基于多时相遥感数据的老山景区地类信息提取及景观格局动态分析

doi:10.19741/j.issn.1673-4831.2019.0426

摘要/Abstract

摘要： 老山景区是南京市的生态屏障及生物多样性保护区，以森林为主体，生态区位极其重要。以研究该景区近17 a景观格局动态变化为目的，运用基于面向对象的模糊分类法和C5.0决策树分类法以及基于像元的最大似然法、人工神经网络法和支持向量机法对研究区2001、2005、2009、2013和2017年5期Landsat影像进行地类信息提取，并运用Fragstats 4.2软件提取多种景观格局指数，对老山景区2001-2017年景观格局动态进行对比分析。结果表明：基于面向对象的模糊分类法精度最高，分类总体精度为91.79%，Kappa系数为0.83。随着景区生态公园的建设与改革，景区内景观破碎化程度加深，2001-2017年斑块数量（NP）呈上升趋势，2017年景区NP达653块，斑块密度（PD）为5.928 1块·km^-2；2017年蔓延度指数（CONTAG）比2001年有所增加，达59.41%，优势斑块类型连通度提高；香农多样性指数（SHDI）上下窄幅波动，2009年达到最大值0.725 5。随着景区建设逐渐成熟，总体开发进程缓慢进入有序状态，老山景区逐步向均衡性、稳定性方向发展。

关键词: 森林资源, 地类信息提取, 面向对象, 景观格局, Landsat

Abstract: The Laoshan scenic area is an ecological barrier and biodiversity conservation area in Nanjing City. The dominant ecosystem in Laoshan is forest, its ecological position is extremely important. This study aims to analyze the dynamic changes of the landscape pattern in the scenic area for the past 17 years. Local land use information based on Landsat images from 2001, 2005, 2009, 2013 and 2017 was extracted, using the technical method of object-oriented fuzzy classification, C5.0 decision tree classification, pixel-based maximum likelihood, artificial neural network and support vector machine. In addition, Fragstats 4.2 software was used to extract multiple landscape pattern indexes, for the comparison of dynamic landscape pattern from 2001 to 2017. Results show that the object-oriented fuzzy classification method had the highest overall accuracy (91.79%) and Kappa coefficient was 0.83. With the continuous construction and reform, the degree of landscape fragmentation in Laoshan scenic area has deepened. From 2001 to 2017, the number of patches (NP) showed an increasing trend, and reached 653 in 2017, with the patch density of 5.928 1 blocks·km^-2. In 2017, contagion index (CONTAG) increased compared with that of 2001, reaching 59.41%, and the connectivity of dominant patch types has improved. The Shannon's diversity index (SHDI) value fluctuated in a narrow range, reaching a maximum of 0.725 5 in 2009. With the development of construction to a mature state, the overall development process slowly enters into an orderly state, and scenic area in Laoshan has gradually developed towards harmony and stability.

Key words: forest resource, land type information extraction, object-oriented, landscape pattern, Landsat

中图分类号:

S771.8

孙敏, 周春国, 邹长新, 张峥男, 刘冬. 基于多时相遥感数据的老山景区地类信息提取及景观格局动态分析[J]. 生态与农村环境学报, 2020, 36(2): 211-219.

SUN Min, ZHOU Chun-guo, ZOU Chang-xin, ZHANG Zheng-nan, LIU Dong. Land Type Information Extraction and Landscape Pattern Dynamic Analysis of Laoshan Scenic Area[J]. Journal of Ecology and Rural Environment, 2020, 36(2): 211-219.

参考文献

[1] 宋建波,武春友.城市化与生态环境协调发展评价研究:以长江三角洲城市群为例[J].中国软科学,2010(2):78-87.[SONG Jian-bo,WU Chun-you.The Study on Evaluation of Coordinated Development Between Urbanization and Ecological Environment Among City Cluster in the Yangtze River Delta[J].China Soft Science,2010(2):78-87.]
[2] 罗仙仙,亢新刚.森林资源综合监测研究综述[J].浙江林学院学报,2008,25(6):803-809.[LUO Xian-xian,KANG Xin-gang.Progress in Research on the Comprehensive Monitoring of Forest Resources[J].Journal of Zhejiang Forestry College,2008,25(6):803-809.]
[3] 吴迪,李冰,杨爱玲.基于Landsat长时间序列数据估算树高和生物量[J].测绘工程,2017,26(6):1-5.[WU Di,LI Bing,YANG Ai-ling.Estimation of Tree Height and Biomass Based on Long Time Series Data of Landsat[J].Engineering of Surveying and Mapping,2017,26(6):1-5.]
[4] KUMAR P,GUPTA D K,MISHRA V N,et al.Comparison of Support Vector Machine,Artificial Neural Network,and Spectral Angle Mapper Algorithms for Crop Classification Using LISS IV Data[J].International Journal of Remote Sensing,2015,36(6):1604-1617.
[5] WALKER J S,BRIGGS J M.An Object Oriented Classification of an Arid Urban Forest With True Color Aerial Photography[C]//Proceedings of the 3rd International Symposium of Remote Sensing and Data Fusion Over Urban Areas,Tempe,USA:Institute of Electrical and Electronics Engineers,2005:66-85.
[6] MALLINIS G,KOUTSIAS N,TSAKIRI-STRATI M,et al.Object-based Classification Using Quickbird Imagery for Delineating Forest Vegetation Polygons in a Mediterranean Test Site[J].ISPRS Journal of Photogrammetry and Remote Sensing,2008,63(2):237-250.
[7] MALANDRA F,VITALI A,URBINATI C,et al.70 Years of Land Use/Land Cover Changes in the Apennines (Italy):A Meta-Analysis[J].Forests,2018,9(9):551.
[8] MIYAMOTO A,SANO M.The Influence of Forest Management on Landscape Structure in the Cool-temperate Forest Region of Central Japan[J].Landscape and Urban Planning,2008,86(3/4):248-256.
[9] FENG S R,GUO L,LI D D,et al.Spatial Patterns of Landscape Change in the Three Rivers Headwaters Region of China,1987-2015[J].Acta Ecologica Sinica,2018,38(2):76-80.
[10] 黄致远,程翔,杨开红,等.南京老山森林公园植被资源的利用与保护[J].植物资源与环境,1993,2(2):21-24.[HUANG Zhi-yuan,CHENG Xiang,YANG Kai-hong,et al.Utilization and Conservation of Vegetation Resources in Nanjing Lao-Shan Mountain Forest Park[J].Journal of Plant Resources and Environment,1993,2(2):21-24.]
[11] HE X,BO Y,DU J,et al.Landscape Pattern Analysis Based on GIS Technology and Index Analysis[J].Cluster Computing,2019,22(Suppl.3):5749-5762.
[12] LU L,LI X,CHENG G D.Landscape Evolution in the Middle Heihe River Basin of North-West China During the Last Decade[J].Journal of Arid Environments,2003,53(3):395-408.
[13] 高玉蓉,许红卫,丁晓东.基于C5.0的钱塘江流域地区土地利用/覆被信息提取研究[J].生态科学,2012,31(5):481-487.[GAO Yu-rong,XU Hong-wei,DING Xiao-dong.Extraction of Land Use/Cover Information Based on C5.0 Algorithm in Qiantang River Drainage Area[J].Ecological Science,2012,31(5):481-487.]
[14] 王增林,朱大明.基于遥感影像的最大似然分类算法的探讨[J].河南科学,2010,28(11):458-461.[WANG Zeng-lin,ZHU Da-ming.A Study of Maximum Likelihood Classification Algorithm Based on Remote Sensing Image[J].Henan Science,2010,28(11):458-461.]
[15] 修丽娜,刘湘南.人工神经网络遥感分类方法研究现状及发展趋势探析[J].遥感技术与应用,2003,18(5):339-345.[XIU Li-na,LIU Xiang-nan.Current Status and Future Direction of the Study on Artificial Neural Network Classification Processing in Remote Sensing[J].Remote Sensing Technology and Application,2003,18(5):339-345.]
[16] 刘颖.基于半监督集成支持向量机的土地覆盖遥感分类方法研究[D].长春:中国科学院研究生院(东北地理与农业生态研究所),2013.[LIU Ying.The Study of Semi-Supervised Ensembled Support Vector Machines for Land Cover Classification[D].Changchun:Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,2013.]
[17] 郎文婧,李效顺,卞正富,等.徐州市区土地利用格局变化分析及其空间扩张模拟[J].生态与农村环境学报,2017,33(7):592-599.[LANG Wen-jing,LI Xiao-shun,BIAN Zheng-fu,et al.Analysis of Changes in Land Use Pattern in Xuzhou City and Simulation of Its Spatial Expansion[J].Journal of Ecology and Rural Environment,2017,33(7):592-599.]
[18] 张明明,张黎俊,粟海军,等.草海国家级自然保护区景观格局变化与景观发展强度研究[J].生态与农村环境学报,2019,35(3):300-306.[ZHANG Ming-ming,ZHANG Li-jun,SU Hai-jun,et al.Study on the Landscape Pattern Changes and the Landscape Development Intensity of Caohai National Nature Reserve,Guizhou[J].Journal of Ecology and Rural Environment,2019,35(3):300-306.]
[19] 陈雅如,肖文发,滕明君,等.三峡库区景观格局粒度效应及其对土地利用变化过程的响应[J].自然资源学报,2018,33(4):588-599.[CHEN Ya-ru,XIAO Wen-fa,TENG Ming-jun,et al.Grain Size Effect of Landscape Pattern and Its Response to Land Use Change in the Three Gorges Reservoir Area[J].Journal of Natural Resources,2018,33(4):588-599.]
[20] 王美玲,张继超,王舶鉴,等.长白山区森林景观格局动态[J].生态学杂志,2017,36(11):3138-3147.[WANG Mei-ling,ZHANG Ji-chao,WANG Bo-jian,et al.Dynamics of Forest Landscape Pattern in Changbai Mountain[J].Chinese Journal of Ecology,2017,36(11):3138-3147.]
[21] 耿莎,石云.黄土丘陵区小流域景观格局与生态恢复措施和地形因子耦合关系研究[J].生态与农村环境学报,2015,31(2):197-203.[GENG Sha,SHI Yun.Coupling Relationships of Terrain Factors With Landscape Pattern and Ecological Restoration Measures in Small Watershed in Loess Hilly-Gully Region[J].Journal of Ecology and Rural Environment,2015,31(2):197-203.]