摘要
针对土地利用(LU)数据因空间尺度或产品来源的不同从而对生态系统服务价值(ESVs)估算产生影响的问题,该文采用当量因子法、升尺度算法与波动性指数等方法,研究了长三角地区ESVs对LU数据的空间尺度效应。结果表明:(1)随着尺度的增加,LU的空间细节逐渐不明显,相同土地利用类型呈现出聚合的现象,但总体的土地利用类型空间分布相似。(2)不同尺度的LU数据估算出的各种生态系统服务功能价值与ESVs各不相同。随着尺度的增加,不同LU产品估算的ESVs差异有所增大,最终差异百分比大约稳定在10%。(3)随着LU尺度的增加,ESVs与LU尺度符合对数关系,拟合度R~2大于0.9。研究结果为选取LU估算ESVs可靠性方面提供参考,对有效评估ESVs潜在的经济与环境效益具有重要意义。
Aiming at the impact of land use(LU) data on the estimation of ecosystem service values(ESVs) due to different spatial scales or product sources,the effect of spatial scale of ESVs on LU data in the Yangtze River Delta region was studied by using equivalent factor method,scale-up algorithm and volatility index in this paper.The results showed that:(1)With the increase of scale,the spatial details of LU became gradually less obvious,and the same land use types converged,but the overall spatial distribution of land use types was similar.(2)The functional values of ecosystem services and ESVs estimated by LU of different products or the same products with different scales were different.With the increase of scale,the difference of ESVs estimated by different LU increases,and the final difference percentage was about 10%.(3)With the increase of LU scale,ESVs and LU scale conform to logarithmic relationship,and the fitting degree R~2 was greater than 0.9.The research results provided a reference for selecting LU to estimate the reliability of ESVs,and were of great significance for effectively evaluating the potential economic and environmental benefits of ESVs.
作者
张学鹏
张凤娇
勾鹏
黄莹双
戴俊英
ZHANG Xuepeng;ZHANG Fengjiao;GOU Peng;HUANG Yingshuang;DAI Junying(Research Center of Big Data Technology,Nanhu Laboratory,Jiaxing,Zhejiang 314000,China;Beijing Big Data Advanced Technology Institute,Beijing 100871,China;College of Geoscience and Surveying Engineering,China University of Mining&Technology,Beijing 100830,China;The 36th Research Institute of China Electronic Technology Group,Jiaxing,Zhejiang 314000,China)
出处
《测绘科学》
CSCD
北大核心
2023年第4期251-257,276,共8页
Science of Surveying and Mapping
基金
北京市自然科学基金项目(8192037)
国家自然科学基金项目(41701391)。
