测绘通报 ›› 2020, Vol. 0 ›› Issue (3): 56-63.doi: 10.13474/j.cnki.11-2246.2020.0078

• 学术研究 • 上一篇    下一篇

尺度变化对城市生态环境与人类活动关系的影响研究

程朋根1,2, 岳琛1,2, 危小建1, 周江文1   

  1. 1. 东华理工大学测绘工程学院, 江西 南昌 330013;
    2. 广西空间信息与测绘重点 实验室, 广西 桂林 541004
  • 收稿日期:2019-12-02 发布日期:2020-04-09
  • 通讯作者: 岳琛。E-mail:872438008@qq.com E-mail:872438008@qq.com
  • 作者简介:程朋根(1964-),男,博士,教授,主要研究方向为三维地理信息系统理论与应用、遥感环境监测理论与应用。E-mail:pgcheng1964@163.com
  • 基金资助:
    国家自然科学基金(41861052;41861062);国家重点研发计划(2017YFB0503704);东华理工大学研究生创新基金(DHYC-201921);广西空间信息与测绘重点实验室基金项目(16-380-25-29)

Study on the influence of scale change on the relationship between urban ecological environment and human activities

CHENG Penggen1,2, YUE Chen1,2, WEI Xiaojian1, ZHOU Jiangwen1   

  1. 1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    2. Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China
  • Received:2019-12-02 Published:2020-04-09

摘要: 针对空间尺度对城市生态环境与人类活动影响的研究,以南昌市为研究区,划分了300×300、500×500、700×700共3种格网尺度。使用遥感生态指数RSEI(目标向量)量化城市生态环境质量,结合POI点、微博签到点与道路网数据(特征向量),利用随机森林回归模型分析不同尺度下两者之间的拟合效果。结果表明:①3种尺度下RSEI与POI点、微博签到点与道路网均呈现较强的负相关性;且负相关性最优的为RSEI和微博签到点数据,最差的为RSEI和道路网数据。②300×300尺度下随机森林回归模型的拟合效果最好。随着尺度的变大,拟合的效果会越来越差。③无论尺度如何变化,利用随机森林回归拟合的标准化残差ε均呈正态分布;且随着尺度的变大,ε值空间分布的随机性也逐渐增大。随机森林回归模型为度量尺度对城市生态环境与人类活动的关系研究提供了有效的途径,也为城市生态文明建设提供了科学的依据和参考。

关键词: 空间尺度, 遥感生态指数, 城市生态环境, 随机森林回归, 南昌

Abstract: In view of the research on the impact of spatial scale on urban ecological environment and human activities, this paper takes Nanchang City as the research area and divides three grid scales of 300×300, 500×500 and 700×700. Using the remote sensing ecological index RSEI (target vector) to quantify the urban ecological environment quality, combined with POI points, Weibo check-in points and road network data (feature vectors), the random forest regression model is used to analyze the fitting effect between the two scales. The results show that: ①RSEI and POI points, Weibo check-in points and road network have strong negative correlation at three scales; and the negative correlation is RSEI and Weibo check-in point data, and the worst is RSEI and road network data. ②The random forest regression model at 300×300 scale has the best fitting effect. As the scale becomes larger, the effect of the fit will get worse. ③Regardless of the scale change, the standardized residuals fitted by random forest regression show a normal distribution; and as the scale becomes larger, the randomness of the standardized residuals space distribution also increases. The random forest regression model provides an effective way for the relationship between urban ecological environment and human activities, and provides a scientific basis and reference for urban ecological civilization construction.

Key words: spatial scale, RSEI, urban ecological environment, random forest regression, Nanchang

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