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Remote Sensing for Natural Resources    2023, Vol. 35 Issue (4) : 244-254     DOI: 10.6046/zrzyyg.2022371
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Spatio-temporal evolution and influencing factors of ecological environment quality in the Changsha-Zhuzhou-Xiangtan urban agglomeration
LI Guangzhe1,2(), WANG Hao1,2(), CAO Yinxuan2, ZHANG Xiaoyu2, NING Xiaogang1,2
1. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2. Chinese Academy of Surveying & Mapping, Beijing 100036, China
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Abstract  

Accurately identifying the evolutionary trend and influencing factors of ecological environment quality in new urban agglomerations holds crucial significance for scientifically guiding urbanization and achieving sustainable development. Existing research on the spatio-temporal evolutionary characteristics of ecological environment quality in new urban agglomerations ignored the interactions of multiple factors on ecological environment quality. Based on the Google Earth Engine (GEE) platform, and long-time-series Landsat TM/OLI remote sensing images as the fundamental data source, this study delved into the spatio-temporal variations of ecological environment quality in the Changsha-Zhuzhou-Xiangtan urban agglomeration from 1990 to 2020 using methods including the remote sensing ecological index (RSEI), Sen’s slope estimator, and Mann-Kendall test. Moreover, the geographical detector was employed to quantitatively measure the effects of various factors on the urban agglomeration’s spatial heterogeneity. The results indicate that the Changsha-Zhuzhou-Xiangtan urban agglomeration exhibited generally high ecological environment quality, with a spatial distribution pattern of higher quality in marginal areas and lower quality in core areas. The average proportion of areas with ecological environment quality graded as “excellent” and “good” exceeds 60% in the urban agglomeration. The sustainable development strategy altered the urban sprawl in this urban agglomeration, leading to a decline followed by an increase in RSEI, with an inflection point in 2000. From 1990 to 2020, the ecological environment quality significantly deteriorated in central urban areas while improvement was observed in non-central urban areas. Physical and geographical conditions significantly influenced the ecological environment quality of the urban agglomeration in the early stages. With socio-economic progression, the influence of socio-economic factors like nighttime lighting on ecological environment quality gradually intensified, assuming a dominant role over time. Besides, the interactions among factors significantly enhanced the effects of individual factors on ecological environment quality. Before 2010, the interactions between human and natural factors exerted considerable influences on the ecological environment. After 2015, the interactions among human factors yielded more pronounced effects on ecological environment quality. These findings serve as a foundational guide for the integrated high-quality development of the Changsha-Zhuzhou-Xiangtan urban agglomeration and a reference for the advancement of other comparable urban agglomerations.
Keywords Changsha-Zhuzhou-Xiangtan urban agglomeration      Google Earth Engine      remote sensing ecological index      geographical detector      ecological environment quality     
ZTFLH:  TP79  
Issue Date: 21 December 2023
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Guangzhe LI
Hao WANG
Yinxuan CAO
Xiaoyu ZHANG
Xiaogang NING
Cite this article:   
Guangzhe LI,Hao WANG,Yinxuan CAO, et al. Spatio-temporal evolution and influencing factors of ecological environment quality in the Changsha-Zhuzhou-Xiangtan urban agglomeration[J]. Remote Sensing for Natural Resources, 2023, 35(4): 244-254.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2022371     OR     https://www.gtzyyg.com/EN/Y2023/V35/I4/244
Fig.1  Geographic location of the study area
数据名称 时间 分辨率 数据来源
影像数据 以1990年、1995年、2000年、2005年、2010年、2015年、2020年为中心年份(4—10月) 30 m Landsat5/8(Google Earth Engine)
土地利用数据 1990年、1995年、2000年、2005年、2010年、2015年、2020年 30 m CNLUCC (http://www.resdc.cn)
人口密度数据 1990年、1995年、2000年、2005年、2010年、2015年、2019年 1 km 中国人口空间分布公里网格数据集(http://www.resdc.cn)
夜间灯光数据 1990年、1995年、2000年、2005年、2010年、2015年、2020年 1 km 中国长时间序列逐年人造夜间灯光数据集(http://data.tpdc.ac.cn)
降水数据 1990年、1995年、2000年、2005年、2010年、2015年、2020年 1 km 中国1 km分辨率逐月降水量数据集(http://data.tpdc.ac.cn)
气温数据 1990年、1995年、2000年、2005年、2010年、2015年、2020年 1 km 中国1 km分辨率逐月平均气温数据集(http://data.tpdc.ac.cn)
DEM数据 — 30 m ASTER GDEM V2(http://www.gscloud.cn)
Tab.1  Data source and pre-processing
β 趋势 Z 显著性 趋势特征
β>0 提升 Z>1.96 显著 显著提升
0<Z≤1.96 不显著 不显著提升
β=0 无变化 Z — 无变化
β<0 退化 0<Z≤1.96 不显著 不显著退化
Z>1.96 显著 显著退化
Tab.2  Eco-environmental quality change level
交互关系 与单因子
q值相比		 单因子
较小值		 单因子
较大值		 两因子
之和
非线性减弱 交互作用q值 < < <
单因子非线性减弱 交互作用q值 > < <
双因子增强 交互作用q值 > > <
独立 交互作用q值 > > =
非线性增强 交互作用q值 > > >
Tab.3  Interaction q-value and single-factor q-value comparison table
Fig.2  Spatial distribution of ecological environment quality in Changsha-Zhuzhou-Xiangtan urban agglomeration
Fig.3  The proportion of area classified by ecological environment quality
Fig.4  Spatial distribution of ecological environment quality change trend in Changsha-Zhuzhou-Xiangtan urban agglomeration
Fig.5  Changes in ecological and environmental quality of counties and districts in Changsha-Zhuzhou-Xiangtan urban agglomeration from 1990 to 2020
Fig.6  Spatial distribution of factors affecting ecological environment quality in 1990
年份 土地利用(X1) 人口密度(X2) 夜间灯光(X3) 海拔(X4) 降水(X5) 温度(X6)
1990年 0.112 3*** 0.105 3*** 0.082 4*** 0.296 1*** 0.168 2*** 0.277 7***
[4] [5] [6] [1] [3] [2]
1995年 0.164 0*** 0.172 0*** 0.142 6*** 0.217 7*** 0.092 9*** 0.190 4***
[4] [3] [5] [1] [6] [2]
2000年 0.291 6*** 0.136 0*** 0.164 1*** 0.267 9*** 0.171 7*** 0.239 4***
[1] [6] [5] [2] [4] [3]
2005年 0.283 8*** 0.205 0*** 0.293 5*** 0.257 6*** 0.156 8*** 0.211 2***
[2] [5] [1] [3] [6] [4]
2010年 0.367 9*** 0.226 5*** 0.324 0 0.254 6 0.154 1 0.220 3
[1] [4] [2] [3] [6] [5]
2015年 0.292 3*** 0.179 3*** 0.335 1*** 0.191 1*** 0.138 7*** 0.169 8***
[2] [4] [1] [3] [6] [5]
2020年 0.339 7*** 0.142 6*** 0.274 4*** 0.176 1*** 0.088 8*** 0.162 8***
[1] [5] [2] [3] [6] [4]
Tab.4  Divergence and q-values of factor detection results
年份 交互因子
1990年 0.349 6 0.338 2 0.337 1 0.324 8 0.321 1 0.309 0 0.306 1 0.305 6 0.302 3 0.296 2
X1∩X4 X3∩X4 X1∩X6 X2∩X4 X3∩X6 X4∩X5 X2∩X6 X4∩X6 X5∩X6 X1∩X2
1995年 0.329 1 0.310 3 0.308 3 0.289 9 0.285 7 0.281 1 0.258 1 0.256 7 0.242 5 0.236 3
X1∩X4 X1∩X6 X3∩X4 X1∩X2 X2∩X4 X3∩X6 X1∩X5 X2∩X6 X2∩X5 X3∩X5
2000年 0.426 6 0.415 2 0.389 1 0.362 6 0.356 0 0.349 3 0.323 3 0.320 0 0.291 1 0.284 4
X1∩X4 X1∩X6 X1∩X5 X1∩X2 X1∩X3 X3∩X4 X2∩X4 X3∩X6 X2∩X6 X4∩X5
2005年 0.437 5 0.434 6 0.420 4 0.412 8 0.393 6 0.386 0 0.383 6 0.377 3 0.369 5 0.334 3
X1∩X4 X3∩X4 X1∩X3 X1∩X6 X3∩X6 X1∩X5 X1∩X2 X2∩X4 X3∩X5 X2∩X6
2010年 0.502 7 0.482 2 0.477 2 0.463 9 0.449 7 0.445 5 0.428 3 0.412 4 0.385 7 0.351 3
X1∩X4 X1∩X6 X1∩X3 X3∩X4 X1∩X5 X1∩X2 X3∩X6 X3∩X5 X2∩X4 X2∩X6
2015年 0.427 2 0.411 6 0.393 9 0.387 5 0.377 1 0.368 5 0.363 5 0.349 6 0.348 5 0.335 2
X1∩X3 X3∩X4 X3∩X6 X1∩X4 X1∩X6 X3∩X5 X1∩X5 X1∩X2 X2∩X3 X2∩X4
2020年 0.410 5 0.404 7 0.410 5 0.382 6 0.369 3 0.354 1 0.342 8 0.339 7 0.321 6 0.293 3
X1∩X3 X1∩X6 X1∩X4 X1∩X5 X1∩X2 X3∩X4 X3∩X6 X2∩X6 X3∩X5 X2∩X3
Tab.5  The q values for factor interaction detection results
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