. Although reed-amended soil had a relatively high SOC and respiration rate, the ESP was reduced the least. Considering the possible risk of heavy metals caused by chicken manure, it is proposed that straw and composted straw are the more efficient materials to use for reclaiming costal saline soil and improving the availability of macronutrients.
This research describes modern phytolith records and distributions from subalpine surface soils in the Dalaoling Forest Reserve, and reveals its implications for local climate conditions with respect to the altitude gradient. Well-preserved phytolith morpho-types, assemblages, and climatic indices were used to study the relationship between local vegetation and climate conditions. The phytolith classification system is mainly based on the characteristics of detailed morpho-types described for anatomical terms, which are divided into seven groups: long cells, short cells, bulliform cells, hair cells, pteridophyte type, broad-leaved type, and gymnosperm type. Phytoliths originating from the Poaceae are composed of Pooideae (rondel and trapeziform), Panicoideae (bilobate, cross, and polylobate), Chloridoideae (short/square saddle), and Bambusoideae (oblong concave saddle). Based on the altitudinal distribution of the phytolith assemblages and the indices of aridity (Iph), climate (Ic), and tree cover density (D/P), five phytolith assemblage zones have revealed the five types of climatic conditions ranging from 1,169 m to 2,005 m in turn: warm-wet, warm-xeric to warm-mesic, warm- xeric to cool-mesic, cool-xeric, and cool-mesic to cool-xeric. The Bambusoideae, Panicoideae, and Chloridoideae are the dominant vegetation at the lower-middle of the mountains, while Pooideae is mainly distributed in the higher mountains. The close relationship between phytolith assembleages and changes of altitude gradient suggest that vegetation distribution patterns and plant ecology in the Dalaoling mountains are controlled by temperature and humidity conditions. Our results highlight the importance of phytolith records as reliable ecoclimatic indicators for vegetation ecology in subtropical regions.
It is well known that urban impervious surface (IS) has a warming effect on urban land surface temperature (LST). However, the influence of an IS’s structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM+ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis (LSMA), and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.
The DF1-1 gas field, located in the western South China Sea, contains a high concentration of CO2, thus there is great concern about the need to reduce the CO2 emissions. Many options have been considered in recent years to dispose of the CO2 separated from the natural gas stream on the Hainan Island. In this study, the feasibility of CO2 storage in the lateral saline aquifer of the DF1-1 gas field is assessed, including aquifer selection and geological assessment, CO2 migration and storage safety, project design, and economic analysis. Six offshore aquifers have been investigated for CO2 geological storage. The lateral aquifer of the DF1-1 gas field has been selected as the best target for CO2 injection and storage because of its proven sealing ability, and the large storage capacity of the combined aquifer and hydrocarbon reservoir geological structure. The separated CO2 will be dehydrated on the Hainan Island and transported by a long-distance subsea pipeline in supercritical or liquid state to the central platform of the DF1-1 gas field for pressure adjustment. The CO2 will then be injected into the lateral aquifer via a subsea well-head through a horizontal well. Reservoir simulations suggest that the injected CO2 will migrate slowly upwards in the aquifer without disturbing the natural gas production. The scoping economic analysis shows that the unit storage cost of the project is approximately US$26‒31/ton CO2 with the subsea pipeline as the main contributor to capital expenditure (CAPEX), and the dehydration system as the main factor of operating expenditure (OPEX).
Wenzhou is a region on the coast of China where storm surges are frequent and serious. Starting with society, economy, land utilization, and anti-disaster capability, the vulnerability of each county in the coastal region of Wenzhou was evaluated. The counties were then divided into mild, moderate, heavy, and extremely heavy fragile areas by choosing 15 factors to establish an evaluation index system, using principal component analysis to set the weight of each factor. The results show that all of the counties fit into the categories of heavy and extremely heavy fragile areas except for Pingyang county, which is mild. There is no significant difference in storm surge vulnerability among all counties in the Wenzhou coastal region, which is highly associated with the general balance of socioeconomic development in the Zhejiang coastal region and the orientation of government policies. This research provides a method for evaluating vulnerability to storm surge. Evaluation results can provide the basis for responses to storm surge, contributing to disaster prevention and mitigation planning, and regional sustainable development planning.
Based on rural household survey data from Taibus Banner, in the Inner Mongolia Autonomous Region, China, this study separately categorizes agricultural land use intensity into labor intensity, capital intensity, the intensity of labor-saving inputs, and the intensity of yield-increasing inputs, and then analyzes their determinants at the household level. The findings reveal that within the study area: (1) labor intensity is higher and capital intensity is lower than in the major grain-producing and economically developed areas of eastern and central China; (2) the most widely planted crops are those with the lowest labor intensity (oats) and capital intensity (benne); (3) there are marked differences in agricultural land use intensity among households; a major factor affecting land use decision-making is the reduced need for labor intensity for those households with high opportunity costs, such as those with income earned from non-farming activities which alleviates financial constraints and allows for increased capital intensity. As a result, these households invest more in labor-saving inputs; (4) households with a larger number of workers will allocate adequate time to manage their land and thus they will not necessarily invest more in labor-saving inputs. Those households with more land to manage tend to adopt an extensive cultivation strategy. Total income has a positive impact on capital intensity and a negative impact on labor intensity. Households that derive a higher proportion of their total income through farming are more reliant upon agriculture, which necessitates significant labor and yield-increasing inputs. Finally, the authors contend that policy makers should clearly recognize the impacts of non-farming employment on agricultural land use intensity. In order to ensure long-term food security and sustainable agricultural development in China, income streams from both farming and non-farming employment should be balanced.
An improved Carnegie Ames Stanford Approach (CASA) model based on two kinds of remote sensing (RS) data, Landsat Enhanced Thematic Mapper Plus (ETM+) and Moderate Resolution Imaging Spectroradiometer (MODIS), and climate variables were applied to estimate the Net Primary Productivity (NPP) of Xuzhou in June of each year from 2001 to 2010. The NPP of the study area decreased as the spatial scale increased. The average NPP of terrestrial vegetation in Xuzhou showed a decreasing trend in recent years, likely due to changes in climate and environment. The study area was divided into four sub-regions, designated as highest, moderately high, moderately low, and lowest in NPP. The area designated as the lowest sub-region in NPP increased with expanding scale, indicating that the NPP distribution varied with different spatial scales. The NPP of different vegetation types was also significantly influenced by scale. In particular, the NPP of urban woodland produced lower estimates because of mixed pixels. Similar trends in NPP were observed with different RS data. In addition, expansion of residential areas and reduction of vegetated areas were the major reasons for NPP change. Land cover changes in urban areas reduced NPP, which could chiefly be attributed to human-induced disturbance.
A substantial number of the coal mines in China are in the geological condition of thick alluvium layer. Under these circumstances, it does not make sense to predict ground surface subsidence and other deformations by using conventional prediction models. This paper presents a novel ground surface subsidence prediction model for sub-critical mining in the geological condition of thick alluvium layer. The geological composition and mechanical properties of thick alluvium is regarded as a random medium, as are the uniformly distributed loads on rock mass; however, the overburden of the rock mass in the bending zone is looked upon as a hard stratum controlling the ground surface subsidence. The different subsidence and displacement mechanisms for the rock mass and the thick alluvium layer are respectively considered and described in this model, which indicates satisfactory performances in a practical prediction case.
In this study, the evidential belief functions (EBFs) were applied for mapping tungsten polymetallic potential in the Nanling belt, South China. Seven evidential layers (e.g., geological, geochemical, and geophysical) related to tungsten polymetallic deposits were extracted from a multi-source geospatial database. The relationships between evidential layers and the target deposits were quantified using EBFs model. Four EBF maps (belief map, disbelief map, uncertainty map, and plausibility map) are generated by integrating seven evidential layers which provide meaningful interpretations for tungsten polymetallic potential. On the final predictive map, the study area was divided into three target zones of high potential, moderate potential, and low potential areas, among which high potential and moderate potential areas accounted for 17.8% of the total area, containing 81% of the total deposits. To evaluate the success rate accuracy, the receiver operating characteristic (ROC) curves and the area under the curves (AUC) for the belief map were calculated. The area under the curve is 0.81 which indicates that the capability for correctly classifying the areas with existing mineral deposits is satisfactory. The results of this study indicate that the EBFs were effectively used for mapping mineral potential and for managing uncertainties associated with evidential layers.
Coupled with intricate regional interactions, the provincial disparity of energy-resource endowment and other economic conditions in China have created spatially complex energy consumption patterns that require analyses beyond the traditional ones. To distill the spatial effect out of the resource and economic factors on China’s energy consumption, this study recast the traditional econometric model in a spatial context. Several analytic steps were taken to reveal different aspects of the issue. Per capita energy consumption (AVEC) at the provincial level was first mapped to reveal spatial clusters of high energy consumption being located in either well developed or energy resourceful regions. This visual spatial autocorrelation pattern of AVEC was quantitatively tested to confirm its existence among Chinese provinces. A Moran scatterplot was employed to further display a relatively centralized trend occurring in those provinces that had parallel AVEC, revealing a spatial structure with attraction among high-high or low-low regions and repellency among high-low or low-high regions. By a comparison between the ordinary least square (OLS) model and its spatial econometric counterparts, a spatial error model (SEM) was selected to analyze the impact of major economic determinants on AVEC. While the analytic results revealed a significant positive correlation between AVEC and economic development, other determinants showed some intricate influential patterns. The provinces endowed with rich energy reserves were inclined to consume much more energy than those otherwise, whereas changing the economic structure by increasing the proportion of secondary and tertiary industries also tended to consume more energy. Both situations seem to underpin the fact that these provinces were largely trapped in the economies that were supported by technologies of low energy efficiency during the period, while other parts of the country were rapidly modernized by adopting advanced technologies and more efficient industries. On the other hand, institutional change (i.e., marketization) and innovation (i.e., technological progress) exerted positive impacts on AVEC improvement, as always expected in this and other studies. Finally, the model comparison indicated that SEM was capable of separating spatial effect from the error term of OLS, so as to improve goodness-of-fit and the significance level of individual determinants.