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

doi:10.3724/SP.J.1047.2017.00281

地球信息科学学报 ›› 2017, Vol. 19 ›› Issue (2): 281-288.doi: 10.3724/SP.J.1047.2017.00281

• 遥感科学与应用技术 • 上一篇

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

王蕾(), 陈崇成^*(), 唐丽玉

福州大学地理空间信息技术国家地方联合工程研究中心,空间数据挖掘与信息共享教育部重点实验室,福建省空间信息工程研究中心,福州 350002

收稿日期:2015-10-29 修回日期:2016-01-05 出版日期:2017-02-28 发布日期:2017-02-17
通讯作者: 陈崇成 E-mail:lay19921208@163.com;chencc@fzu.edu.cn
作者简介:
作者简介：王蕾（1992-）,女,江西南昌人,硕士生,研究方向为空间信息技术与城乡规划管理。E-mail: lay19921208@163.com
基金资助:
国家自然科学基金项目（41471334）;国家“863”计划项目课题（2012AA102002）

Forest Landscape Pattern Analysis Using the Integration of Virtual Forest Environment and Landscape Index Calculation Model

WANG Lei(), CHEN Chongcheng^*(), TANG Liyu

National Engineering Research Centre of Geospatial Information Technology, Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Spatial Information Research Center of Fujian Province,Fuzhou University, Fuzhou 350002, China

Received:2015-10-29 Revised:2016-01-05 Online:2017-02-28 Published:2017-02-17
Contact: CHEN Chongcheng E-mail:lay19921208@163.com;chencc@fzu.edu.cn

摘要/Abstract

摘要：

森林景观格局分析是森林景观优化配置与实施规划的基础。本文以森林资源二类调查数据为基础,采用森林景观定量空间分析方法,在自主开发而成的森林景观可视化系统VisForest支持下,利用VS2008开发平台、ArcEngine组件与OSG图形渲染引擎,集成景观指数计算模型和地理信息系统的分析方法,形成森林景观格局分析与景观三维可视化模拟系统,实现了景观格局分析的定量化和景观可视化;并以闽侯县白沙国有林场2013年的数据为例,按优势树种划分森林景观类型,计算分析了景观组成结构、斑块特征和景观异质性等。结果表明,杉木林、马尾松林、湿地松林、木荷林、非林地是白沙林场的优势景观类型,总体景观类型丰富、景观异质性较高;木荷作为隔离带树种,以小面积狭长斑块居多,其形状指数和分形维数最大,斑块形状复杂而不规则;森林景观的三维可视化模拟为研究景观格局提供了一个直观、交互的展示平台。

关键词: 森林景观格局, 景观指数, 可视化, 二类调查

Abstract:

Forest landscape pattern analysis is the basis for the optimization allocation and planning of forest landscape. Based on the data obtained from the second class survey of forest resources, with the integration of the forest landscape quantitative spatial analysis method and the independently-developed forest landscape visualization system software VisForest, a forest landscape pattern analysis and forest landscape 3D visualization simulation system was developed. This system is integrated with the landscape index calculation model and the geographic information system analysis method. The mainframe of the system was coded on Visual Studio 2008 platform with ArcEngine component and OSG graphics rendering engine incorporated, which has realized the quantitative and visual analysis of landscape pattern. Minhou Baisha national forest farm was taken as an example in this study. According to the dominant tree species, the forest landscape was classified and the landscape composition, patch characteristics and landscape heterogeneity etc. were analyzed. The results showed that the Cunninghamia lanceolate forest, Pinus massoniana forest, Pinus elliottii forest, Schima superba forest and the non-forest land are the dominant landscape types in Minhou Baisha national forest farm. The landscape types are generally versatile and the heterogeneity level is relatively high. Moreover, as the median one of all species, Schima superba is scattered majorly in long and narrow patches with small area. Schima superba’s shape index and fractal dimension number are the largest and its patch shape is intricate and irregular. The 3D visualization simulation of forest landscape provides an intuitive and interactive platform to the research of landscape pattern.

Key words: forest landscape pattern, landscape index, visualization, 2nd-class survey

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.DOI:10.3724/SP.J.1047.2017.00281

WANG Lei,CHEN Chongcheng,TANG Liyu. Forest Landscape Pattern Analysis Using the Integration of Virtual Forest Environment and Landscape Index Calculation Model[J]. Journal of Geo-information Science, 2017, 19(2): 281-288.DOI:10.3724/SP.J.1047.2017.00281

图/表 8

表1

景观指数的计算公式"

景观格局分析	景观指数	计算公式
景观组成结构	斑块类型面积 CA/hm²	$CA = ∑ j = 1 n a ij / 10000$
	斑块面积百分比PLAND	$PLAND = p i = ∑ j = 1 n a ij / A × 100$
	斑块类型个数NP	$NP = n i$
	优势度D	$D i = ∑ j = 1 n a ij / A + ∑ j = 1 n n ij N × 100 / 2$
景观斑块特征	平均斑块面积 MPA	$MPA = ∑ j = 1 n a ij 10000 / n i$
	最大斑块指数 LPI	$LPI = max (a ij) j = 1 n / A × 100$
	面积加权的平均形状指数AWMSI	$AWMSI = ∑ j = 1 n 0.25 p ij / a ij) ? (a ij / ∑ j = 1 n a ij)$
	面积加权的平均分形维数AWFRAC	$AWFRAC = ∑ j = 1 n (2 ln (0.25 p ij) / ln (a ij)) ? (a ij / ∑ j = 1 n a ij)$
景观异质性	斑块密度PD/ （块/100hm²）	$PD = n i A × 10000 × 100$
	边缘密度ED/ （m/hm²）	$ED = ∑ k = 1 m e ik / A × 10000$
	Shannon′s多样性指数SHDI	$SHDI = - ∑ i = 1 m p i × ln p i$
	Shannon′s均匀度指数SHEI	$SHEI = - ∑ i = 1 m p i × ln p i / lnm$
景观空间分布	平均最小距离 MNN/m	$MNN = ∑ j = 1 n h ij / n i$
景观空间分布	聚集度CONT	$CONT = 1 + ∑ i = 1 m ∑ j = 1 m g ij ln g ij 2 lnm × 100$

表1

图1

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图3

图4

表2

图5

图6

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指标	杉木林	马尾松林	湿地松林	木荷林	樟树林	桉树林	毛竹林	果树林	非林地
斑块数	393	185	133	165	20	35	17	50	270
斑块数百分比/%	30.99	14.59	10.49	13.01	1.58	2.76	1.34	3.95	21.29
斑块类型面积/hm²	1790.13	778.84	715.41	390.04	60.82	155.53	37.12	132.11	950.07
斑块类型面积比/%	35.73	15.55	14.28	7.79	1.21	3.10	0.74	2.64	18.96
优势度/%	33.36	15.07	12.38	10.40	1.40	2.93	1.04	3.29	20.13
平均斑块面积/hm²	4.56	4.21	5.38	2.36	3.04	4.44	2.18	2.64	3.52
斑块面积标准差	3.37	3.35	3.89	2.27	3.62	3.18	1.93	2.42	8.54
斑块面积变动系数	74.07	79.63	72.25	95.88	119.08	71.65	88.32	91.60	242.76
最大斑块指数	0.35	0.32	0.40	0.34	0.33	0.28	0.13	0.23	2.25
面积加权的平均形状指数	1.48	1.47	1.41	4.37	1.37	1.41	1.52	1.38	2.01
面积加权的平均分形维数	1.07	1.06	1.06	1.22	1.06	1.06	1.08	1.06	1.11
斑块密度	7.84	3.69	2.65	3.29	0.40	0.70	0.34	1.00	5.39
边缘密度	89.92	40.50	32.15	82.44	3.31	7.65	2.69	8.17	55.49
平均最小距离	114.57	224.65	324.36	50.17	1270.31	502.01	790.37	649.4	112.86
聚集度	86.27	82.65	86.47	51.85	81.29	89.19	72.77	81.53	79.70

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

Forest Landscape Pattern Analysis Using the Integration of Virtual Forest Environment and Landscape Index Calculation Model

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