JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2024, Vol. 59 ›› Issue (11): 110-125.doi: 10.6040/j.issn.1671-9352.0.2022.553

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A coupling study of habitat quality and urbanization in the lower Yellow River

Jinxin SUN1(),Mei HAN1,*(),Fanbiao KONG1,Fan WEI2   

  1. 1. College of Geography and Environment, Shandong Normal University, Jinan 250358, Shandong, China
    2. School of Ecology, Resources and Environment, Dezhou University, Dezhou 253023, Shandong, China
  • Received:2022-10-20 Online:2024-11-20 Published:2024-11-29
  • Contact: Mei HAN E-mail:sunjinxineeeee@163.com;hanmei568568@126.com

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Abstract:

In the process of urbanization, natural habitats have been degraded to different degrees by human disturbance, which hinders high-quality regional development. The coupled and coordinated relationship between habitat quality and urbanization development needed to be reconciled. In this paper, we used the InVEST model to analyze the spatial and temporal evolution characteristics of habitat quality in the lower Yellow River from 2000 to 2020, and used the light index to characterize the urbanization level, and evaluated the interactive coupling relationship between habitat quality and urbanization with the help of coupled coordination model and decoupling model. The results showed that (1) From 2000 to 2020, the overall level of habitat quality in the lower Yellow River was poor but gradually tended to improve. The areas with higher habitat quality were mainly concentrated in coastal and lakeside wetlands, southwestern and eastern hills and mountains, showing a general trend of low in the middle and high at the edges, with a more stable distribution pattern. (2) The overall level of urbanization in the lower Yellow River has improved and regional differences have been enhanced, gradually developing into a pattern of urbanization level distribution with Ji-Zi and Zheng-Xin urban areas as important growth poles. (3) The coupling and coordination stage of habitat quality and urbanization in the lower Yellow River belonged to the basic coordination stage. The number of counties transformed to the direction of decoupling decreased. The decoupling types are mainly strong negative decoupling and weak decoupling two negative decoupling types, and the proportion of negative decoupling types gradually decreased. The coupling coordination degree of the two systems deepened, the decoupling degree decreased, and the overall development in the direction of coordination.

Key words: habitat quality, InVEST model, urbanization, coupled coordination, the lower Yellow River

CLC Number: 

  • X321

Fig.1

Schematic diagram of the scope of the study area"

Table 1

Data sources"

数据类型数据产品分辨率数据来源链接
土地利用数据—1 km中国科学院资源环境科学与数据中心https://www.resdc.cn/
夜间灯光数据[34]—1 km国家青藏高原科学数据中心http://data.tpdc.ac.cn
NDVI数据MODIS(MOD09A1)500 mUSGShttps://www.usgs.gov
NPP数据MODI(MOD17A2H)500 mUSGShttps://www.usgs.gov

Fig.2

Land use classification in the lower Yellow River"

Table 2

Maximum impact distance, weights and spatial recession types of threat sources"

威胁源最大影响距离/km权重空间衰退类型
耕地30.5线性
城镇用地101.0指数
农村居民用地50.7指数
其他建筑用地70.9指数
未利用地10.3线性

Table 3

Habitat suitability of different land use types and their sensitivity to threat sources"

土地利用类型生境适宜性威胁因子
耕地城镇用地农村居民用地其他建筑用地未利用地
耕地0.401.00.50.60.2
林地1.00.81.00.70.80.4
草地0.80.60.80.60.70.6
水体湿地0.90.70.90.70.80.3
未利用地0.00.50.60.60.60.0

Table 4

Criteria for dividing coupling types"

耦合度C耦合阶段
0≤C≤0.3低水平耦合
0.3 < C≤0.6拮抗阶段
0.6 < C≤0.8磨合阶段
0.8<C≤1高水平耦合

Table 5

Criteria for dividing the types of coupling coordination"

耦合协调度D耦合协调度阶段
0≤D≤0.2极度失调
0.2 < D≤0.4中度失调
0.4 < D≤0.6基本协调
0.6 < D≤0.8中度协调
0.8 < D≤1高度协调

Table 6

Classification criteria for decoupling types"

类型ΔEΔUε类型ΔEΔUε
扩张性解耦++ε≥1.2衰退解耦--ε≥1.2
扩张性耦合++0.8≤ε<1.2衰退耦合--0.8≤ε<1.2
弱解耦++0 < ε≤0.8衰退耦合--0 < ε≤0.8
强解耦+-ε≤0强负解耦-+ε≤0

Fig.3

Spatial distribution of habitat quality levels in the lower Yellow River from 2000 to 2020"

Table 7

Area and proportion of each class of habitat quality in the lower Yellow River from 2000 to 2020"

等级2000年2010年2020年
面积/km2比例/%面积/km2比例/%面积/km2比例/%
差36 07726.6235 88826.4830 41522.44
较差83 70661.7783 33961.4987 80064.79
中9 5697.0610 3157.617 8135.77
良好3 2162.372 8882.134 6083.40
好2 9542.183 0922.284 8863.61

Fig.4

Habitat quality class shift in the lower Yellow River from 2000 to 2020"

Table 8

Area proportion of habitat quality class transfer in the lower Yellow River from 2000 to 2020 单位: %"

2000年2010年2010年2020年
差较差中良好好差较差中良好好
差21.584.900.080.010.05差10.5913.830.840.101.12
较差4.6655.980.990.010.13较差10.8747.441.910.720.55
中0.090.466.080.420.00中0.702.712.811.390.01
良好0.050.120.451.670.08良好0.120.450.201.160.20
好0.110.040.000.022.02好0.170.350.000.021.74

Fig.5

Distribution of cold hot spots of habitat quality in the lower Yellow River counties from 2000 to 2020"

Fig.6

Map of the distribution of cold and hot spots of the lighting index in the lower Yellow River counties from 2000 to 2020"

Table 9

Extreme values, means and standard deviations of coupling degree and coupling coordination in the lower Yellow River"

数值类型耦合度C耦合协调度D
2000年2010年2020年2000年2010年2020年
极大值0.9990.9990.9990.6730.6560.749
极小值0.3050.2030.2060.2220.1940.278
均值0.8710.8450.8260.4260.4240.484
标准差0.1390.1510.1480.0970.0940.086

Fig.7

Schematic diagram of the distribution of coupled coordination types between habitat quality and urbanization level in the lower Yellow River counties from 2000 to 2020"

Fig.8

Schematic diagram of the distribution of decoupling types and urbanization types in the lower Yellow River counties from 2000 to 2020"

Table 10

Percentage of the number of coupled coordination and decoupling types of counties and districts in the lower Yellow River urban hotspot"

城市热点区耦合协调类型占比/%解耦类型占比/%
类型2000年2010年2020年类型2000—2010年2010—2020年
济-淄城市群中度失调9.0914.290.00强负解耦92.8657.14
基本协调72.7378.5754.55弱解耦7.1428.57
中度协调18.187.1445.45扩张解耦0.0014.29
郑-新城市群中度失调13.339.524.17强负解耦50.0070.83
基本协调63.3380.9575.00弱解耦50.0020.83
中度协调23.339.5220.83扩张解耦0.008.33
黄河下游极度失调0.000.670.00强负解耦63.0934.23
中度失调46.9846.9812.08弱解耦34.9044.30
基本协调46.3147.6577.18扩张耦合0.003.36
中度协调6.714.7010.74扩张解耦2.0118.12

Fig.9

Sensitivity analysis of InVEST model parameters"

Fig.10

Correlation analysis between remote sensing ecological index and InVEST results"

Fig.11

Correlation analysis of urbanization level results evaluated by remote sensing of nightlight and socio-economic data"

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