文献类型：期刊文献

中文题名：乡村景观格局热效应研究

英文题名：Thermal Effect of Rural Landscape Patterns

作者：史久西[1,2] 邓劲松[3] 王小明[2] 骆成方[4] 裘鑫灿[4]

第一作者：史久西

机构：[1]南京林业大学;[2]中国林业科学研究院亚热带林业研究所;[3]浙江大学;[4]浙江省绍兴县林业局

年份：2009

卷号：22

期号：6

起止页码：792-800

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：国家“十一五”林业科技支撑计划专题项目“新农村绿色家园建设技术试验示范”(2006BAD03A00-6);浙江省科技厅重大项目“环杭州湾林业景观生态体系构建技术研究与示范”(2004C12030)

语种：中文

中文关键词：乡村景观格局;景观指数;热效应;村庄绿化

外文关键词：rural landscape patterns; landscape patterns index; thermal effect; village greening

分类号：S731.1

摘要：利用Quickbird和ETM影像对浙江省绍兴县北部平原220 km2区域内50个村庄景观格局热效应进行了研究。通过环境亮温与建筑、水体、草地、林地、绿地(草地+林地)5种地类斑块共45个景观指数间的数量关系分析,结果表明:各景观指数与环境亮温间具有良好的线性关系;众多景观指数可分为密度类指数、覆盖率类指数、形状指数、核心区规模指数、100 m缓冲区相关指数、其它指数6类,其中优势斑块和景观总体的密度类指数、覆盖率类指数是环境亮温的主要作用因子;有关建筑斑块及核心区景观总体规模的指数(建筑的覆盖率、块均面积、聚合度,核心区的总面积、总周长、总块均面积)与环境亮温为正相关关系,其它多为负相关,因此建成区规模较小、各地类以众多小斑块均匀分布、建筑覆盖率低且形状狭长的村庄更有助于环境降温。建立了4个亮温预测模型(Ra2>0.9),筛选出相应的亮温预测及调控因子组;在核心区,环境亮温的单因子拟合效果欠佳,景观格局结构指数的作用不能忽略,结构指数对亮温的作用贡献约占总量的25%。
The thermal effect of landscape patterns from 50 villages in northern plain of Shaoxing County, Zhejiang Province was analyzed based on 2002 Quickbird and ETM images data. In the core area （build-up area） of villages, 45 landscape patterns indices （LPI） of 5 patches （land-use types including building, water, grass plot, woodland and green area mixed by grassplot, woodland） and whole landscape were calculated, and their correlation to environment brightness temperature （EBT） were discussed. The result showed that there was a sound linear relationship between the LPI and BET; the LPI studied here could be classified into 6 groups, i.e. density index, coverage index, shape index, core area size, indices of 100 m wide buffer ring and others, of which the indices type of density, coverage aggregation of dominant patch or of whole landscape have more significant correlation with BET; the indices about building patch and core area size （ coverage, mean patch size and aggregation of building patches, area, perimeter and mean patch size of core area） and the shape indices of temperature-reducing patches had positive correlation with BET, others had negative correlation. So those villages, small size and even disperse in patches and narrow shape in buildings, were helpful small size in built-up area, for environment temperaturereducing. 4 empirical models were established （R^2 〉 0.9） referring to 4 groups of LPI for predicting and adjusting the EBT being selected. However, the models fitted with single landscape quantity structure index had low performance. It means that the contribution of landscape patterns indices to environment temperature, up to about 25% of total, can not be ignored in village buih-up area.