大数据分析下三维景观图像布局优化提取仿真
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摘要
对大数据分析下三维景观图像的布局进行提取,对城市平面扩张的定量研究有重要意义。目前对城市扩张进行定量研究只停留在扩张层面,不能对内部土地结构演变的过程进行衡量。传统方法对并查集连通域计算法进行改进,为景观布局指数提供参数。提出基于改进梯度匹配三维景观图像布局优化指数提取方法。首先利用不同的三维集聚空间算法在不同的角度对三维景观图像布局优化的指数特征进行提取,结合提取出的特征利用改进梯度匹配的方法对三维景观图像布局优化的指数进行提取,在原始的梯度向量只包含幅度信息基础上,对相位的信息进行引入,对原始的匹配进行不断地变化,将景观布局的异常值进行消化,提取斑块的数量、斑块指数以及景观的斑块面积和斑块的分维数等指数。实验结果表明,能有效地对城市的扩张进行定量研究。
A method for extracting 3 D landscape image layout optimization index based on improved gradient matching is proposed. Firstly,different 3 D agglomeration space algorithms are used to extract the exponent characteristic of 3 D image layout optimization in different angles. By combining with extracted characteristics,the improved method based on gradient matching is used to extract index of 3 D landscape image layout optimization. Because the amplitude information is only included in original gradient vector,the phase information is introduced and the original matching is changed constantly,then abnormal value of landscape layout is digested. Thus,the number of plaque,the plaque index,the plaque area of landscape and the fractal dimension index of plaque are extracted. Simulation results show that the proposed method can quantitatively study the urban sprawl.
A method for extracting 3 D landscape image layout optimization index based on improved gradient matching is proposed. Firstly,different 3 D agglomeration space algorithms are used to extract the exponent characteristic of 3 D image layout optimization in different angles. By combining with extracted characteristics,the improved method based on gradient matching is used to extract index of 3 D landscape image layout optimization. Because the amplitude information is only included in original gradient vector,the phase information is introduced and the original matching is changed constantly,then abnormal value of landscape layout is digested. Thus,the number of plaque,the plaque index,the plaque area of landscape and the fractal dimension index of plaque are extracted. Simulation results show that the proposed method can quantitatively study the urban sprawl.
引文
[1]邵大伟,吴殿鸣.基于景观指数的南京主城区绿色空间演变特征研究[J].中国园林,2016,32(2):103-107.
[2]吴未,等.不同斑块类型的景观指数粒度效应响应——以无锡市为例[J].生态学报,2016,36(9):2740-2749.
[3]黄思琴,等.基于景观指数的耕地细碎化与农业经济水平的空间相关性分析[J].干旱地区农业研究,2015,33(3):238-244.
[4]吴未,等.无锡市景观指数的粒度效应研究[J].自然资源学报,2016,31(3):413-424.
[5]康孝岩,王艳慧,段福洲.单一景观空间分布指数及其适用性评价[J].生态学报,2015,35(5):1311-1320.
[6]宋彦涛,等.放牧强度对克氏针茅(Stipakrylovii)草原植被景观格局的影响[J].中国沙漠,2016,36(3):674-680.
[7]郑媛元.城市道路两翼植物景观三维图像优化设计仿真[J].计算机仿真,2016,33(11):250-253.
[8]刘洋,关庆锋.景观指数的并行计算方法[J].地球信息科学学报,2017,19(4):457-466.
[9]崔闪闪,刘庆,王静.滨海开发带景观格局指数的尺度效应及对土地利用变化的响应——以江苏省大丰市为例[J].地理与地理信息科学,2016,32(6):87-93.
[10]王蕾,陈崇成,唐丽玉.集成虚拟森林环境与景观指数计算模型的森林景观格局分析[J].地球信息科学学报,2017,19(2):281-288.
[2]吴未,等.不同斑块类型的景观指数粒度效应响应——以无锡市为例[J].生态学报,2016,36(9):2740-2749.
[3]黄思琴,等.基于景观指数的耕地细碎化与农业经济水平的空间相关性分析[J].干旱地区农业研究,2015,33(3):238-244.
[4]吴未,等.无锡市景观指数的粒度效应研究[J].自然资源学报,2016,31(3):413-424.
[5]康孝岩,王艳慧,段福洲.单一景观空间分布指数及其适用性评价[J].生态学报,2015,35(5):1311-1320.
[6]宋彦涛,等.放牧强度对克氏针茅(Stipakrylovii)草原植被景观格局的影响[J].中国沙漠,2016,36(3):674-680.
[7]郑媛元.城市道路两翼植物景观三维图像优化设计仿真[J].计算机仿真,2016,33(11):250-253.
[8]刘洋,关庆锋.景观指数的并行计算方法[J].地球信息科学学报,2017,19(4):457-466.
[9]崔闪闪,刘庆,王静.滨海开发带景观格局指数的尺度效应及对土地利用变化的响应——以江苏省大丰市为例[J].地理与地理信息科学,2016,32(6):87-93.
[10]王蕾,陈崇成,唐丽玉.集成虚拟森林环境与景观指数计算模型的森林景观格局分析[J].地球信息科学学报,2017,19(2):281-288.