Trend surface analysis of forest landscape pattern in Guandishan forest region of Shanxi,China

Landscape pattern is a widely used concept for the demonstration of landscape characteristic features. The integral spatial distribution trend of landscape elements is interested point in the landscape ecological research, especially in those of complex secondary forest regions with confusing mosaics of land cover. Trend surface analysis which used in community and population ecological researches was introduced to reveal the landscape pattern. A reasonable and reliable approach for application of trend surface analysis was provided in detail. As key steps of the approach, uniform grid point sampling method was developed. The efforts were also concentrated at an example of Guandishan forested landscape. Some basic rules of spatial distribution of landscape elements were exclaimed. These will be benefit to the further study in the area to enhance the forest sustainable management and landscape planning.

Remote sensing composite information's trend surface analysis of Nansha Islands coral islets and reefs' top

Based on the remote sensing information feature of Nansha coral islets and reefs that controlled by the Nansha Islands local area's goological structure and growth law, by means of mathematical model and PC, the Nansha Islands coral islets and reefs' top geological data' spatial distribution and local change trend are simulated by using the trend surface system on the remote sensing composite information, and an scientific interpretation and local comparison of Nansha coral islands and islets' spatial distribution feature are made.

Human settlement's social network analysis based on spatial trend surface model:a case study of Chongqing Municipality

Integrated with GIS and remote sensing(RS) technology,a systematic analysis and its methodology for human-settlements social environment has been introduced.This methodology has been called spatial trend field model(STFM).STFM's application history in the field of human-settlements social environment has been discussed at first.Then,some index data models have been created through STFM,which include population density trend field,human activity strength trend field,city-town spatial density trend field,urbanization ratio trend field,road density trend field,GDP spatial density trend field and PER-GDP spatial density trend field.With all above-mentioned indexes as input data,through Iterative Self-Organizing Data Analysis Techniques Algorithm(ISODATA),this paper makes a verification study of Chongqing municipality.The result of the case study confirms that STFM methodology is credible and has high efficiency for regional human-settlements study.

Forward a spatio-temporal trend surface for long-term groundmeasured albedo upscaling over heterogeneous land surface

Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements.Conventional ground-based measurements cannot provide sufficient information on the characteristics of surface albedo at the scale of coarse pixels over heterogeneous land surfaces.One method of overcoming this problem is to introduce high-resolution albedo imagery as ancillary information for upscaling.However,due to the low frequency of updating of high-resolution albedo maps,upscaling time series of ground-based albedo measurements is difficult.This paper proposes a method that is based on the idea of conceptual universal scaling methodology for establishing a spatiotemporal trend surface using very few high-resolution images and time series of ground-based measurements for spatial-temporal upscaling of albedo.The construction of the spatiotemporal trend surface incorporates the spatial information provided by auxiliary remote sensing images and the temporal information provided by long time series of ground observations.This approach was illustrated by upscaling ground-based fine-scale albedo measurements to a coarse scale over the core study area in HiWATER.The results indicate that this method can characterize the spatiotemporal variations in surface albedo well,and the overall correlation coefficient was 0.702 during the study period.

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model lntercomparison Project Phase 5 （CMIP5） results, multidecadal variations and trends in annual mean surface air temperature anomalies （SATa） at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways （RCPs） are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere （NH） and of the ocean in the southern hemisphere （SH） are similar to those of the global mean, showing an increase during the 1900-1944 and 1971-2000 periods, and flattening or even cooling during the 1945-1970 and 2001-2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945-1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period （2001-2013）, the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006-2099 period. The selected multi-model ensemble （MME） projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 （RCP8.5） are 0.17 （0.29） ℃, 0.22 （0.36） ℃, and 0.11 （0.23） ℃-decade-1 in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.

Reconstruction of Ore-controlling Structures Resulting from Magmatic Intrusion into the Tongling Ore Cluster Area during the Yanshanian Epoch

The Tongling ore cluster area experienced intensive compression and associated shearing during the Indosinian-Yanshanian Epoch, which formed a trunk ore-controlling fold and fault system in the caprock. The magmatic intrusion in the Yanshanian Epoch induced a multi-stage unmixing of poly-phase fluids, resulting in mineralization characterized by multi-layer, wide-range, and multiform styles. The magmatic intrusion in the Tongling area not only supplied the essential ore-forming materials, but also reconstructed the ore-controlling structures according to a trend surface simulation of the following five strata boundaries： Silurian-Devonian, Devonian-Carboniferous, Carboniferous- Permian, Middle Permian-Upper Permian and Permian -Triassic. The result of this simulation shows that there exists a significant difference between the strata in the upper part and those in the lower. The lower trend surfaces are antiform whereas the upper trend surfaces are synform. In addition, superposing of the trend surfaces of adjacent bed boundaries （such as, Silurian-Devonian boundary superposed upon Devonian-Carboniferous boundary） shows that the lower trend surface always pierces the one above. Moreover, the position and orientation of the pierced parts of the different superposed trend surfaces are similar and show E-W-trending zonal distribution in accordance with the distribution of the regional E-W-trending magmatic-metallogenic belt. Based on comprehensive analysis of the mechanical properties of the strata, structural deformation mechanisms, and field phenomena, it seems that the special characteristics of the stratal trend surface resulted from jacking due to magmatic intrusion into the caprock previously controlled by an E-W-trending basement fault. Therefore, it is deduced that the major ore-controlling structures, which formed during regional horizontal compression, were reconstructed by the vertical jacking function of ore-forming magmas during the Yanshanian Epoch. During the ore-forming process, the local vertical jacking of magmas, coupled with the regional horizontal compression, optimized an extensive environment in the fluid- conduit network and accelerated the unmixing of poly-phase fluids following magmatic emplacement. Jacking also strengthened the vertical and lateral fluid-guiding structures, supplying more suitable physical conditions for multi-layer emplacement and wide-ranging transport of poly-phase fluids.

Integrating RS technology into a GIS-based earthquake prevention and disaster reduction system for earthquake damage evaluation

This paper presents a method to integrate remote sensing （RS） data processing, generation of isoseismal lines and human-computer interaction modules into an improved GIS-based disaster reduction system. Using the RS data processing module, a statistical sample gray value and the RS-intensity at each field survey point in the region are calculated from the probabilistic relationship between the RS-variable and earthquake intensity, and stored in the GIS-based system database. Then, isoseismal lines are generated by a trend surface model from RS-intensity. They are further improved via modification of the isoseismal lines based on the empirical attenuation relationship calculated by using the RS-variable in the human-computer interaction module. The field survey shows that the proposed method gives a good generation of isoseismic lines. As a result, the accuracy of the damage and loss evaluation and the efficiency of the emergency decision making capability are improved.

Study on the detection of abnormal sounding data based on LS-SVM

A new method of detecting abnormal sounding data based on LS-SVM is presented.The theorem proves that the trend surface filter is the especial result of LS-SVM.In order to depict the relationship of trend surface filter and LS-SVM,a contrast is given.The example shows that abnormal sounding data could be detected effectively by LS-SVM when the training samples and kernel function are reasonable.

Theoretical Study on Stochastic Modeling of Combined Gravity-Magnetic-Electric-Seismic Inversion and Its Application

As gravity field, magnetic field, electric field and seismic wave field are all physical fields, their object function, reverse function and compound function are certainly infinite continuously differentiable functions which can be expanded into Taylor (Fourier) series within domain of definition and be further reduced into solving stochastic distribution function of series and statistic inference of optimal approximation. This is the basis of combined gravity-magnetic-electric-seismic inversion of stochastic modeling. It is an uncertainty modeling technology of combining gravity-magnetic-electric-seismic inversion built on the basis of separation of field and source gravity-magnetic difference-value (D-value) trend surface, taking distribution-independent fault system as its unit, depths of seismic and electric interfaces of interests as its corresponding bivariate compound reverse function of gravity-magnetic anomalies and using high order polynomial (high order trigonometric function) approximating to its series distribution. The difference from current dominant inversion techniques is that, first, it does not respectively create gravity-seismic, magnetic-seismic deterministic inversion model from theoretical model, but combines gravity-magnetic-electric-seismic stochastic inversion model from stochastic model; second, after the concept of equivalent geological body being introduced, using feature of independent variable of gravity-magnetic field functions, taking density and susceptibility related to gravity-magnetic function as default parameters of model, the deterministic model is established owing to better solution to the contradiction of difficulty in identifying strata and less test analytical data for density and susceptibility in newly explored area; third, under assumption of independent parent distribution, a real modeling by strata, the problem of difficult plane closure arising in profile modeling is avoided. This technology has richer and more detailed fault and strata information than sparse pattern seismic data in newly explored area, successfully inverses and plots structural map of Indosinian discontinuity in Hefei basin with combined gravity-magnetic-electric-seismic inversion. With development of high precision gravity-magnetic and overall geophysical technology, it is certain for introducing new methods of stochastic modeling and computational intelligence and promoting the development of combined gravity-magnetic-electric-seismic inversion to open a new substantial path.

Support vector regression constraint to remove fault shadows-A case study of an oil field in the pearl river estuary basin,South China Sea

The main reservoirs in different fields in the YP oil region of the eastern Pearl River Estuary Basin are all fault-locked reservoirs.A large amount of seismic data in this area has fault-influenced distortion imaging zones,which poses a challenge to the tectonic evaluation of the area.Traditional solutions to fault shadows generally use reacquisition of multi-directional seismic data or targeted processing for fault imaging,which involves the acquisition of high cost and long processing cycle.In this paper,we propose to quantitatively depict the shadow zone range of faults using 3D stratigraphic dip attributes,and then combine it with the lateral distribution of marine stratigraphy features in the YP oil region,we introduced a support vector regression algorithm to calculate a high-precision nonlinear tectonic trend surface in the area.Under the constraint of this trend surface,we completed the prediction of distortion area structure of the fault shadow zone.The theoretical model test calculations and the production application of an oil field in the YP oil region show that the method has a great potential for application.

Geo-Spatial Mapping of the Eastern Bushveld Rustenburg Layered Suite (RLS) in South Africa

This paper focused on the results of the Trend Surface Analysis (TSA) of the Rustenburg Layered Suite (RLS) within the three major limbs of the Bushveld Complex. This second part focused on the Eastern Bushveld Complex and discussed the major trends, geometry and age relationship of the various structures within the Complex. The trend surface analysis of the Eastern Bushveld reveals that most of the residual positive structures occur as isolated closures with dome shape and are consistent with the location of the diapiric structures previously identified by geophysical and field mapping techniques.

Geo-Spatial Mapping of the Northern Bushveld Rustenburg Layered Suite (RLS) in South Africa

The focus of this paper is on determination of the geometry and stratigraphic contact pattern of the Rustenburg Layered Suite (RLS) in the Northern Bushveld Complex area using available borehole data and trend surface analysis technique. This technique was used to analyse over one hundred borehole log data in the Northern Bushveld Complex in order to describe the geometric pattern and trends of the RLS rocks. The results demonstrate the usefulness of this technique in identifying structural features. Regional trends of each of the stratigraphic units reveal the presence of regional structures that were not obvious at the surface. This first part of the paper focused on the Northern Bushveld Complex, while the second and the third part focused on the eastern and western Bushveld limbs respectively.

Trends and Uncertainties in Surface Air Temperature over the Tibetan Plateau,1951–2013

Trends and uncertainties of surface air temperature over the Tibetan Plateau（TP）are evaluated by using observations at 100 meteorological stations during the period 1951–2013.The sampling error variances of gridded monthly data are estimated for every month and every grid box of data.The gridded data and their sampling error variances are used to calculate TP averages,their trends,and associated uncertainties.It is shown that large sampling error variances dominate northern and western TP,while small variances appear over southern and eastern TP.Every month from January to December has a positive linear trend during the study period.February has the largest trend of 0.34±0.18°C（10 yr）^（–1）,and April the smallest at 0.15±0.11°C（10 yr）^（–1）.The uncertainties decrease steadily with time,implying that they are not large enough to alter the TP warming trend.

Winter sea ice albedo variations in the Bohai Sea of China

Sea ice conditions in the Bohai Sea of China are sensitive to large-scale climatic variations. On the basis of CLARA-A1-SAL data, the albedo variations are examined in space and time in the winter（December, January and February） from 1992 to 2008 in the Bohai Sea sea ice region. Time series data of the sea ice concentration（SIC）, the sea ice extent（SIE） and the sea surface temperature（SST） are used to analyze their relationship with the albedo. The sea ice albedo changed in volatility appears along with time, the trend is not obvious and increases very slightly during the study period at a rate of 0.388% per decade over the Bohai Sea sea ice region.The interannual variation is between 9.93% and 14.50%, and the average albedo is 11.79%. The sea ice albedo in years with heavy sea ice coverage, 1999, 2000 and 2005, is significantly higher than that in other years; in years with light sea ice coverage, 1994, 1998, 2001 and 2006, has low values. For the monthly albedo, the increasing trend（at a rate of 0.988% per decade） in December is distinctly higher than that in January and February. The mean albedo in January（12.90%） is also distinctly higher than that in the other two months. The albedo is significantly positively correlated with the SIC and is significantly negatively correlated with the SST（significance level 90%）.

Investigating long-term trends of climate change and their spatial variations caused by regional and local environments through data mining

Climate change is a global phenomenon but is modified by regional and local environmental conditions.Moreover,climate change exhibits remarkable cyclical oscillations and disturbances,which often mask and distort the long-term trends of climate change we would like to identify.Inspired by recent advancements in data mining,we experimented with empirical mode decomposition(EMD)technique to extract long-term change trends from climate data.We applied GIS elevation model to construct 3 D EMD trend surface to visualize spatial variations of climate change over regions and biomes.We then computed various time-series similarity measures and plot them to examine spatial patterns across meteorological stations.We conducted a case study in Inner Mongolia based on daily records of precipitation and temperature at 45 meteorological stations from 1959 to 2010.The EMD curves effectively illustrated the long-term trends of climate change.The EMD 3 D surfaces revealed regional variations of climate change,while the EMD similarity plots disclosed cross-station deviations.In brief,the change trends of temperature were significantly different from those of precipitation.Noticeable regional patterns and local disturbances of the changes in both temperature and precipitation were identified.The trends of change were modified by regional and local topographies and land covers.

The Ame2020 atomic mass evaluation(II).Tables,graphs and references

This is the second part of the new evaluation of atomic masses,Ame2020.Using least-squares adjustments to all evaluated and accepted experimental data,described in Part I,we derived tables with numerical values and graphs which supersede those given in Ame2016.The first table presents the recommended atomic mass values and their uncertainties.It is followed by a table of the influences of data on primary nuclides,a table of various reaction and decay energies,and finally,a series of graphs of separation and decay energies.The last section of this paper provides all input data references that were used in the Ame2020 and the Nubase2020 evaluations.

The Ame2020 atomic mass evaluation (I). Evaluation of input data, and adjustment procedures

This is the first of two articles(Part I and Part II)that presents the results of the new atomic mass evaluation,Ame2020.It includes complete information on the experimental input data that were used to derive the tables of recommended values which are given in Part II.This article describes the evaluation philosophy and procedures that were implemented in the selection of specific nuclear reaction,decay and mass-spectrometric data which were used in a least-squares fit adjustment in order to determine the recommended mass values and their uncertainties.All input data,including both the accepted and rejected ones,are tabulated and compared with the adjusted values obtained from the least-squares fit analysis.Differences with the previous Ame2016 evaluation are discussed and specific examples are presented for several nuclides that may be of interest to Ame users.

The AME2016 atomic mass evaluation

This paper is the first of two articles （Part I and Part II） that presents the results of the new atomic mass evaluation, AME2016. It includes complete information on the experimental input data （also including unused and rejected ones）, as well as details on the evaluation procedures used to derive the tables of recommended values given in the second part. This article describes the evaluation philosophy and procedures that were implemented in the selection of specific nuclear reaction, decay and mass-spectrometric results. These input values were entered in the least-squares adjustment for determining the best values for the atomic masses and their uncertainties. Details of the calculation and particularities of the AME are then described. All accepted and rejected data, including outweighted ones, are presented in a tabular format and compared with the adjusted values obtained using the least-squares fit analysis. Differences with the previous AME2012 evaluation are discussed and specific information is presented for several cases that may be of interest to AME users. The second AME2016 article gives a table with the recommended values of atomic masses, as well as tables and graphs of derived quantities, along with the list of references used in both the AME2016 and the NUBASE2016 evaluations （the first paper in this issue）.