景观生态学原理在城市土地利用分类中的应用

Applying landscape ecological concepts in urban land use classification

根据城市相同土地利用类型具有相似景观格局特征的原理,探讨了融合景观格局特征指数和遥感技术的城市土地利用信息提取的新方法。以北京市五环内建城区为例,研究表明,在斑块类型水平和景观水平上,居住用地和非居住用地内景观斑块的大小、形状、边缘特征、空间连接度、核心区面积特征、多样性、均匀性等特征都有极显著的差异。进一步融合TM遥感影像和这些景观格局特征指数,提取了居民用地和非居民用地类型,总分类精度是79.7%,Kappa系数达到59.8%。研究揭示,景观生态学原理的引入,为传统的遥感技术应用提供了新的思路,在格局复杂的城市土地利用信息提取中有很大的应用发展潜力。

Generally,land uses are the ways in which lands are used by human activities.Especially in cities with dense population,land use is the direct results of various living requirements by the people.Therefore,urban land use is a very important indicator that can be used to measure the development of urbanization and their impacts on ecosystems.Hence,accurate extraction of urban land uses is critical for urban planning,land management and environmental protection.It has been proved that remote sensing technique is most efficient to extract land covers with high accuracy since different land covers have the specific physical properties which can be discriminated easily by the spectral bands of remote sensing data.However,considering the difference in land use and land cover,it is still a big challenge to extract urban land uses directly from remote sensing data with fast and satisfied accuracy because every land use is usually composed of different land covers.This study developed a new approach on urban land use classification by introducing landscape ecology theory into the application of traditional remote sensing techniques.According to the landscape ecology concepts,the landscape patterns within the same land use types are similar.In landscape ecology,many landscape metrics have been developed to measure landscape patterns on different spatial levels,such as patch level,class level and landscape level.On each spatial level,the landscape patterns have their own characteristics.Thus,some significant landscape metrics might be found to characterize the specific landscape patterns of different land uses,which can be identified as the important variables to discriminate different land uses.Then,by integrating these variables and traditional remote sensing approach,urban land uses were classified.The study area is the city center of Beijing,where dense population is living and amount of residential land use developed intensively.Considering the characteristics of landscape pattern of the study site,residential and non-residential land uses are proposed to be extracted by using the medium-resolution Landsat data.Firstly,the land covers mainly including built ups and non-built ups（vegetation） were extracted directly from the remote sensed data by the traditional approach based on the spectral response features.Then,the land parcels that are the basic land use units extracted mainly by the road segments as the boundaries.Totally,by the significant test,there are 27 significant landscape metrics identified to discriminate residential and non-residential land uses.On the class level,there are 12 significant landscape metrics measuring the distribution patterns of built ups within different land uses,while on the landscape level there are 15 significant landscape metrics measuring the total landscape patterns.Based on these significant landscape metrics,the Fisher linear discrimination model was developed to discriminate different land uses.By applying this model,the residential land non-residential land uses within the 5th ring of Beijing were finally classified.The total classification accuracy was 79.7%,and the statistical Kappa coefficient was 59.8%.This study developed a new approach for urban land use classification,which enriches the application techniques of remote sensing.The approach on land use classification could be potentially applied to other urban area.