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应用生态学报 ›› 2025, Vol. 36 ›› Issue (12): 3799-3809.doi: 10.13287/j.1001-9332.202512.023

• 研究论文 • 上一篇    下一篇

基于物候相机监测的城郊植被物候特征:以南京市二球悬铃木为例

田昊翔1, 曹畅1*, 时冬头2, 徐家平3, 肖薇1, 宗鹏程3   

  1. 1南京信息工程大学气候系统预测与变化应对全国重点实验室大气环境中心, 南京 210044;
    2南京市高淳区气象局, 南京 211300;
    3江苏省气候中心, 金坛国家气候观象台, 南京 210009
  • 收稿日期:2025-01-25 修回日期:2025-10-02 出版日期:2025-12-18 发布日期:2026-07-18
  • 通讯作者: *E-mail: chang.cao@nuist.edu.cn
  • 作者简介:田昊翔, 男, 1999年生, 硕士。主要从事城市气象研究。E-mail: cryslining@126.com
  • 基金资助:
    中国气象局生态系统碳源汇重点开放实验室重点项目(ECSS-CMA202302)、中国气象局气候资源经济转化重点开放实验室开放课题(2025009K)、国家自然科学基金项目(42005143)、江苏省自然科学基金项目(BK20180796)、江苏省杰出青年基金项目(BK20220055)、江苏省“333人才”领军型人才团队(BRA2022023)和中国气象局气候变化专题项目(QBZ202404)

Urban and suburban vegetation phenology feature based on phenology camera: A case study of Platanus acerifolia in Nanjing City, China

TIAN Haoxiang1, CAO Chang1*, SHI Dongtou2, XU Jiaping3, XIAO Wei1, ZONG Pengcheng3   

  1. 1Yale-NUIST Center on Atmospheric Environment, State Key Laboratory of Climate System Prediction and Risk Management, Nanjing University of Information Science and Technology, Nanjing 210044, China;
    2Gaochun Meteorology Bureau, Nanjing 211300, China;
    3Jintan National Climate Observatory, Jiangsu Climate Center, Nanjing 210009, China
  • Received:2025-01-25 Revised:2025-10-02 Online:2025-12-18 Published:2026-07-18

摘要: 针对卫星遥感在城市和城郊异质景观中物候监测的局限性,本研究以二球悬铃木为对象,基于2020年南京城市和城郊物候相机观测站点的图像数据,提出了一种新的基于像素的感兴趣区域(ROI)内目标植被的提取方法,通过计算相对绿度指数(GCC),采用 Klosterman 曲线拟合与 Gu 物候参数提取法,获取返青期、成熟期、衰老期和休眠期4个关键物候期,分析城市和城郊二球悬铃木的物候特征,并在日尺度上探讨了气象因素对城市和城郊二球悬铃木物候期的影响。结果表明: 本研究提出的基于像素的ROI内目标植被的提取方法,可显著降低建筑、林下植被等干扰物的影响。在物候期的识别上,本研究结果与卫星遥感结果具有良好的一致性,比传统基于像素的ROI整体平均的方法更为稳健合理。城市与城郊二球悬铃木的物候期差异显著,2020年南京城市二球悬铃木的返青期比城郊提前5.5 d,而衰老期延迟9.1 d。气温和短波辐射是影响研究区城市和城郊二球悬铃木物候变化的主要因素,而降水的影响不显著。本研究建立的基于像素的ROI内目标植被提取技术可有效提升城市景观物候观测精度,为城市化对植被物候影响的研究提供方法支撑。

关键词: 城市物候, 物候相机, 像素, 气象因素, 二球悬铃木

Abstract: To address the limitations of satellite remote sensing in monitoring vegetation phenology across heterogeneous urban and suburban landscapes, with Platanus acerifolia as research object, we proposed a novel pixel-based method for extracting target vegetation within region of interest (ROI) based on images from phenology camera observation sites in urban and suburban Nanjing during the year of 2020. By calculating the green chromatic coordinate (GCC) index, we employed Klosterman curve fitting alongside the Gu phenological parameter extraction method to derive four key phenological phases, i.e., greenup, maturity, senescence, and dormancy, and analyzed urban and suburban phenology feature of P. acerifolia. We analyzed the impact of meteorological factors on phenological phase of urban and suburban P. acerifolia at the daily scale. The results showed that the pixel-based target vegetation extraction method within ROI proposed here significantly reduced interference from buildings and understory vegetation. The identified phenological phase showed strong consistency with satellite remote sensing results, being more robust and reasonable than traditional pixel-averaged ROI method. There was a significant difference of phenological phases of P. acerifolia between urban and suburban sites. In 2020, the greenup of urban P. acerifolia occurred 5.5 days earlier than that of suburban areas, while senescence was delayed by 9.1 days. Temperature and shortwave radiation were the main factors affecting the phenological changes of P. acerifolia in the urban and suburban areas, while the impact of precipitation was not significant. The pixel-based target vegetation extraction technique developed in this study could enhance the accuracy of urban landscape phenological observation and provide methodological support for research on the impact of urbanization on vegetation phenology.

Key words: urban phenology, phenology camera, pixel, meteorological factor, Platanus acerifolia