基于地学信息的土壤属性高精度曲面建模

目前土壤属性的曲面建模面临两大问题,一是缺乏足够多的采样点进行模拟,二是采样点的土壤属性与环境变量间存在非线性关系。高精度曲面建模(HASM)方法在如何融合地学信息对土壤属性进行空间插值,尚需深入研究。本文提出高精度曲面建模与地学信息相结合的土壤属性空间插值方法(High accuracy surface modeling for soil properties, HASM-SP),分别基于研究区的土壤类型、土地利用类型和母岩类型,模拟了江西省典型红壤丘陵区土壤的速效磷(AP)、锂(Li)、pH、碱解氮(AN)、全钾(K) 和铬(Cr) 6 种土壤属性的空间分布。将HASM-SP与普通克立格(OK)、OK与地学信息相结合的方法(OK-Geo) 和分层克立格(SK) 相对比,结果表明：结合地学信息可以使插值方法(HASM-SP和OK-Geo) 模拟结果的平均误差更趋近于0;相对于其他3 种方法,HASM-SP具有较小的平均绝对误差和均方根误差。从模拟的空间分布图上来看,HASM-SP获得了由于地学要素类型突变导致的土壤属性空间变异的细节信息。因此,基于地学信息的土壤属性高精度曲面建模方法(HASM-SP) 与传统插值方法相比,不仅提高了土壤属性空间分布的模拟精度,还能更好地刻画突变边界处土壤属性的空间变异,使土壤属性分布图更好地符合地学规律和实际情况。HASM-SP的提出对于丰富土壤属性的高精度曲面建模理论具有重要意义,并为土壤管理、精准农业的实施以及区域环境规划等提供科学依据。     

A high accuracy surface modeling method based on GPU accelerated multi‐grid method

A high accuracy surface modeling method (HASM) has been developed to provide a solution to many surface modeling problems such as DEM construction, surface estimation and spatial prediction. Although HASM is able to model surfaces with a higher accuracy, its low computing speed limits its popularity in constructing large scale surfaces. Hence, the research described in this article aims to improve the computing efficiency of HASM with a graphic processor unit (GPU) accelerated multi‐grid method (HASM‐GMG). HASM‐GMG was tested with two types of surfaces: a Gauss synthetic surface and a real‐world example. Results indicate that HASM‐GMG can gain significant speedups compared with CPU‐based HASM without acceleration on GPU. Moreover, both the accuracy and speed of HASM‐GMG are superior to the classical interpolation methods including Kriging, Spline and IDW.     

中国气温与降水的时空变化趋势分析

如何对离散分布的气象台站观测数据进行高精度曲面模拟,为生态系统及服务功能时空变化趋势模拟及其综合评估提供高质量、高分辨率的空间气候数据,以满足栅格层次上的生态系统过程模型、生态系统格局模型及生态系统综合评估模型的参数需求,一直是存于生态学界的难点问题.在对全国1964一2007年的752个气象台站长期观测的气温和降水数...     

基于GPU的HASM动态模拟与实时渲染方法

 基于微分几何曲面论的高精度曲面模拟(high accuracy surface modeling, HASM)需要大量的复杂密集计算,在CPU上模拟极为耗时,使得在现有的硬件条件下,实时动态模拟曲面并实时可视化极具挑战性。论文提出了GPU加速的HASM方法,充分利用现代显示适配器(graphic processor unit, GPU)技术,运用GPU最新发展起来的并行计算能力,使用并行化的预处理共轭梯度方法解算曲面,完成曲面模拟,并同时利用GPU的高速缓存架构,对渲染操作进行充分优化,以实现高效实时可视化。HASM需要的有限差分离散和高速解算操作,均充分利用现代GPU架构,所具有的多处理器和众多的流处理器所产生的强大并行计算能力,可视化也用GPU高速缓存技术和三角条带方法进行充分优化。数值实验和实际项目区高程模拟实验均表明, 在GPU为NVIDIA quadro 2000和CPU为DualCore Intel Core 2 Duo E8400的硬件配置下,GPU并行化的曲面模拟方法比普通方法速度提高了约10倍,使得动态模拟与可视化算法可以达到交互式的帧速及实时可视化的要求。     

基于HASM的中国森林植被碳储量空间分布模拟

当前区域尺度上森林碳储量估算主要依据森林资源清查数据,整个过程不仅消耗大量人力、物力,而且十分耗时,严重影响了森林碳储量估算的时效性。针对这一问题,本文提出了基于HASM的森林植被碳储量模拟方法,该方法以全球植被动态模型LPJ-Guess 输出的植被碳储量为驱动场,以森林清查样地数据为精度控制点,模拟生成中国陆地森林碳储量分布情况。研究以第7 次中国森林资源清查数据作为精度控制点数据源,同时作为本文模拟方法的精度验证。结果表明,中国森林碳储量为9.2405 Pg,考虑到森林资源清查是基于一定的郁闭度进行的,因此HASM模拟的结果与根据森林资源清查结果计算得出的7.8115 Pg 相比更符合实际情况,西南山区和东北林区是中国森林最主要的碳库,其碳储量分别占中国森林植被碳储量的39.82%和20.46%。同时与之前(1975-1995 年) 相比具有较大幅度的增长,表明近几十年来中国坚持大规模植树造林的碳汇效果显著。同时也表明基于HASM的森林植被碳储量空间分布模拟方法是有效的,模拟结果合理且精度较高,表明该方法在全球尺度上森林植被碳储量模拟及其它生态系统中碳储量模拟中具有应用潜力。     

HASM-AD algorithm based on the sequential least squares

The HASM(high accuracy surface modeling) technique is based on the fundamental theory of surfaces,which has been proved to improve the interpolation accuracy in surface fitting.However,the integral iterative solution in previous studies resulted in high temporal complexity in computation and huge memory usage so that it became difficult to put the technique into application,especially for large-scale datasets.In the study,an innovative model(HASM-AD) is developed according to the sequential least squares on...     

机载LIDAR数据的树高识别算法与应用分析

利用机载激光雷达数据提取天然次生林的树高,旨在探索影响树高提取精度的主要因素。首先,采用高精度曲面建模平差算法(Adjustment Computation of High-accuracy Surface Modeling,HASM-AD)生成研究区不同空间分辨率的数字高程模型(Digital Elevation Model,DEM)、数字地表模型(Digital Surface Model,DSM)和冠层高度模型(Canopy Height Model,CHM);其次,用树顶点识别算法提取林木树高,设置不同树高识别范围,对比分析不同CHM分辨率和不同树高识别范围对树高提取精度的影响;最后,以天涝池流域30个实测样地数据为样本,对提取精度进行检验。结果显示：提取的样地平均树高与实测值具有明显线性相关关系,线性回归系数为0.694;树高识别范围是影响树高提取精度的重要因素,CHM分辨率对其影响较小。研究表明,采用高采样密度的雷达点云数据、正确选择CHM生成方法和改进树顶点识别算法是提高天然次生林树高提取精度的有效途径。     

省尺度森林植被碳储量空间分布模拟不确定性分析——以江西省为例（英文）

Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertainty apparently existed between results of different methods, even estimates of same method in different studies. Three previous methods, including Atmosphere-vegetation interaction model 2(AVIM2), Kriging, Satellite-data Based Approach(SBA), and a new method, High Accuracy Surface Modeling(HASM), were used to simulate forest vegetation carbon stock patterns in Jiangxi Province in China. Cross-validation was used to evaluate methods. The uncertainty and applicability of the four methods on provincial scale were analyzed and discussed. The results showed that HASM had the highest accuracy, which improved by 50.66%, 33.37% and 28.58%, compared with AVIM2, Kriging and SBA, respectively. Uncertainty of simulation of forest biomass carbon stock was mainly derived from modeling error, sampling error and statistical error of forest area. Total forest carbon stock, carbon density and forest area of Jiangxi were 288.62 Tg, 3.06 kg/m~2 and 94.32×109 m~2 simulated by HASM, respectively.     

一种土壤属性制图的曲面建模方法(英文)

High accuracy surface modeling(HASM) is a method which can be applied to soil property interpolation.In this paper,we present a method of HASM combined geographic information for soil property interpolation(HASM-SP) to improve the accuracy.Based on soil types,land use types and parent rocks,HASM-SP was applied to interpolate soil available P,Li,pH,alkali-hydrolyzable N,total K and Cr in a typical red soil hilly region.To evaluate the performance of HASM-SP,we compared its performance with that of ordinary kriging(OK),ordinary kriging combined geographic information(OK-Geo) and stratified kriging(SK).The results showed that the methods combined with geographic information including HASM-SP and OK-Geo obtained a lower estimation bias.HASM-SP also showed less MAEs and RMSEs when it was compared with the other three methods(OK-Geo,OK and SK).Much more details were presented in the HASM-SP maps for soil properties due to the combination of different types of geographic information which gave abrupt boundary for the spatial varia-tion of soil properties.Therefore,HASM-SP can not only reduce prediction errors but also can be accordant with the distribution of geographic information,which make the spatial simula-tion of soil property more reasonable.HASM-SP has not only enriched the theory of high accuracy surface modeling of soil property,but also provided a scientific method for the ap-plication in resource management and environment planning.     

Combining LPJ-GUESS and HASM to simulate the spatial distribution of forest vegetation carbon stock in China简

It is very important in accurately estimating the forests＇ carbon stock and spatial distribution in the regional scale because they possess a great rate in the carbon stock of the terrestrial ecosystem. Yet the current estimation of forest carbon stock in the regional scale mainly depends on the forest inventory data, and the whole process consumes too much labor, money and time. And meanwhile it has many negative influences on the forest carbon storage updating. In order to figure out these problems, this paper, based on High Accuracy Surface Modeling （HASM）, proposes a forest vegetation carbon storage simulation method. This new method employs the output of LPJ-GUESS model as initial values of HASM and uses the inventory data as sample points of HASM to simulate the distribution of forest carbon storage in China. This study also adopts the seventh forest resources statistics of China as the data source to generate sample points, and it also works as the simulation accuracy test. The HASM simulation shows that the total forest carbon storage of China is 9.2405 Pg, while the calculated value based on forest resources statistics are 7.8115 Pg. The forest resources statistics is taken based on a forest canopy closure, and the result of HASM is much more suitable to the real forest carbon storage. The simulation result also indicates that the southwestern mountain region and the northeastern forests are the important forest carbon reservoirs in China, and they account for 39.82% and 20.46% of the country＇s total forest vegetation carbon stock respectively. Compared with the former value （1975-1995）, it mani- fests that the carbon storage of the two regions do increase clearly. The results of this re- search show that the large-scale reforestation in the last decades in China attains a signifi- cant carbon sink.