Introducing tree neighbouring relationship factors in forest pattern spatial analysis:weighted Delaunay triangulation method

It is important to quantify and analyze forest spatial patterns for studying biological characteristics,population interaction and the relationship between the population and environment.In this study,the forest spatial structure unit was generated based on the Delaunay triangulation model(DTM),and the weights were generated using the comprehensive values of the tree diameter at breast height,total height and crown width.The distance between neighbors determined by the DTM was weighted to transform the original coordinates of trees into logical coordinates.Then,a weighted spatial pattern(WSP)was developed.After weighting,the neighboring trees were replaced,the replacement ratio was 38.3%,and there was 57.4%of the central tree.Correlation analysis showed that the uniform angle index of the WSP was significantly correlated with the tree size standard deviation under uniformity(r=0.932)and randomness(r=0.711).The DTM method not only considers the spatial distance between trees,but also considers the non-spatial attributes of trees.By changing the spatial topological relation between trees,this method further improves the spatial structure measurement of forest.

Layer-Constrained Triangulated Irregular Network Algorithm Based on Ground Penetrating Radar Data and Its Application

In this paper,a layer-constrained triangulated irregular network（ LC-TIN） algorithm is proposed for three-dimensional（ 3 D） modelling,and applied to construct a 3 D model for geological disease information based on ground penetrating radar（ GPR） data. Compared with the traditional TIN algorithm,the LCTIN algorithm introduced a layer constraint to the discrete data points during the 3 D modelling process,and it can dynamically construct networks from layer to layer and implement 3 D modelling for arbitrary shapes with high precision. The experimental results validated this method,the proposed algorithm not only can maintain the rationality of triangulation network,but also can obtain a good generation speed. In addition,the algorithm is also introduced to our self-developed 3 D visualization platform,which utilized GPR data to model geological diseases. Therefore the feasibility of the algorithm is verified in the practical application.

Source and hazard identification of heavy metals in soils of Changsha based on TIN model and direct exposure method

A total of 153 soil samples were collected from Changsha City, China, to analyze the contents of As, Cd, Cr, Cu, Hg, Mn, Ni, Pb and Zn. A combination of sampling data, multivariate statistical method, geostatistical analysis, direct exposure method and triangulated irregular network （TIN） model was successfully employed to discriminate sources, simulate spatial distributions and evaluate children＇s health risks of heavy metals in soils. The results show that not all sites in Changsha city may be suitable for living without remediation. About 9.0% of the study area provided a hazard index （HI）1.0, and 1.9% had an HI2.0. Most high HIs were located in the southern and western areas. The element of arsenic and the pathway of soil ingestion were the largest contribution to potential health risks for children. This study indicates that we should attach great importance to the direct soil heavy metals exposure for children＇s health.

Three-Dimensional TIN Algorithm for Digital Terrain Modeling

The problem of taking an unorganized point cloud in 3D space and fitting a polyhedral surface to those points is both important and difficult. Aiming at increasing applications of full three dimensional digital terrain surface modeling, a new algorithm for the automatic generation of three dimensional triangulated irregular network from a point cloud is pro- posed. Based on the local topological consistency test, a combined algorithm of constrained 3D Delaunay triangulation and region-growing is extended to ensure topologically correct reconstruction. This paper also introduced an efficient neighbor- ing triangle location method by making full use of the surface normal information. Experimental results prove that this algo- rithm can efficiently obtain the most reasonable reconstructed mesh surface with arbitrary topology, wherein the automati- cally reconstructed surface has only small topological difference from the true surface. This algorithm has potential applica- tions to virtual environments, computer vision, and so on.

A New Algorithm to Automatically Extract the Drainage Networks and Catchments Based on Triangulation Irregular Network Digital Elevation Model

A new algorithm to automatically extract drainage networks and catchments based on triangulation irregular networks(TINs) digital elevation model(DEM) was developed. The flow direction in this approach is determined by computing the spatial gradient of triangle and triangle edges. Outflow edge was defined by comparing the contribution area that is separated by the steepest descent of the triangle. Local channels were then tracked to build drainage networks. Both triangle edges and facets were considered to construct flow path. The algorithm has been tested in the site for Hawaiian Island of Kaho'olawe, and the results were compared with those calculated by ARCGIS as well as terrain map. The reported algorithm has been proved to be a reliable approach with high efficiency to generate well-connected and coherent drainage networks.

Comparative study and error analysis of digital elevation model interpolations

Researchers in P.R.China commonly create triangulate irregular networks(TINs) from contours and then convert TINs into digital elevation models(DEMs).However,the DEM produced by this method can not precisely describe and simulate key hydrological features such as rivers and drainage borders.Taking a hilly region in southwestern China as a research area and using ArcGISTM software,we analyzed the errors of different interpolations to obtain distributions of the errors and precisions of different algorithms and to provide references for DEM productions.The results show that different interpolation errors satisfy normal distributions,and large error exists near the structure line of the terrain.Furthermore,the results also show that the precision of a DEM interpolated with the Australian National University digital elevation model(ANUDEM) is higher than that interpolated with TIN.The DEM interpolated with TIN is acceptable for generating DEMs in the hilly region of southwestern China.

Large-Scale Terrain Simplification and Visualization Based on TIN

In the preprocessing phase, the global terrain model is partitioned into blocks with their feature points being picked out to generate TIN model for each terrain block, then the multi-resolution models of terrain organized in the form of quad-tree is created bottom-up. Cracks between terrain blocks are avoided by inserting vertices to form common boundaries. At run-time, a view-dependent LOD algorithm is used to control the loading and unloading of the proper blocks by an additional synchronous thread. To eliminate the artifacts created by LOD transitions, geomorphing is used in real-time. These rendering strategies increase the throughput of GPU and avoid imbalance of load among CPU, GPU and Disk I/O. Experimental results show that the system can perform visually smooth rendering of large-scale terrain scenes with fine quality at an average rate of 80 fps.

Methods for the construction of DEMs of artificial slopes considering morphological features and semantic information

As human activities increase,artificially modified terrain is increasingly widely distributed in road,hydrological,and urban construction.Artificially modified terrain plays an important role in protecting from geological disasters and in the planning and design of urban landscapes.Compared with natural slopes,artificial slopes have obvious morphological characteristics.Traditional modeling methods are no longer suitable for digital elevation model(DEM)modeling of artificial slopes because they often seriously distort the DEM results.In this paper,from the perspective of morphological characteristics,artificial slopes are divided into two types,namely,regular slopes and irregular slopes,based on whether the top and bottom lines of the artificial slope are parallel.Then,according to the morphological characteristics of the two types of slopes,the following DEM construction methods are designed:the first method(perpendicular+inverse distance weighted)is suitable for regular slopes,and the second method(perpendicular+high-accuracy surface modeling)is suitable for irregular slopes.Finally,a DEM construction test is carried out using the artificial slopes in the study area.The results show that for the regular and irregular slopes in the study area,the construction method proposed in this paper has significant advantages in morphological accuracy over the traditional method(triangulated irregular network),and the elevation accuracy method is also superior to the traditional method(using this method,the mean error and standard deviation error of the regular slope DEM are 0.08 m and 0.13 m,respectively,and those of the irregular slope DEM are 0.08 m and 0.06 m).In addition,the top lines and bottom lines can be included in the DEM construction of the background area after processing the elevation information of the boundary line to realize a smooth transition in the boundary between the artificial slope and the background area.

Terrain Simplification Research in Augmented Scene Modeling

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

A combined contour lines iteration algorithm and Delaunay triangulation for terrain modeling enhancement

Digital Elevation Models(DEMs)play a crucial role in civil and environmental applications,such as hydrologic and geologic analyses,hazard monitoring,natural resources exploration,etc.Generally,DEMs can be generated from various data sources,such as ground surveys,photogrammetric stereo methods,satellite images,laser scanning,and digitized contour lines.Compared with other data sources,contour lines are still the cheapest and more common data source becausethey cover all areas,at different scales,in most countries.Although there are different algorithms and technologies for interpolation in between contour lines,DEMs extracted solely from contours still suffer from poor terrain quality representation,which in turn negatively affects the quality of analytical applications results.In this paper,an approach for improving the digital terrain modeling based on contour line densification and Delaunay triangulation is presented to acquire a more suitable DEM for hydrographic modeling and its applications.The proposed methodology was tested using a variety of terrain patterns in terms of intensity:hilly,undulated,and plain(1:25,000 topographic map,5 m contour interval).The precision of the extracted GRID model increases as the number of added contours increases.Adding four contour lines,the Root Mean Square Error(RMSE)of examining points were 0.26 m,0.29 m,and 0.05 m for hilly,undulated,and plain samples,respectively,and the Mean Absolute Error(MAE)were 0.50 m,0.48 m,and 0.17 m.The convergence probabilities between extracted and original flow lines for the same regions were 96.91%,94.93%,and 84.03%.Applying the methodology,experimental results indicate that the developed approach provides a significant advantage in terrain modeling enhancement,generates DEMs smoothly and effectively from contours,mitigates problems and reduces uncertainties.

SAR imaging simulation for an inhomogeneous undulated lunar surface based on triangulated irregular network

Based on the statistics of the lunar cratered terrain, e.g., population, dimension and shape of craters, the terrain feature of cratered lunar surface is numerically generated. According to the inhomogeneous distribution of the lunar surface slope, the triangulated irregular network （TIN） is employed to make the digital elevation of lunar surface model. The Kirchhoff approximation of surface scattering is then applied to simulation of lunar surface scattering. The synthetic aperture radar （SAR） image for compre- hensive cratered lunar surface is numerically generated using back projection （BP） algorithm of SAR imaging. Making use of the digital elevation and Clementine UVVIS data at Apollo 15 landing site as the ground truth, an SAR image at Apollo 15 landing site is simulated. The image simulation is verified using real SAR image and echoes statistics.

Reconstructing pre-erosion topography using spatial interpolation techniques： A validation-based approach

Understanding the topographic context preceding the development of erosive landforms is of major relevance in geomorphic research, as topography is an important factor on both water and mass movement-related erosion, and knowledge of the original surface is a condition for quantifying the volume of eroded material. Although any reconstruction implies assuming that the resulting surface reflects the original topography, past works have been dominated by linear interpolation methods, incapable of generating curved surfaces in areas with no data or values out- side the range of variation of inputs. In spite of these limitations, impossibility of validation has led to the assumption of surface representativity never being challenged. In this paper, a validation-based method is applied in order to define the optimal interpolation technique for reconstructing pre-erosion topography in a given study area. In spite of the absence of the original surface, different techniques can be nonetheless evaluated by quantifying their ca- pacity to reproduce known topography in unincised locations within the same geomorphic contexts of existing erosive landforms. A linear method （Triangulated Irregular Network, TIN） and 23 parameterizations of three distinct Spline interpolation techniques were compared using 50 test areas in a context of research on large gully dynamics in the South of Portugal. Results show that almost all Spline methods produced smaller errors than the TIN, and that the latter produced a mean absolute error 61.4% higher than the best Spline method, clearly establishing both the better adjustment of Splines to the geomorphic context considered and the limitations of linear approaches. The proposed method can easily be applied to different interpolation techniques and topographic contexts, enabling better calculations of eroded volumes and denudation rates as well as the investigation of controls by antecedent topographic form over erosive processes.

Extracting body surface dimensions from top-view images of pigs

Continuous live weight and carcass traits estimation are important for the pig production and breeding industry.It is widely known that top-view images of a pig’s body(excluding its head and neck)reveal surface dimension parameters,which are correlated with live weight and carcass traits.However,because a pig is not constrained when an image is captured,the body does not always have a straight posture.This creates a big challenge when extracting the body surface dimension parameters,and consequently the live weight and carcass traits estimation has a high level of uncertainty.The primary goal of this study is to propose an algorithm to automatically extract pig body surface dimension parameters,with a better accuracy,from top-view pig images.Firstly,the backbone line of a pig was extracted.Secondly,lengths of line segments perpendicular to the backbone line were calculated,and then feature points on the pig’s contour line were extracted based on the lengths variation of the perpendicular line segments.Thirdly,the head and neck of the pig were removed from the pig’s contour by an ellipse.Finally,four length and one area parameters were calculated.The proposed algorithm was implemented in Matlab®(R2012b)and applied to 126 depth images of pigs.Taking the results of the manual labeling tool as the gold standard,the length and area parameters could be obtained by the proposed algorithm with an accuracy of 97.71%(SE=1.64%)and 97.06%(SE=1.82%),respectively.These parameters can be used to improve pig live weight and carcass traits estimation accuracy in the future work.

Comparison of Extrapolation and Interpolation Methods for Estimating Daily Photosynthetically Active Radiation(PAR)——A Case Study of the Poyang Lake National Nature Reserve,China

Measurements of photosynthetically active radiation （PAR）, which are indispensable for simulating plant growth and productivity, are generally very scarce. This study aimed to compare two extrapolation and one interpolation methods for estimating daily PAR reaching the earth surface within the Poyang Lake national nature reserve, China. The daily global solar radiation records at Nanchang meteorological station and daily sunshine duration measurements at nine meteorological stations around Poyang Lake were obtained to achieve the objective. Two extrapolation methods of PARs using recorded and estimated global solar radiation at Nanchang station and three stations （Yongxiu, Xingzi and Duchang） near the nature reserve were carried out, respectively, and a spatial interpolation method combining triangulated irregular network （TIN） and inverse distance weighting （IDW） was imple- mented to estimate daily PAR. The performance evaluation of the three methods using the PARs measured at Dahuchi Conservation Station （day number of measurement = 105 days） revealed that： （1） the spatial interpolation method achieved the best PAR estima- tion （R2 - 0.89, s.c. = 0.99, F= 830.02, P 〈 0.001 ）; （2） the extrapolation method from Nanchang station obtained an unbiased result （R2 = 0.88, s.c. = 0.99, F = 745.29, P 〈 0.001）; however, （3） the extrapolation methods from Yongxiu, Xingzi and Duchang stations were not suitable for this specific site for their biased estimations. Considering the assumptions and principles supporting the extrapolation and interpolation methods, the authors conclude that the spatial interpolation method produces more reliable results than the extrapolation methods and holds the greatest potential in all tested methods, and more PAR measurements should be recorded to evaluate the seasonal, yearly and spatial stabilities of these models for their application to the whole nature reserve of Poyang Lake.

An Improved Filter of Progressive TIN Densification for LiD AR Point Cloud Data

Based on the classic filter of progressive triangulated irregular network（TIN） densification, an improved filter is proposed in this paper. In this method, we divide ground points into grids with certain size and select the lowest points in the grids to reconstruct TIN in the process of iteration. Compared with the classic filter of progressive TIN densification（PTD）, the improved method can filter out attached objects, avoid the interference of low objects and obtain relatively smooth bare-earth. In addition, this proposed filter can reduce memory requirements and be more efficient in processing huge data volume. The experimental results show that the filtering accuracy and efficiency of this method is higher than that of the PTD method.