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.

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.

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.

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.

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.

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.