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林业科学 ›› 2020, Vol. 56 ›› Issue (3): 61-72.doi: 10.11707/j.1001-7488.20200307

• 论文与研究报告 • 上一篇    下一篇

我国4个典型城市近30年绿色空间时空演变规律

金佳莉,王成*,贾宝全   

  1. 中国林业科学研究院林业研究所 国家林业和草原局林木培育重点实验室 国家林业和草原局城市森林研究中心 北京 100091
  • 收稿日期:2018-05-04 出版日期:2020-03-25 发布日期:2020-04-08
  • 通讯作者: 王成
  • 基金资助:
    中央级公益性科研院所基本科研业务费专项(CAFYBB2019SY004);林业公益性行业科研专项经费项目(201404301)

Spatio-Temporal Patterns of Evolution Urban Greenspace during the Last Three Decades in Four Typical Cities of China

Jiali Jin,Cheng Wang*,Baoquan Jia   

  1. Urban Forest Research Centre, National Forestry and Grassland Administration Key Laboratory of Tree Breeding and Cultivation, National Forestry and Grassland Administration Research Institute of Forestry, CAF Beijing 100091
  • Received:2018-05-04 Online:2020-03-25 Published:2020-04-08
  • Contact: Cheng Wang

摘要:

目的: 以长沙、大连、南昌和深圳为例,探究城市绿色空间格局近30年来的时空演变规律及主要影响因素,为完善城市景观生态学的相关理论和模型提供数据支持,为城市绿色空间管理提升和政策调整提供参考依据。方法: 以30 m分辨率的Landsat TM/ETM+合成影像为数据源,运用NDVI阈值将绿色空间分为4种类型,利用景观指数量化绿色空间格局特征,并引入距离归一化指数(NDI)进行城乡梯度分析,使用Mann-Kendall趋势检测分别计算绿色空间格局在时间和城乡梯度上的单调变化趋势,运用时间动态弯曲法(DTW)探究不同城市绿色空间格局时空变化轨迹的差异性,采用最大信息非参数勘探法(MINE)对影响绿色空间格局变化的主要因素进行相关性分析。结果: 1985—2011年,长沙、大连和深圳高密度植被面积比例平均增加0.26%,斑块面积平均增加0.11 hm2,而中密度植被面积比例平均下降0.40%;中密度植被平均斑块面积在南昌和深圳均呈上升趋势,分别增加0.15和0.04 hm2,而在长沙和大连则分别减少0.01和0.08 hm2;低密度植被面积比例和平均斑块面积在长沙和南昌均呈增加趋势,其面积比例分别增加0.12%和0.23%,平均斑块面积分别增加0.04和0.01 hm2,而在大连和深圳则均呈减少趋势,低密度植被面积比例分别减少0.22%和0.63%,平均斑块面积分别减少0.04和0.06 hm2;高密度植被面积比例在长沙和南昌呈"∩"型轨迹;低密度植被面积比例在长沙和深圳呈单调下降轨迹,而在大连和南昌呈"∪"型轨迹;绿色空间格局的时空变化与城市居民人均年收入、人均国民生产总值、城市人口比例和城市市区面积比例之间有极强的非线性相关。结论: 1985—2011年,长沙、大连和深圳高密度植被比例增加,其斑块空间分布更集中,而中密度植被则相反;所选城市中,内陆城市的低密度植被比例增加,破碎度减少,而沿海城市则相反;绿色空间的城乡梯度轨迹主要呈3种规律,一是抛物线"∩/∪"型,二是平稳"—"型,三是递增或递减型;绿色空间在城市中心或城郊区域有显著的大幅变化趋势。

关键词: 城市绿色空间, 景观格局, 城乡梯度, 时空变化

Abstract:

Objective: Changsha, Dalian, Nanchang and Shenzhen were selected to detect the spatio-temporal patterns of greenspace changes and main impact factors.This study aims to provide the new spatial data for the improvement of urban greenspace theories and models, and for the optimization of greenspace network. Method: Based on the time-series Landsat composites imagess, NDVI-thresholding technique was applied to reclassify greenspace into four categories and landscape indices were used to measure the characteristics of greenspace patterns. Temporal dynamics of greenspace was assessed using the Mann-Kendall trend test. Normalized distance index (NDI) was calculated to measure the urban-to-rural gradients. Dynamic time warping (DTW) was applied to detect the differences of long-term trends trajectories of landscape indices in four cities. Finally, maximum information-based non-parametric exploration method (MINE) was used to detect the pairwise relationships between the changes in greenspace patterns and main impact factors. Result: From 1985 to 2011, the percentage of dense vegetation in Changsha, Dalian, and Shenzhen had an average increase of 0.26% and the mean patch size of dense vegetation increased 0.11 hm2. The percentage of medium-dense vegetation in these three cities had an average decrease of 0.40%, while the mean patch size in Nanchang and Shenzhen increased 0.15, 0.04 hm2 respectively, however, Changsha and Dalian decreased 0.01, 0.08 hm2 respectively. The percentage and mean patch size of sparse vegetation in Changsha and Nanchang showed an increase trend. The percentage increased by 0.12% and 0.23%, the mean patch size increased by 0.04 and 0.01 hm2, respectively. To the contrary, the percentage of sparse vegetation in Dalian and Shenzhen decreased 0.22% and 0.63% while the mean patch size decreased 0.04 and 0.06 hm2.The urban-to-rural gradients of dense vegetation in Changsha and Nanchang had a ∩-shaped trajectory. Sparse vegetation in Changsha and Shenzhen had a monotonic decreasing trajectory, while Dalian, and Nanchang had a ∪-shaped trajectory. The changes in greenspace patterns had strong non-linear relationships with income, gross domestic product per person, proportion of urban population and proportion of city area. Conclusion: From 1985 to 2011, the dense vegetation in Changsha, Dalian and Shenzhen increased and the patches became more connected, contrasting to medium-dense vegetations. In the four selected cities, sparse vegetation increased in inland cities and the patterns became less fragmented, contrasting to the coastal cities. There are three trajectories of urban-to-rural gradients of greenspace, the first one is parabola-shaped trajectory ("∩or∪"), second is constant trajectory ("-"), third is monotonic increasing or decreasing trajectory. The greenspaces tended to have large changes in the city centers and suburb areas.

Key words: urban greenspace, landscape patterns, urban-to-rural gradient, spatio-temporal dynamics

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